LostTech.TensorFlow : API Documentation

Type gen_nn_ops

Namespace tensorflow.python.ops.gen_nn_ops

Methods

Properties

Public static methods

Tensor avg_pool(IGraphNodeBase value, IEnumerable<int> ksize, PythonClassContainer strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, ValueTuple<int, object> ksize, PythonClassContainer strides, string padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, ValueTuple<int, object> ksize, object strides, IEnumerable<int> padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, ValueTuple<int, object> ksize, object strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, ValueTuple<int, object> ksize, object strides, PythonClassContainer padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, ValueTuple<int, object> ksize, object strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, ValueTuple<int, object> ksize, object strides, string padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, ValueTuple<int, object> ksize, PythonClassContainer strides, string padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, ValueTuple<int, object> ksize, object strides, string padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, int ksize, PythonClassContainer strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, int ksize, PythonClassContainer strides, PythonClassContainer padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, int ksize, PythonClassContainer strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, int ksize, PythonClassContainer strides, string padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, int ksize, object strides, IEnumerable<int> padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, int ksize, object strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, int ksize, PythonClassContainer strides, IEnumerable<int> padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, int ksize, object strides, PythonClassContainer padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, ValueTuple<int, object> ksize, PythonClassContainer strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, ValueTuple<int, object> ksize, PythonClassContainer strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, IEnumerable<int> ksize, PythonClassContainer strides, IEnumerable<int> padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, IEnumerable<int> ksize, PythonClassContainer strides, PythonClassContainer padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, IEnumerable<int> ksize, PythonClassContainer strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, IEnumerable<int> ksize, PythonClassContainer strides, string padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, int ksize, object strides, string padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, IEnumerable<int> ksize, PythonClassContainer strides, string padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, ValueTuple<int, object> ksize, PythonClassContainer strides, PythonClassContainer padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, int ksize, object strides, string padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, IEnumerable<int> ksize, object strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, IEnumerable<int> ksize, object strides, PythonClassContainer padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, IEnumerable<int> ksize, object strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, IEnumerable<int> ksize, object strides, string padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, IEnumerable<int> ksize, object strides, string padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, ValueTuple<int, object> ksize, PythonClassContainer strides, IEnumerable<int> padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, IEnumerable<int> ksize, object strides, IEnumerable<int> padding, string data_format, PythonFunctionContainer name)

Tensor avg_pool(IGraphNodeBase value, int ksize, object strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool(IGraphNodeBase value, int ksize, PythonClassContainer strides, string padding, string data_format, string name)

object avg_pool_dyn(object value, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name)

object avg_pool_eager_fallback(IGraphNodeBase value, ValueTuple<int, object> ksize, IEnumerable<int> strides, object padding, string data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, int ksize, object strides, object padding, string data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, int ksize, PythonClassContainer strides, object padding, Byte[] data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, int ksize, int strides, object padding, string data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, int ksize, int strides, object padding, Byte[] data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, int ksize, IEnumerable<int> strides, object padding, string data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, int ksize, IEnumerable<int> strides, object padding, Byte[] data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, ValueTuple<int, object> ksize, object strides, object padding, string data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, ValueTuple<int, object> ksize, object strides, object padding, Byte[] data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, int ksize, object strides, object padding, Byte[] data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, ValueTuple<int, object> ksize, PythonClassContainer strides, object padding, string data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, ValueTuple<int, object> ksize, PythonClassContainer strides, object padding, Byte[] data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, int ksize, PythonClassContainer strides, object padding, string data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, ValueTuple<int, object> ksize, int strides, object padding, Byte[] data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, IEnumerable<int> ksize, IEnumerable<int> strides, object padding, Byte[] data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, IEnumerable<int> ksize, IEnumerable<int> strides, object padding, string data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, IEnumerable<int> ksize, int strides, object padding, Byte[] data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, IEnumerable<int> ksize, int strides, object padding, string data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, IEnumerable<int> ksize, PythonClassContainer strides, object padding, Byte[] data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, IEnumerable<int> ksize, PythonClassContainer strides, object padding, string data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, ValueTuple<int, object> ksize, int strides, object padding, string data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, IEnumerable<int> ksize, object strides, object padding, Byte[] data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, IEnumerable<int> ksize, object strides, object padding, string data_format, string name, Context ctx)

object avg_pool_eager_fallback(IGraphNodeBase value, ValueTuple<int, object> ksize, IEnumerable<int> strides, object padding, Byte[] data_format, string name, Context ctx)

object avg_pool_eager_fallback_dyn(object value, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name, object ctx)

Tensor avg_pool_grad(IGraphNodeBase orig_input_shape, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, string data_format, string name)

object avg_pool_grad_dyn(object orig_input_shape, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name)

object avg_pool_grad_eager_fallback(IGraphNodeBase orig_input_shape, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, Byte[] data_format, string name, Context ctx)

object avg_pool_grad_eager_fallback(IGraphNodeBase orig_input_shape, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, Byte[] data_format, string name, Context ctx)

object avg_pool_grad_eager_fallback(IGraphNodeBase orig_input_shape, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, string data_format, string name, Context ctx)

object avg_pool_grad_eager_fallback(IGraphNodeBase orig_input_shape, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, string data_format, string name, Context ctx)

object avg_pool_grad_eager_fallback_dyn(object orig_input_shape, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name, object ctx)

Tensor avg_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, int ksize, int strides, string padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, int ksize, int strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, int ksize, int strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, string padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, string padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, int strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, int strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, string padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, int strides, string padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, int ksize, IEnumerable<int> strides, string padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, string padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, int ksize, IEnumerable<int> strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, int ksize, IEnumerable<int> strides, IEnumerable<int> padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, string padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, PythonClassContainer padding, string data_format, string name)

Tensor avg_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, IEnumerable<int> padding, string data_format, string name)

object avg_pool3d_dyn(object input, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name)

Performs the average pooling on the input.

Each entry in `output` is the mean of the corresponding size `ksize` window in `value`.
Parameters
object input
A 5-D `Tensor` of shape `[batch, height, width, channels]` and type `float32`, `float64`, `qint8`, `quint8`, or `qint32`.
object ksize
An int or list of `ints` that has length `1`, `3` or `5`. The size of the window for each dimension of the input tensor.
object strides
An int or list of `ints` that has length `1`, `3` or `5`. The stride of the sliding window for each dimension of the input tensor.
object padding
A string, either `'VALID'` or `'SAME'`. The padding algorithm. See the "returns" section of tf.nn.convolution for details.
ImplicitContainer<T> data_format
A string. 'NDHWC' and 'NCDHW' are supported.
object name
Optional name for the operation.
Returns
object
A `Tensor` with the same type as `value`. The average pooled output tensor.

object avg_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, int strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, int strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, int strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, int strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, int ksize, int strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, int ksize, int strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, int ksize, int strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, int ksize, int strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, int ksize, IEnumerable<int> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, int ksize, IEnumerable<int> strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, int ksize, IEnumerable<int> strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, int ksize, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object avg_pool3d_eager_fallback_dyn(object input, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name, object ctx)

Tensor avg_pool3d_grad(IGraphNodeBase orig_input_shape, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, string data_format, string name)

object avg_pool3d_grad_dyn(object orig_input_shape, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name)

object avg_pool3d_grad_eager_fallback(IGraphNodeBase orig_input_shape, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, Byte[] data_format, string name, Context ctx)

object avg_pool3d_grad_eager_fallback(IGraphNodeBase orig_input_shape, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, string data_format, string name, Context ctx)

object avg_pool3d_grad_eager_fallback(IGraphNodeBase orig_input_shape, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, Byte[] data_format, string name, Context ctx)

object avg_pool3d_grad_eager_fallback(IGraphNodeBase orig_input_shape, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, string data_format, string name, Context ctx)

object avg_pool3d_grad_eager_fallback_dyn(object orig_input_shape, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name, object ctx)

object batch_norm_with_global_normalization_grad(IGraphNodeBase t, IGraphNodeBase m, IGraphNodeBase v, IGraphNodeBase gamma, IGraphNodeBase backprop, double variance_epsilon, bool scale_after_normalization, string name)

object batch_norm_with_global_normalization_grad_dyn(object t, object m, object v, object gamma, object backprop, object variance_epsilon, object scale_after_normalization, object name)

object batch_norm_with_global_normalization_grad_eager_fallback(IGraphNodeBase t, IGraphNodeBase m, IGraphNodeBase v, IGraphNodeBase gamma, IGraphNodeBase backprop, double variance_epsilon, bool scale_after_normalization, string name, Context ctx)

object batch_norm_with_global_normalization_grad_eager_fallback_dyn(object t, object m, object v, object gamma, object backprop, object variance_epsilon, object scale_after_normalization, object name, object ctx)

Tensor bias_add(IGraphNodeBase value, IGraphNodeBase bias, string data_format, PythonFunctionContainer name)

Adds `bias` to `value`.

This is (mostly) a special case of tf.add where `bias` is restricted to 1-D. Broadcasting is supported, so `value` may have any number of dimensions. Unlike tf.add, the type of `bias` is allowed to differ from `value` in the case where both types are quantized.
Parameters
IGraphNodeBase value
A `Tensor` with type `float`, `double`, `int64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, or `complex128`.
IGraphNodeBase bias
A 1-D `Tensor` with size matching the channel dimension of `value`. Must be the same type as `value` unless `value` is a quantized type, in which case a different quantized type may be used.
string data_format
A string. 'N...C' and 'NC...' are supported.
PythonFunctionContainer name
A name for the operation (optional).
Returns
Tensor
A `Tensor` with the same type as `value`.

Tensor bias_add(IGraphNodeBase value, IGraphNodeBase bias, string data_format, string name)

Adds `bias` to `value`.

This is (mostly) a special case of tf.add where `bias` is restricted to 1-D. Broadcasting is supported, so `value` may have any number of dimensions. Unlike tf.add, the type of `bias` is allowed to differ from `value` in the case where both types are quantized.
Parameters
IGraphNodeBase value
A `Tensor` with type `float`, `double`, `int64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, or `complex128`.
IGraphNodeBase bias
A 1-D `Tensor` with size matching the channel dimension of `value`. Must be the same type as `value` unless `value` is a quantized type, in which case a different quantized type may be used.
string data_format
A string. 'N...C' and 'NC...' are supported.
string name
A name for the operation (optional).
Returns
Tensor
A `Tensor` with the same type as `value`.

object bias_add_dyn(object value, object bias, ImplicitContainer<T> data_format, object name)

object bias_add_eager_fallback(IGraphNodeBase value, IGraphNodeBase bias, Byte[] data_format, string name, Context ctx)

object bias_add_eager_fallback(IGraphNodeBase value, IGraphNodeBase bias, string data_format, string name, Context ctx)

object bias_add_eager_fallback_dyn(object value, object bias, ImplicitContainer<T> data_format, object name, object ctx)

Tensor bias_add_grad(IGraphNodeBase out_backprop, string data_format, string name)

object bias_add_grad_dyn(object out_backprop, ImplicitContainer<T> data_format, object name)

object bias_add_grad_eager_fallback(IGraphNodeBase out_backprop, string data_format, string name, Context ctx)

object bias_add_grad_eager_fallback(IGraphNodeBase out_backprop, Byte[] data_format, string name, Context ctx)

object bias_add_grad_eager_fallback_dyn(object out_backprop, ImplicitContainer<T> data_format, object name, object ctx)

object bias_add_v1_eager_fallback(IGraphNodeBase value, IGraphNodeBase bias, string name, Context ctx)

object bias_add_v1_eager_fallback_dyn(object value, object bias, object name, object ctx)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, object padding, Nullable<bool> use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ValueTuple<int, object> dilations, string name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, object padding, Nullable<bool> use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ValueTuple<int, object> dilations, PythonFunctionContainer name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, object padding, Nullable<bool> use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ImplicitContainer<T> dilations, PythonFunctionContainer name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, object padding, Nullable<bool> use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ValueTuple<int, object> dilations, string name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, object padding, Nullable<bool> use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ImplicitContainer<T> dilations, PythonFunctionContainer name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, PythonFunctionContainer name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ValueTuple<int, object> dilations, string name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ValueTuple<int, object> dilations, PythonFunctionContainer name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, object padding, Nullable<bool> use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ValueTuple<int, object> dilations, PythonFunctionContainer name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, object padding, Nullable<bool> use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, object padding, Nullable<bool> use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ValueTuple<int, object> dilations, PythonFunctionContainer name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ValueTuple<int, object> dilations, string name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, int strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ValueTuple<int, object> dilations, PythonFunctionContainer name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, PythonFunctionContainer name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, int strides, object padding, Nullable<bool> use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, int strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ValueTuple<int, object> dilations, string name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, int strides, object padding, Nullable<bool> use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ImplicitContainer<T> dilations, PythonFunctionContainer name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, int strides, object padding, Nullable<bool> use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ValueTuple<int, object> dilations, string name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, int strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, PythonFunctionContainer name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, int strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, int strides, object padding, Nullable<bool> use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ValueTuple<int, object> dilations, PythonFunctionContainer name)

Tensor conv2d(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, string dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, string dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, object padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, string dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, object padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, object padding, bool use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, string dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, object padding, bool use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, string dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, string dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, string dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, bool use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, string dilations, string name)

Tensor conv2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, bool use_cudnn_on_gpu, IEnumerable<object> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

object conv2d_backprop_filter_dyn(object input, object filter_sizes, object out_backprop, object strides, object padding, ImplicitContainer<T> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, bool use_cudnn_on_gpu, object explicit_paddings, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, object padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, object padding, bool use_cudnn_on_gpu, object explicit_paddings, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, object padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, object explicit_paddings, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, object padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, bool use_cudnn_on_gpu, object explicit_paddings, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, object explicit_paddings, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_filter_eager_fallback_dyn(object input, object filter_sizes, object out_backprop, object strides, object padding, ImplicitContainer<T> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name, object ctx)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, string padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, string strides, object padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, string strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, string strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, string strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, string strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, string strides, object padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, string padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, object padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, string strides, string padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, object padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, object padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, object padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, string strides, string padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv2d_backprop_input(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, object explicit_paddings, string data_format, ImplicitContainer<T> dilations, string name)

object conv2d_backprop_input_dyn(object input_sizes, object filter, object out_backprop, object strides, object padding, ImplicitContainer<T> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, string padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, object padding, bool use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, object padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, Byte[] padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, bool use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, object padding, bool use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, object padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<object> padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, bool use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, Byte[] padding, bool use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, bool use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, string padding, bool use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_backprop_input_eager_fallback_dyn(object input_sizes, object filter, object out_backprop, object strides, object padding, ImplicitContainer<T> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name, object ctx)

object conv2d_dyn(object input, object filter, object strides, object padding, ImplicitContainer<T> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, object padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, ValueTuple<IEnumerable<object>, object> padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, ValueTuple<IEnumerable<object>, object> padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, string padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, ValueTuple<IEnumerable<object>, object> padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, ValueTuple<IEnumerable<object>, object> padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, Byte[] padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, Byte[] padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, string padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, string padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, object padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, IEnumerable<object> padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, object padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, string padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, Byte[] padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, Byte[] padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, string padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, IEnumerable<object> padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, string padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, IEnumerable<object> padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, Byte[] padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, Byte[] padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, IEnumerable<object> padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, ValueTuple<IEnumerable<object>, object> padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, object padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, IEnumerable<object> padding, Nullable<bool> use_cudnn_on_gpu, object explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, ValueTuple<int, object> strides, IEnumerable<object> padding, Nullable<bool> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv2d_eager_fallback_dyn(object input, object filter, object strides, object padding, ImplicitContainer<T> use_cudnn_on_gpu, ImplicitContainer<T> explicit_paddings, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name, object ctx)

Tensor conv3d(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, string padding, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv3d(IGraphNodeBase input, IGraphNodeBase filter, int strides, string padding, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv3d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase out_backprop, object strides, object padding, ImplicitContainer<T> dilations, string name)

object conv3d_backprop_filter_dyn(object input, object filter, object out_backprop, object strides, object padding, ImplicitContainer<T> dilations, object name)

object conv3d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_filter_eager_fallback_dyn(object input, object filter, object out_backprop, object strides, object padding, ImplicitContainer<T> dilations, object name, object ctx)

object conv3d_backprop_filter_v2_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_filter_v2_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_filter_v2_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_filter_v2_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_filter_v2_eager_fallback_dyn(object input, object filter_sizes, object out_backprop, object strides, object padding, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name, object ctx)

Tensor conv3d_backprop_input(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase out_backprop, object strides, object padding, ImplicitContainer<T> dilations, string name)

object conv3d_backprop_input_dyn(object input, object filter, object out_backprop, object strides, object padding, ImplicitContainer<T> dilations, object name)

object conv3d_backprop_input_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_input_eager_fallback_dyn(object input, object filter, object out_backprop, object strides, object padding, ImplicitContainer<T> dilations, object name, object ctx)

Tensor conv3d_backprop_input_v2(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, string padding, string data_format, ImplicitContainer<T> dilations, PythonFunctionContainer name)

Tensor conv3d_backprop_input_v2(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, string padding, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv3d_backprop_input_v2(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, string strides, string padding, string data_format, IEnumerable<double> dilations, PythonFunctionContainer name)

Tensor conv3d_backprop_input_v2(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, string strides, string padding, string data_format, IEnumerable<double> dilations, string name)

Tensor conv3d_backprop_input_v2(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, string strides, string padding, string data_format, ImplicitContainer<T> dilations, PythonFunctionContainer name)

Tensor conv3d_backprop_input_v2(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, string strides, string padding, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv3d_backprop_input_v2(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, string data_format, ImplicitContainer<T> dilations, string name)

Tensor conv3d_backprop_input_v2(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, string padding, string data_format, IEnumerable<double> dilations, string name)

Tensor conv3d_backprop_input_v2(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, string data_format, IEnumerable<double> dilations, PythonFunctionContainer name)

Tensor conv3d_backprop_input_v2(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, string padding, string data_format, IEnumerable<double> dilations, PythonFunctionContainer name)

Tensor conv3d_backprop_input_v2(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, string data_format, IEnumerable<double> dilations, string name)

Tensor conv3d_backprop_input_v2(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, string data_format, ImplicitContainer<T> dilations, PythonFunctionContainer name)

object conv3d_backprop_input_v2_dyn(object input_sizes, object filter, object out_backprop, object strides, object padding, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, string padding, string data_format, IEnumerable<double> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, Byte[] padding, Byte[] data_format, IEnumerable<double> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, string padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, string padding, Byte[] data_format, IEnumerable<double> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, Byte[] padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, Byte[] padding, string data_format, IEnumerable<double> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, Byte[] padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, string data_format, IEnumerable<double> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, int strides, string padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, Byte[] data_format, IEnumerable<double> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, string data_format, IEnumerable<double> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, string padding, Byte[] data_format, IEnumerable<double> dilations, string name, Context ctx)

object conv3d_backprop_input_v2_eager_fallback_dyn(object input_sizes, object filter, object out_backprop, object strides, object padding, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name, object ctx)

object conv3d_dyn(object input, object filter, object strides, object padding, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name)

object conv3d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, string padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, Byte[] padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, string padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, string padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, Byte[] padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, string padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, int strides, Byte[] padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, Byte[] padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object conv3d_eager_fallback_dyn(object input, object filter, object strides, object padding, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name, object ctx)

Tensor data_format_dim_map(IGraphNodeBase x, string src_format, string dst_format, string name)

object data_format_dim_map_dyn(object x, ImplicitContainer<T> src_format, ImplicitContainer<T> dst_format, object name)

object data_format_dim_map_eager_fallback(IGraphNodeBase x, string src_format, Byte[] dst_format, string name, Context ctx)

object data_format_dim_map_eager_fallback(IGraphNodeBase x, string src_format, string dst_format, string name, Context ctx)

object data_format_dim_map_eager_fallback(IGraphNodeBase x, Byte[] src_format, string dst_format, string name, Context ctx)

object data_format_dim_map_eager_fallback(IGraphNodeBase x, Byte[] src_format, Byte[] dst_format, string name, Context ctx)

object data_format_dim_map_eager_fallback_dyn(object x, ImplicitContainer<T> src_format, ImplicitContainer<T> dst_format, object name, object ctx)

Tensor data_format_vec_permute(IGraphNodeBase x, string src_format, string dst_format, string name)

object data_format_vec_permute_dyn(object x, ImplicitContainer<T> src_format, ImplicitContainer<T> dst_format, object name)

object data_format_vec_permute_eager_fallback(IGraphNodeBase x, Byte[] src_format, string dst_format, string name, Context ctx)

object data_format_vec_permute_eager_fallback(IGraphNodeBase x, Byte[] src_format, Byte[] dst_format, string name, Context ctx)

object data_format_vec_permute_eager_fallback(IGraphNodeBase x, string src_format, string dst_format, string name, Context ctx)

object data_format_vec_permute_eager_fallback(IGraphNodeBase x, string src_format, Byte[] dst_format, string name, Context ctx)

object data_format_vec_permute_eager_fallback_dyn(object x, ImplicitContainer<T> src_format, ImplicitContainer<T> dst_format, object name, object ctx)

object depthwise_conv2d_native_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object depthwise_conv2d_native_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter_sizes, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object depthwise_conv2d_native_backprop_filter_eager_fallback_dyn(object input, object filter_sizes, object out_backprop, object strides, object padding, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name, object ctx)

object depthwise_conv2d_native_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object depthwise_conv2d_native_backprop_input_eager_fallback(IGraphNodeBase input_sizes, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, Byte[] padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object depthwise_conv2d_native_backprop_input_eager_fallback_dyn(object input_sizes, object filter, object out_backprop, object strides, object padding, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name, object ctx)

object depthwise_conv2d_native_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, IEnumerable<int> padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object depthwise_conv2d_native_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, string padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object depthwise_conv2d_native_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, string padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object depthwise_conv2d_native_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, Byte[] padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object depthwise_conv2d_native_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, Byte[] padding, Byte[] data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object depthwise_conv2d_native_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, string padding, IEnumerable<int> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object depthwise_conv2d_native_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, IEnumerable<int> padding, IEnumerable<int> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object depthwise_conv2d_native_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, Byte[] padding, IEnumerable<int> data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object depthwise_conv2d_native_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, IEnumerable<int> padding, string data_format, ImplicitContainer<T> dilations, string name, Context ctx)

object depthwise_conv2d_native_eager_fallback_dyn(object input, object filter, object strides, object padding, ImplicitContainer<T> data_format, ImplicitContainer<T> dilations, object name, object ctx)

Tensor dilation2d(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, IEnumerable<int> rates, string padding, string name)

Tensor dilation2d(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, IEnumerable<int> rates, string padding, PythonFunctionContainer name)

Tensor dilation2d_backprop_filter(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase out_backprop, object strides, object rates, object padding, string name)

object dilation2d_backprop_filter_dyn(object input, object filter, object out_backprop, object strides, object rates, object padding, object name)

object dilation2d_backprop_filter_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<int> rates, Byte[] padding, string name, Context ctx)

object dilation2d_backprop_filter_eager_fallback_dyn(object input, object filter, object out_backprop, object strides, object rates, object padding, object name, object ctx)

Tensor dilation2d_backprop_input(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase out_backprop, object strides, object rates, object padding, string name)

object dilation2d_backprop_input_dyn(object input, object filter, object out_backprop, object strides, object rates, object padding, object name)

object dilation2d_backprop_input_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase out_backprop, IEnumerable<int> strides, IEnumerable<int> rates, Byte[] padding, string name, Context ctx)

object dilation2d_backprop_input_eager_fallback_dyn(object input, object filter, object out_backprop, object strides, object rates, object padding, object name, object ctx)

object dilation2d_dyn(object input, object filter, object strides, object rates, object padding, object name)

object dilation2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, IEnumerable<int> rates, Byte[] padding, string name, Context ctx)

object dilation2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IEnumerable<int> strides, IEnumerable<int> rates, string padding, string name, Context ctx)

object dilation2d_eager_fallback_dyn(object input, object filter, object strides, object rates, object padding, object name, object ctx)

object elu_eager_fallback(IGraphNodeBase features, string name, Context ctx)

object elu_eager_fallback_dyn(object features, object name, object ctx)

Tensor elu_grad(IGraphNodeBase gradients, IGraphNodeBase outputs, string name)

object elu_grad_dyn(object gradients, object outputs, object name)

object elu_grad_eager_fallback(IGraphNodeBase gradients, IGraphNodeBase outputs, string name, Context ctx)

object elu_grad_eager_fallback_dyn(object gradients, object outputs, object name, object ctx)

object fractional_avg_pool(IGraphNodeBase value, ValueTuple<int, double, object, object> pooling_ratio, bool pseudo_random, bool overlapping, bool deterministic, int seed, int seed2, string name)

object fractional_avg_pool(IGraphNodeBase value, IEnumerable<double> pooling_ratio, bool pseudo_random, bool overlapping, bool deterministic, int seed, int seed2, string name)

object fractional_avg_pool_dyn(object value, object pooling_ratio, ImplicitContainer<T> pseudo_random, ImplicitContainer<T> overlapping, ImplicitContainer<T> deterministic, ImplicitContainer<T> seed, ImplicitContainer<T> seed2, object name)

Performs fractional average pooling on the input. (deprecated)

Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: `seed2` and `deterministic` args are deprecated. Use fractional_avg_pool_v2.

This is a deprecated version of `fractional_avg_pool`.

Fractional average pooling is similar to Fractional max pooling in the pooling region generation step. The only difference is that after pooling regions are generated, a mean operation is performed instead of a max operation in each pooling region.
Parameters
object value
A `Tensor`. 4-D with shape `[batch, height, width, channels]`.
object pooling_ratio
A list of `floats` that has length >= 4. Pooling ratio for each dimension of `value`, currently only supports row and col dimension and should be >= 1.0. For example, a valid pooling ratio looks like [1.0, 1.44, 1.73, 1.0]. The first and last elements must be 1.0 because we don't allow pooling on batch and channels dimensions. 1.44 and 1.73 are pooling ratio on height and width dimensions respectively.
ImplicitContainer<T> pseudo_random
An optional `bool`. Defaults to `False`. When set to `True`, generates the pooling sequence in a pseudorandom fashion, otherwise, in a random fashion. Check paper [Benjamin Graham, Fractional Max-Pooling](http://arxiv.org/abs/1412.6071) for difference between pseudorandom and random.
ImplicitContainer<T> overlapping
An optional `bool`. Defaults to `False`. When set to `True`, it means when pooling, the values at the boundary of adjacent pooling cells are used by both cells. For example: `index 0 1 2 3 4` `value 20 5 16 3 7` If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice. The result would be [20, 16] for fractional avg pooling.
ImplicitContainer<T> deterministic
An optional `bool`. Deprecated; use `fractional_avg_pool_v2` instead.
ImplicitContainer<T> seed
An optional `int`. Defaults to `0`. If set to be non-zero, the random number generator is seeded by the given seed. Otherwise it is seeded by a random seed.
ImplicitContainer<T> seed2
An optional `int`. Deprecated; use `fractional_avg_pool_v2` instead.
object name
A name for the operation (optional).
Returns
object
A tuple of `Tensor` objects (`output`, `row_pooling_sequence`, `col_pooling_sequence`).

object fractional_avg_pool_eager_fallback(IGraphNodeBase value, ValueTuple<int, double, object, object> pooling_ratio, bool pseudo_random, bool overlapping, bool deterministic, int seed, int seed2, string name, Context ctx)

object fractional_avg_pool_eager_fallback(IGraphNodeBase value, IEnumerable<double> pooling_ratio, bool pseudo_random, bool overlapping, bool deterministic, int seed, int seed2, string name, Context ctx)

object fractional_avg_pool_eager_fallback_dyn(object value, object pooling_ratio, ImplicitContainer<T> pseudo_random, ImplicitContainer<T> overlapping, ImplicitContainer<T> deterministic, ImplicitContainer<T> seed, ImplicitContainer<T> seed2, object name, object ctx)

Tensor fractional_avg_pool_grad(IGraphNodeBase orig_input_tensor_shape, IGraphNodeBase out_backprop, IGraphNodeBase row_pooling_sequence, IGraphNodeBase col_pooling_sequence, bool overlapping, string name)

object fractional_avg_pool_grad_dyn(object orig_input_tensor_shape, object out_backprop, object row_pooling_sequence, object col_pooling_sequence, ImplicitContainer<T> overlapping, object name)

object fractional_avg_pool_grad_eager_fallback(IGraphNodeBase orig_input_tensor_shape, IGraphNodeBase out_backprop, IGraphNodeBase row_pooling_sequence, IGraphNodeBase col_pooling_sequence, bool overlapping, string name, Context ctx)

object fractional_avg_pool_grad_eager_fallback_dyn(object orig_input_tensor_shape, object out_backprop, object row_pooling_sequence, object col_pooling_sequence, ImplicitContainer<T> overlapping, object name, object ctx)

object fractional_max_pool(IGraphNodeBase value, IEnumerable<double> pooling_ratio, bool pseudo_random, bool overlapping, bool deterministic, int seed, int seed2, string name)

object fractional_max_pool(IGraphNodeBase value, ValueTuple<int, double, object, object> pooling_ratio, bool pseudo_random, bool overlapping, bool deterministic, int seed, int seed2, string name)

object fractional_max_pool_dyn(object value, object pooling_ratio, ImplicitContainer<T> pseudo_random, ImplicitContainer<T> overlapping, ImplicitContainer<T> deterministic, ImplicitContainer<T> seed, ImplicitContainer<T> seed2, object name)

Performs fractional max pooling on the input. (deprecated)

Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: `seed2` and `deterministic` args are deprecated. Use fractional_max_pool_v2.

This is a deprecated version of `fractional_max_pool`.

Fractional max pooling is slightly different than regular max pooling. In regular max pooling, you downsize an input set by taking the maximum value of smaller N x N subsections of the set (often 2x2), and try to reduce the set by a factor of N, where N is an integer. Fractional max pooling, as you might expect from the word "fractional", means that the overall reduction ratio N does not have to be an integer.

The sizes of the pooling regions are generated randomly but are fairly uniform. For example, let's look at the height dimension, and the constraints on the list of rows that will be pool boundaries.

First we define the following:

1. input_row_length : the number of rows from the input set 2. output_row_length : which will be smaller than the input 3. alpha = input_row_length / output_row_length : our reduction ratio 4. K = floor(alpha) 5. row_pooling_sequence : this is the result list of pool boundary rows

Then, row_pooling_sequence should satisfy:

1. a[0] = 0 : the first value of the sequence is 0 2. a[end] = input_row_length : the last value of the sequence is the size 3. K <= (a[i+1] - a[i]) <= K+1 : all intervals are K or K+1 size 4. length(row_pooling_sequence) = output_row_length+1

For more details on fractional max pooling, see this paper: [Benjamin Graham, Fractional Max-Pooling](http://arxiv.org/abs/1412.6071)
Parameters
object value
A `Tensor`. 4-D with shape `[batch, height, width, channels]`.
object pooling_ratio
A list of `floats` that has length >= 4. Pooling ratio for each dimension of `value`, currently only supports row and col dimension and should be >= 1.0. For example, a valid pooling ratio looks like [1.0, 1.44, 1.73, 1.0]. The first and last elements must be 1.0 because we don't allow pooling on batch and channels dimensions. 1.44 and 1.73 are pooling ratio on height and width dimensions respectively.
ImplicitContainer<T> pseudo_random
An optional `bool`. Defaults to `False`. When set to `True`, generates the pooling sequence in a pseudorandom fashion, otherwise, in a random fashion. Check paper [Benjamin Graham, Fractional Max-Pooling](http://arxiv.org/abs/1412.6071) for difference between pseudorandom and random.
ImplicitContainer<T> overlapping
An optional `bool`. Defaults to `False`. When set to `True`, it means when pooling, the values at the boundary of adjacent pooling cells are used by both cells. For example: `index 0 1 2 3 4` `value 20 5 16 3 7` If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice. The result would be [20, 16] for fractional max pooling.
ImplicitContainer<T> deterministic
An optional `bool`. Deprecated; use `fractional_max_pool_v2` instead.
ImplicitContainer<T> seed
An optional `int`. Defaults to `0`. If set to be non-zero, the random number generator is seeded by the given seed. Otherwise it is seeded by a random seed.
ImplicitContainer<T> seed2
An optional `int`. Deprecated; use `fractional_max_pool_v2` instead.
object name
A name for the operation (optional).
Returns
object
A tuple of `Tensor` objects (`output`, `row_pooling_sequence`, `col_pooling_sequence`).

object fractional_max_pool_eager_fallback(IGraphNodeBase value, ValueTuple<int, double, object, object> pooling_ratio, bool pseudo_random, bool overlapping, bool deterministic, int seed, int seed2, string name, Context ctx)

object fractional_max_pool_eager_fallback(IGraphNodeBase value, IEnumerable<double> pooling_ratio, bool pseudo_random, bool overlapping, bool deterministic, int seed, int seed2, string name, Context ctx)

object fractional_max_pool_eager_fallback_dyn(object value, object pooling_ratio, ImplicitContainer<T> pseudo_random, ImplicitContainer<T> overlapping, ImplicitContainer<T> deterministic, ImplicitContainer<T> seed, ImplicitContainer<T> seed2, object name, object ctx)

Tensor fractional_max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase out_backprop, IGraphNodeBase row_pooling_sequence, IGraphNodeBase col_pooling_sequence, bool overlapping, string name)

object fractional_max_pool_grad_dyn(object orig_input, object orig_output, object out_backprop, object row_pooling_sequence, object col_pooling_sequence, ImplicitContainer<T> overlapping, object name)

object fractional_max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase out_backprop, IGraphNodeBase row_pooling_sequence, IGraphNodeBase col_pooling_sequence, bool overlapping, string name, Context ctx)

object fractional_max_pool_grad_eager_fallback_dyn(object orig_input, object orig_output, object out_backprop, object row_pooling_sequence, object col_pooling_sequence, ImplicitContainer<T> overlapping, object name, object ctx)

object fused_batch_norm_grad(IGraphNodeBase y_backprop, IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase reserve_space_1, IGraphNodeBase reserve_space_2, double epsilon, string data_format, bool is_training, string name)

object fused_batch_norm_grad_dyn(object y_backprop, object x, object scale, object reserve_space_1, object reserve_space_2, ImplicitContainer<T> epsilon, ImplicitContainer<T> data_format, ImplicitContainer<T> is_training, object name)

object fused_batch_norm_grad_eager_fallback(IGraphNodeBase y_backprop, IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase reserve_space_1, IGraphNodeBase reserve_space_2, double epsilon, Byte[] data_format, bool is_training, string name, Context ctx)

object fused_batch_norm_grad_eager_fallback(IGraphNodeBase y_backprop, IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase reserve_space_1, IGraphNodeBase reserve_space_2, double epsilon, string data_format, bool is_training, string name, Context ctx)

object fused_batch_norm_grad_eager_fallback_dyn(object y_backprop, object x, object scale, object reserve_space_1, object reserve_space_2, ImplicitContainer<T> epsilon, ImplicitContainer<T> data_format, ImplicitContainer<T> is_training, object name, object ctx)

object fused_batch_norm_grad_v2(IGraphNodeBase y_backprop, IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase reserve_space_1, IGraphNodeBase reserve_space_2, double epsilon, string data_format, bool is_training, string name)

object fused_batch_norm_grad_v2_dyn(object y_backprop, object x, object scale, object reserve_space_1, object reserve_space_2, ImplicitContainer<T> epsilon, ImplicitContainer<T> data_format, ImplicitContainer<T> is_training, object name)

object fused_batch_norm_grad_v2_eager_fallback(IGraphNodeBase y_backprop, IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase reserve_space_1, IGraphNodeBase reserve_space_2, double epsilon, Byte[] data_format, bool is_training, string name, Context ctx)

object fused_batch_norm_grad_v2_eager_fallback(IGraphNodeBase y_backprop, IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase reserve_space_1, IGraphNodeBase reserve_space_2, double epsilon, string data_format, bool is_training, string name, Context ctx)

object fused_batch_norm_grad_v2_eager_fallback_dyn(object y_backprop, object x, object scale, object reserve_space_1, object reserve_space_2, ImplicitContainer<T> epsilon, ImplicitContainer<T> data_format, ImplicitContainer<T> is_training, object name, object ctx)

object fused_batch_norm_grad_v3(IGraphNodeBase y_backprop, IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase reserve_space_1, IGraphNodeBase reserve_space_2, IGraphNodeBase reserve_space_3, double epsilon, string data_format, bool is_training, string name)

object fused_batch_norm_grad_v3_dyn(object y_backprop, object x, object scale, object reserve_space_1, object reserve_space_2, object reserve_space_3, ImplicitContainer<T> epsilon, ImplicitContainer<T> data_format, ImplicitContainer<T> is_training, object name)

object fused_batch_norm_grad_v3_eager_fallback(IGraphNodeBase y_backprop, IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase reserve_space_1, IGraphNodeBase reserve_space_2, IGraphNodeBase reserve_space_3, double epsilon, Byte[] data_format, bool is_training, string name, Context ctx)

object fused_batch_norm_grad_v3_eager_fallback(IGraphNodeBase y_backprop, IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase reserve_space_1, IGraphNodeBase reserve_space_2, IGraphNodeBase reserve_space_3, double epsilon, string data_format, bool is_training, string name, Context ctx)

object fused_batch_norm_grad_v3_eager_fallback_dyn(object y_backprop, object x, object scale, object reserve_space_1, object reserve_space_2, object reserve_space_3, ImplicitContainer<T> epsilon, ImplicitContainer<T> data_format, ImplicitContainer<T> is_training, object name, object ctx)

object fused_batch_norm_v2(IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase offset, IGraphNodeBase mean, IGraphNodeBase variance, double epsilon, string data_format, bool is_training, string name)

object fused_batch_norm_v2_dyn(object x, object scale, object offset, object mean, object variance, ImplicitContainer<T> epsilon, ImplicitContainer<T> data_format, ImplicitContainer<T> is_training, object name)

object fused_batch_norm_v2_eager_fallback(IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase offset, IGraphNodeBase mean, IGraphNodeBase variance, double epsilon, string data_format, bool is_training, string name, Context ctx)

object fused_batch_norm_v2_eager_fallback(IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase offset, IGraphNodeBase mean, IGraphNodeBase variance, double epsilon, Byte[] data_format, bool is_training, string name, Context ctx)

object fused_batch_norm_v2_eager_fallback_dyn(object x, object scale, object offset, object mean, object variance, ImplicitContainer<T> epsilon, ImplicitContainer<T> data_format, ImplicitContainer<T> is_training, object name, object ctx)

object fused_batch_norm_v3(IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase offset, IGraphNodeBase mean, IGraphNodeBase variance, double epsilon, string data_format, bool is_training, string name)

object fused_batch_norm_v3_dyn(object x, object scale, object offset, object mean, object variance, ImplicitContainer<T> epsilon, ImplicitContainer<T> data_format, ImplicitContainer<T> is_training, object name)

object fused_batch_norm_v3_eager_fallback(IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase offset, IGraphNodeBase mean, IGraphNodeBase variance, double epsilon, string data_format, bool is_training, string name, Context ctx)

object fused_batch_norm_v3_eager_fallback(IGraphNodeBase x, IGraphNodeBase scale, IGraphNodeBase offset, IGraphNodeBase mean, IGraphNodeBase variance, double epsilon, Byte[] data_format, bool is_training, string name, Context ctx)

object fused_batch_norm_v3_eager_fallback_dyn(object x, object scale, object offset, object mean, object variance, ImplicitContainer<T> epsilon, ImplicitContainer<T> data_format, ImplicitContainer<T> is_training, object name, object ctx)

Tensor fused_pad_conv2d(IGraphNodeBase input, IGraphNodeBase paddings, IGraphNodeBase filter, object mode, object strides, object padding, string name)

object fused_pad_conv2d_dyn(object input, object paddings, object filter, object mode, object strides, object padding, object name)

object fused_pad_conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase paddings, IGraphNodeBase filter, Byte[] mode, IEnumerable<int> strides, Byte[] padding, string name, Context ctx)

object fused_pad_conv2d_eager_fallback_dyn(object input, object paddings, object filter, object mode, object strides, object padding, object name, object ctx)

Tensor fused_resize_and_pad_conv2d(IGraphNodeBase input, IGraphNodeBase size, IGraphNodeBase paddings, IGraphNodeBase filter, object mode, object strides, object padding, bool resize_align_corners, string name)

object fused_resize_and_pad_conv2d_dyn(object input, object size, object paddings, object filter, object mode, object strides, object padding, ImplicitContainer<T> resize_align_corners, object name)

object fused_resize_and_pad_conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase size, IGraphNodeBase paddings, IGraphNodeBase filter, Byte[] mode, IEnumerable<int> strides, Byte[] padding, bool resize_align_corners, string name, Context ctx)

object fused_resize_and_pad_conv2d_eager_fallback_dyn(object input, object size, object paddings, object filter, object mode, object strides, object padding, ImplicitContainer<T> resize_align_corners, object name, object ctx)

Tensor in_top_k(IGraphNodeBase predictions, IGraphNodeBase targets, IGraphNodeBase k, string name)

Says whether the targets are in the top `K` predictions.

This outputs a `batch_size` bool array, an entry `out[i]` is `true` if the prediction for the target class is finite (not inf, -inf, or nan) and among the top `k` predictions among all predictions for example `i`. Note that the behavior of `InTopK` differs from the `TopK` op in its handling of ties; if multiple classes have the same prediction value and straddle the top-`k` boundary, all of those classes are considered to be in the top `k`.

More formally, let

\\(predictions_i\\) be the predictions for all classes for example `i`, \\(targets_i\\) be the target class for example `i`, \\(out_i\\) be the output for example `i`,

$$out_i = predictions_{i, targets_i} \in TopKIncludingTies(predictions_i)$$
Parameters
IGraphNodeBase predictions
A `Tensor` of type `float32`. A `batch_size` x `classes` tensor.
IGraphNodeBase targets
A `Tensor`. Must be one of the following types: `int32`, `int64`. A `batch_size` vector of class ids.
IGraphNodeBase k
An `int`. Number of top elements to look at for computing precision.
string name
A name for the operation (optional).
Returns
Tensor
A `Tensor` of type `bool`. Computed Precision at `k` as a `bool Tensor`.

Tensor in_top_k(IGraphNodeBase predictions, IGraphNodeBase targets, int k, string name)

Says whether the targets are in the top `K` predictions.

This outputs a `batch_size` bool array, an entry `out[i]` is `true` if the prediction for the target class is finite (not inf, -inf, or nan) and among the top `k` predictions among all predictions for example `i`. Note that the behavior of `InTopK` differs from the `TopK` op in its handling of ties; if multiple classes have the same prediction value and straddle the top-`k` boundary, all of those classes are considered to be in the top `k`.

More formally, let

\\(predictions_i\\) be the predictions for all classes for example `i`, \\(targets_i\\) be the target class for example `i`, \\(out_i\\) be the output for example `i`,

$$out_i = predictions_{i, targets_i} \in TopKIncludingTies(predictions_i)$$
Parameters
IGraphNodeBase predictions
A `Tensor` of type `float32`. A `batch_size` x `classes` tensor.
IGraphNodeBase targets
A `Tensor`. Must be one of the following types: `int32`, `int64`. A `batch_size` vector of class ids.
int k
An `int`. Number of top elements to look at for computing precision.
string name
A name for the operation (optional).
Returns
Tensor
A `Tensor` of type `bool`. Computed Precision at `k` as a `bool Tensor`.

object in_top_k_eager_fallback(IGraphNodeBase predictions, IGraphNodeBase targets, IGraphNodeBase k, string name, Context ctx)

object in_top_k_eager_fallback(IGraphNodeBase predictions, IGraphNodeBase targets, int k, string name, Context ctx)

object in_top_k_eager_fallback_dyn(object predictions, object targets, object k, object name, object ctx)

Tensor in_top_kv2(IGraphNodeBase predictions, IGraphNodeBase targets, IGraphNodeBase k, string name)

object in_top_kv2_dyn(object predictions, object targets, object k, object name)

object in_top_kv2_eager_fallback(IGraphNodeBase predictions, IGraphNodeBase targets, IGraphNodeBase k, string name, Context ctx)

object in_top_kv2_eager_fallback_dyn(object predictions, object targets, object k, object name, object ctx)

object l2_loss_eager_fallback(IGraphNodeBase t, string name, Context ctx)

object l2_loss_eager_fallback_dyn(object t, object name, object ctx)

Tensor leaky_relu(IGraphNodeBase features, ndarray alpha, PythonFunctionContainer name)

Tensor leaky_relu(IGraphNodeBase features, double alpha, PythonFunctionContainer name)

Tensor leaky_relu(IGraphNodeBase features, int alpha, string name)

Compute the Leaky ReLU activation function.

Source: [Rectifier Nonlinearities Improve Neural Network Acoustic Models. AL Maas, AY Hannun, AY Ng - Proc. ICML, 2013](https://ai.stanford.edu/~amaas/papers/relu_hybrid_icml2013_final.pdf).
Parameters
IGraphNodeBase features
A `Tensor` representing preactivation values. Must be one of the following types: `float16`, `float32`, `float64`, `int32`, `int64`.
int alpha
Slope of the activation function at x < 0.
string name
A name for the operation (optional).
Returns
Tensor
The activation value.

Tensor leaky_relu(IGraphNodeBase features, double alpha, string name)

Compute the Leaky ReLU activation function.

Source: [Rectifier Nonlinearities Improve Neural Network Acoustic Models. AL Maas, AY Hannun, AY Ng - Proc. ICML, 2013](https://ai.stanford.edu/~amaas/papers/relu_hybrid_icml2013_final.pdf).
Parameters
IGraphNodeBase features
A `Tensor` representing preactivation values. Must be one of the following types: `float16`, `float32`, `float64`, `int32`, `int64`.
double alpha
Slope of the activation function at x < 0.
string name
A name for the operation (optional).
Returns
Tensor
The activation value.

Tensor leaky_relu(IGraphNodeBase features, int alpha, PythonFunctionContainer name)

Tensor leaky_relu(IGraphNodeBase features, ndarray alpha, string name)

Compute the Leaky ReLU activation function.

Source: [Rectifier Nonlinearities Improve Neural Network Acoustic Models. AL Maas, AY Hannun, AY Ng - Proc. ICML, 2013](https://ai.stanford.edu/~amaas/papers/relu_hybrid_icml2013_final.pdf).
Parameters
IGraphNodeBase features
A `Tensor` representing preactivation values. Must be one of the following types: `float16`, `float32`, `float64`, `int32`, `int64`.
ndarray alpha
Slope of the activation function at x < 0.
string name
A name for the operation (optional).
Returns
Tensor
The activation value.

object leaky_relu_dyn(object features, ImplicitContainer<T> alpha, object name)

Compute the Leaky ReLU activation function.

Source: [Rectifier Nonlinearities Improve Neural Network Acoustic Models. AL Maas, AY Hannun, AY Ng - Proc. ICML, 2013](https://ai.stanford.edu/~amaas/papers/relu_hybrid_icml2013_final.pdf).
Parameters
object features
A `Tensor` representing preactivation values. Must be one of the following types: `float16`, `float32`, `float64`, `int32`, `int64`.
ImplicitContainer<T> alpha
Slope of the activation function at x < 0.
object name
A name for the operation (optional).
Returns
object
The activation value.

object leaky_relu_eager_fallback(IGraphNodeBase features, double alpha, string name, Context ctx)

object leaky_relu_eager_fallback(IGraphNodeBase features, ndarray alpha, string name, Context ctx)

object leaky_relu_eager_fallback(IGraphNodeBase features, int alpha, string name, Context ctx)

object leaky_relu_eager_fallback_dyn(object features, ImplicitContainer<T> alpha, object name, object ctx)

Tensor leaky_relu_grad(IGraphNodeBase gradients, IGraphNodeBase features, double alpha, string name)

object leaky_relu_grad_dyn(object gradients, object features, ImplicitContainer<T> alpha, object name)

object leaky_relu_grad_eager_fallback(IGraphNodeBase gradients, IGraphNodeBase features, double alpha, string name, Context ctx)

object leaky_relu_grad_eager_fallback_dyn(object gradients, object features, ImplicitContainer<T> alpha, object name, object ctx)

Tensor log_softmax(IGraphNodeBase logits, string name)

object log_softmax_dyn(object logits, object name)

object log_softmax_eager_fallback(IGraphNodeBase logits, string name, Context ctx)

object log_softmax_eager_fallback_dyn(object logits, object name, object ctx)

object lrn_eager_fallback(IGraphNodeBase input, int depth_radius, double bias, double alpha, double beta, string name, Context ctx)

object lrn_eager_fallback(IGraphNodeBase input, int depth_radius, double bias, int alpha, double beta, string name, Context ctx)

object lrn_eager_fallback(IGraphNodeBase input, int depth_radius, int bias, double alpha, double beta, string name, Context ctx)

object lrn_eager_fallback(IGraphNodeBase input, int depth_radius, int bias, int alpha, double beta, string name, Context ctx)

object lrn_eager_fallback_dyn(object input, ImplicitContainer<T> depth_radius, ImplicitContainer<T> bias, ImplicitContainer<T> alpha, ImplicitContainer<T> beta, object name, object ctx)

Tensor lrn_grad(IGraphNodeBase input_grads, IGraphNodeBase input_image, IGraphNodeBase output_image, int depth_radius, int bias, int alpha, double beta, string name)

object lrn_grad_dyn(object input_grads, object input_image, object output_image, ImplicitContainer<T> depth_radius, ImplicitContainer<T> bias, ImplicitContainer<T> alpha, ImplicitContainer<T> beta, object name)

object lrn_grad_eager_fallback(IGraphNodeBase input_grads, IGraphNodeBase input_image, IGraphNodeBase output_image, int depth_radius, double bias, int alpha, double beta, string name, Context ctx)

object lrn_grad_eager_fallback(IGraphNodeBase input_grads, IGraphNodeBase input_image, IGraphNodeBase output_image, int depth_radius, double bias, double alpha, double beta, string name, Context ctx)

object lrn_grad_eager_fallback(IGraphNodeBase input_grads, IGraphNodeBase input_image, IGraphNodeBase output_image, int depth_radius, int bias, int alpha, double beta, string name, Context ctx)

object lrn_grad_eager_fallback(IGraphNodeBase input_grads, IGraphNodeBase input_image, IGraphNodeBase output_image, int depth_radius, int bias, double alpha, double beta, string name, Context ctx)

object lrn_grad_eager_fallback_dyn(object input_grads, object input_image, object output_image, ImplicitContainer<T> depth_radius, ImplicitContainer<T> bias, ImplicitContainer<T> alpha, ImplicitContainer<T> beta, object name, object ctx)

Tensor max_pool(IGraphNodeBase input, int ksize, PythonClassContainer strides, string padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, PythonClassContainer strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, IEnumerable<int> ksize, PythonClassContainer strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, int ksize, object strides, string padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, IEnumerable<int> ksize, object strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, IEnumerable<int> ksize, object strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, IEnumerable<int> ksize, object strides, string padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, int ksize, object strides, string padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, IEnumerable<int> ksize, object strides, PythonClassContainer padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, int ksize, object strides, PythonClassContainer padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, IEnumerable<int> ksize, PythonClassContainer strides, string padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, int ksize, PythonClassContainer strides, string padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, IEnumerable<int> ksize, object strides, IEnumerable<int> padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, int ksize, object strides, IEnumerable<int> padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, IEnumerable<int> ksize, object strides, string padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, int ksize, object strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, IEnumerable<int> ksize, PythonClassContainer strides, string padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, PythonClassContainer strides, IEnumerable<int> padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, int ksize, PythonClassContainer strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, object strides, IEnumerable<int> padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, int ksize, object strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, int ksize, PythonClassContainer strides, IEnumerable<int> padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, int ksize, PythonClassContainer strides, PythonClassContainer padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, object strides, string padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, IEnumerable<int> ksize, PythonClassContainer strides, IEnumerable<int> padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, object strides, string padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, PythonClassContainer strides, string padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, PythonClassContainer strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, object strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, PythonClassContainer strides, string padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, IEnumerable<int> ksize, PythonClassContainer strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, PythonClassContainer strides, PythonClassContainer padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, int ksize, PythonClassContainer strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool(IGraphNodeBase input, IEnumerable<int> ksize, PythonClassContainer strides, PythonClassContainer padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, object strides, PythonClassContainer padding, string data_format, PythonFunctionContainer name)

Tensor max_pool(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, object strides, IEnumerable<int> padding, string data_format, string name)

object max_pool_dyn(object input, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name)

object max_pool_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, object padding, Byte[] data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, object padding, string data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, int ksize, object strides, object padding, string data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, int ksize, object strides, object padding, Byte[] data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, int ksize, PythonClassContainer strides, object padding, Byte[] data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, int strides, object padding, Byte[] data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, int ksize, int strides, object padding, string data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, int ksize, int strides, object padding, Byte[] data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, int strides, object padding, string data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, object strides, object padding, Byte[] data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, int ksize, IEnumerable<int> strides, object padding, Byte[] data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, int ksize, PythonClassContainer strides, object padding, string data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, int ksize, IEnumerable<int> strides, object padding, string data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, object strides, object padding, Byte[] data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, object strides, object padding, string data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, PythonClassContainer strides, object padding, Byte[] data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, IEnumerable<int> strides, object padding, Byte[] data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, int strides, object padding, Byte[] data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, int strides, object padding, string data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, IEnumerable<int> strides, object padding, string data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, PythonClassContainer strides, object padding, Byte[] data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, PythonClassContainer strides, object padding, string data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, PythonClassContainer strides, object padding, string data_format, string name, Context ctx)

object max_pool_eager_fallback(IGraphNodeBase input, ValueTuple<int, int, object, object> ksize, object strides, object padding, string data_format, string name, Context ctx)

object max_pool_eager_fallback_dyn(object input, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name, object ctx)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IGraphNodeBase strides, string padding, IEnumerable<double> data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, PythonClassContainer strides, string padding, IEnumerable<double> data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, string strides, string padding, string data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IGraphNodeBase strides, string padding, string data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, PythonClassContainer strides, string padding, IEnumerable<double> data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, string strides, string padding, IEnumerable<double> data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IEnumerable<int> strides, string padding, IEnumerable<double> data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, IEnumerable<double> data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, string data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IGraphNodeBase strides, string padding, string data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, string strides, string padding, string data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, PythonClassContainer strides, string padding, string data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IGraphNodeBase strides, string padding, IEnumerable<double> data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, string strides, string padding, IEnumerable<double> data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, PythonClassContainer strides, string padding, string data_format, string name)

Tensor max_pool_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IEnumerable<int> strides, string padding, string data_format, string name)

object max_pool_grad_dyn(object orig_input, object orig_output, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, string strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, string strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IEnumerable<int> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, PythonClassContainer strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IGraphNodeBase strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IGraphNodeBase strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IGraphNodeBase strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IGraphNodeBase strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, string strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, string strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, PythonClassContainer strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, PythonClassContainer strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, PythonClassContainer strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool_grad_eager_fallback_dyn(object orig_input, object orig_output, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name, object ctx)

Tensor max_pool_grad_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<object> ksize, IEnumerable<object> strides, object padding, string data_format, string name)

object max_pool_grad_grad_dyn(object orig_input, object orig_output, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name)

object max_pool_grad_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, string data_format, string name, Context ctx)

object max_pool_grad_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, Byte[] data_format, string name, Context ctx)

object max_pool_grad_grad_eager_fallback_dyn(object orig_input, object orig_output, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name, object ctx)

Tensor max_pool_grad_grad_v2(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IGraphNodeBase strides, object padding, string data_format, string name)

object max_pool_grad_grad_v2_dyn(object orig_input, object orig_output, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name)

object max_pool_grad_grad_v2_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IGraphNodeBase strides, Byte[] padding, string data_format, string name, Context ctx)

object max_pool_grad_grad_v2_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IGraphNodeBase strides, Byte[] padding, Byte[] data_format, string name, Context ctx)

object max_pool_grad_grad_v2_eager_fallback_dyn(object orig_input, object orig_output, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name, object ctx)

Tensor max_pool_grad_grad_with_argmax(IGraphNodeBase input, IGraphNodeBase grad, IGraphNodeBase argmax, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, bool include_batch_in_index, string name)

object max_pool_grad_grad_with_argmax_dyn(object input, object grad, object argmax, object ksize, object strides, object padding, ImplicitContainer<T> include_batch_in_index, object name)

object max_pool_grad_grad_with_argmax_eager_fallback(IGraphNodeBase input, IGraphNodeBase grad, IGraphNodeBase argmax, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, bool include_batch_in_index, string name, Context ctx)

object max_pool_grad_grad_with_argmax_eager_fallback(IGraphNodeBase input, IGraphNodeBase grad, IGraphNodeBase argmax, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, bool include_batch_in_index, string name, Context ctx)

object max_pool_grad_grad_with_argmax_eager_fallback_dyn(object input, object grad, object argmax, object ksize, object strides, object padding, ImplicitContainer<T> include_batch_in_index, object name, object ctx)

Tensor max_pool_grad_v2(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IGraphNodeBase strides, string padding, string data_format, string name)

object max_pool_grad_v2_dyn(object orig_input, object orig_output, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name)

object max_pool_grad_v2_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IGraphNodeBase strides, string padding, string data_format, string name, Context ctx)

object max_pool_grad_v2_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IGraphNodeBase strides, Byte[] padding, string data_format, string name, Context ctx)

object max_pool_grad_v2_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IGraphNodeBase strides, string padding, Byte[] data_format, string name, Context ctx)

object max_pool_grad_v2_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IGraphNodeBase ksize, IGraphNodeBase strides, Byte[] padding, Byte[] data_format, string name, Context ctx)

object max_pool_grad_v2_eager_fallback_dyn(object orig_input, object orig_output, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name, object ctx)

Tensor max_pool_grad_with_argmax(IGraphNodeBase input, IGraphNodeBase grad, IGraphNodeBase argmax, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, bool include_batch_in_index, string name)

object max_pool_grad_with_argmax_dyn(object input, object grad, object argmax, object ksize, object strides, object padding, ImplicitContainer<T> include_batch_in_index, object name)

object max_pool_grad_with_argmax_eager_fallback(IGraphNodeBase input, IGraphNodeBase grad, IGraphNodeBase argmax, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, bool include_batch_in_index, string name, Context ctx)

object max_pool_grad_with_argmax_eager_fallback(IGraphNodeBase input, IGraphNodeBase grad, IGraphNodeBase argmax, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, bool include_batch_in_index, string name, Context ctx)

object max_pool_grad_with_argmax_eager_fallback_dyn(object input, object grad, object argmax, object ksize, object strides, object padding, ImplicitContainer<T> include_batch_in_index, object name, object ctx)

Tensor max_pool_v2(IGraphNodeBase input, IGraphNodeBase ksize, IGraphNodeBase strides, string padding, string data_format, string name)

object max_pool_v2_dyn(object input, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name)

object max_pool_v2_eager_fallback(IGraphNodeBase input, IGraphNodeBase ksize, IGraphNodeBase strides, Byte[] padding, Byte[] data_format, string name, Context ctx)

object max_pool_v2_eager_fallback(IGraphNodeBase input, IGraphNodeBase ksize, IGraphNodeBase strides, string padding, string data_format, string name, Context ctx)

object max_pool_v2_eager_fallback(IGraphNodeBase input, IGraphNodeBase ksize, IGraphNodeBase strides, string padding, Byte[] data_format, string name, Context ctx)

object max_pool_v2_eager_fallback(IGraphNodeBase input, IGraphNodeBase ksize, IGraphNodeBase strides, Byte[] padding, string data_format, string name, Context ctx)

object max_pool_v2_eager_fallback_dyn(object input, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name, object ctx)

object max_pool_with_argmax(IGraphNodeBase input, IEnumerable<double> ksize, IEnumerable<double> strides, string padding, ImplicitContainer<T> Targmax, bool include_batch_in_index, string name)

object max_pool_with_argmax_dyn(object input, object ksize, object strides, object padding, ImplicitContainer<T> Targmax, ImplicitContainer<T> include_batch_in_index, object name)

object max_pool_with_argmax_eager_fallback(IGraphNodeBase input, IEnumerable<double> ksize, IEnumerable<double> strides, Byte[] padding, ImplicitContainer<T> Targmax, bool include_batch_in_index, string name, Context ctx)

object max_pool_with_argmax_eager_fallback(IGraphNodeBase input, IEnumerable<double> ksize, IEnumerable<double> strides, string padding, int Targmax, bool include_batch_in_index, string name, Context ctx)

object max_pool_with_argmax_eager_fallback(IGraphNodeBase input, IEnumerable<double> ksize, IEnumerable<double> strides, Byte[] padding, int Targmax, bool include_batch_in_index, string name, Context ctx)

object max_pool_with_argmax_eager_fallback(IGraphNodeBase input, IEnumerable<double> ksize, IEnumerable<double> strides, string padding, ImplicitContainer<T> Targmax, bool include_batch_in_index, string name, Context ctx)

object max_pool_with_argmax_eager_fallback_dyn(object input, object ksize, object strides, object padding, ImplicitContainer<T> Targmax, ImplicitContainer<T> include_batch_in_index, object name, object ctx)

Tensor max_pool3d(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, int ksize, int strides, string padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, int ksize, int strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, string padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, string padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, int strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, int strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, int strides, string padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, int ksize, int strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, string padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, string padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, int ksize, IEnumerable<int> strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, int ksize, IEnumerable<int> strides, PythonClassContainer padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, IEnumerable<int> padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, int ksize, IEnumerable<int> strides, string padding, string data_format, string name)

Tensor max_pool3d(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, string padding, string data_format, string name)

object max_pool3d_dyn(object input, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name)

Performs the max pooling on the input.
Parameters
object input
A 5-D `Tensor` of the format specified by `data_format`.
object ksize
An int or list of `ints` that has length `1`, `3` or `5`. The size of the window for each dimension of the input tensor.
object strides
An int or list of `ints` that has length `1`, `3` or `5`. The stride of the sliding window for each dimension of the input tensor.
object padding
A string, either `'VALID'` or `'SAME'`. The padding algorithm. See the "returns" section of tf.nn.convolution for details.
ImplicitContainer<T> data_format
An optional string from: "NDHWC", "NCDHW". Defaults to "NDHWC". The data format of the input and output data. With the default format "NDHWC", the data is stored in the order of: [batch, in_depth, in_height, in_width, in_channels]. Alternatively, the format could be "NCDHW", the data storage order is: [batch, in_channels, in_depth, in_height, in_width].
object name
A name for the operation (optional).
Returns
object
A `Tensor` of format specified by `data_format`. The max pooled output tensor.

object max_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, int strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, int ksize, int strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, int ksize, int strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, int ksize, int strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, int ksize, int strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, int ksize, ValueTuple<int, object, object> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, int ksize, IEnumerable<int> strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, int ksize, IEnumerable<int> strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, int ksize, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, int strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, int ksize, IEnumerable<int> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, int strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, ValueTuple<int, object, object> strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, int strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, ValueTuple<int, object, object> strides, Byte[] padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, int strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, IEnumerable<int> ksize, IEnumerable<int> strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, IEnumerable<int> padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback(IGraphNodeBase input, ValueTuple<int, object, object> ksize, IEnumerable<int> strides, PythonClassContainer padding, ImplicitContainer<T> data_format, string name, Context ctx)

object max_pool3d_eager_fallback_dyn(object input, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name, object ctx)

Tensor max_pool3d_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, string data_format, string name)

object max_pool3d_grad_dyn(object orig_input, object orig_output, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name)

object max_pool3d_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, string data_format, string name, Context ctx)

object max_pool3d_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, Byte[] data_format, string name, Context ctx)

object max_pool3d_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, string data_format, string name, Context ctx)

object max_pool3d_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, Byte[] data_format, string name, Context ctx)

object max_pool3d_grad_eager_fallback_dyn(object orig_input, object orig_output, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name, object ctx)

Tensor max_pool3d_grad_grad(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, string data_format, string name)

object max_pool3d_grad_grad_dyn(object orig_input, object orig_output, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name)

object max_pool3d_grad_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, string data_format, string name, Context ctx)

object max_pool3d_grad_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, Byte[] data_format, string name, Context ctx)

object max_pool3d_grad_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, string padding, string data_format, string name, Context ctx)

object max_pool3d_grad_grad_eager_fallback(IGraphNodeBase orig_input, IGraphNodeBase orig_output, IGraphNodeBase grad, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, Byte[] data_format, string name, Context ctx)

object max_pool3d_grad_grad_eager_fallback_dyn(object orig_input, object orig_output, object grad, object ksize, object strides, object padding, ImplicitContainer<T> data_format, object name, object ctx)

object nth_element_eager_fallback(IGraphNodeBase input, IGraphNodeBase n, bool reverse, string name, Context ctx)

object nth_element_eager_fallback_dyn(object input, object n, ImplicitContainer<T> reverse, object name, object ctx)

object quantized_avg_pool_eager_fallback(IGraphNodeBase input, IGraphNodeBase min_input, IGraphNodeBase max_input, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, string name, Context ctx)

object quantized_avg_pool_eager_fallback_dyn(object input, object min_input, object max_input, object ksize, object strides, object padding, object name, object ctx)

object quantized_batch_norm_with_global_normalization(IGraphNodeBase t, IGraphNodeBase t_min, IGraphNodeBase t_max, IGraphNodeBase m, IGraphNodeBase m_min, IGraphNodeBase m_max, IGraphNodeBase v, IGraphNodeBase v_min, IGraphNodeBase v_max, IGraphNodeBase beta, IGraphNodeBase beta_min, IGraphNodeBase beta_max, IGraphNodeBase gamma, IGraphNodeBase gamma_min, IGraphNodeBase gamma_max, object out_type, object variance_epsilon, object scale_after_normalization, string name)

object quantized_batch_norm_with_global_normalization_dyn(object t, object t_min, object t_max, object m, object m_min, object m_max, object v, object v_min, object v_max, object beta, object beta_min, object beta_max, object gamma, object gamma_min, object gamma_max, object out_type, object variance_epsilon, object scale_after_normalization, object name)

object quantized_batch_norm_with_global_normalization_eager_fallback(IGraphNodeBase t, IGraphNodeBase t_min, IGraphNodeBase t_max, IGraphNodeBase m, IGraphNodeBase m_min, IGraphNodeBase m_max, IGraphNodeBase v, IGraphNodeBase v_min, IGraphNodeBase v_max, IGraphNodeBase beta, IGraphNodeBase beta_min, IGraphNodeBase beta_max, IGraphNodeBase gamma, IGraphNodeBase gamma_min, IGraphNodeBase gamma_max, int out_type, double variance_epsilon, object scale_after_normalization, string name, Context ctx)

object quantized_batch_norm_with_global_normalization_eager_fallback_dyn(object t, object t_min, object t_max, object m, object m_min, object m_max, object v, object v_min, object v_max, object beta, object beta_min, object beta_max, object gamma, object gamma_min, object gamma_max, object out_type, object variance_epsilon, object scale_after_normalization, object name, object ctx)

object quantized_bias_add(IGraphNodeBase input, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_bias, IGraphNodeBase max_bias, object out_type, string name)

object quantized_bias_add_dyn(object input, object bias, object min_input, object max_input, object min_bias, object max_bias, object out_type, object name)

object quantized_bias_add_eager_fallback(IGraphNodeBase input, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_bias, IGraphNodeBase max_bias, int out_type, string name, Context ctx)

object quantized_bias_add_eager_fallback_dyn(object input, object bias, object min_input, object max_input, object min_bias, object max_bias, object out_type, object name, object ctx)

object quantized_conv2d_and_relu(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name)

object quantized_conv2d_and_relu_and_requantize(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name)

object quantized_conv2d_and_relu_and_requantize_dyn(object input, object filter, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name)

object quantized_conv2d_and_relu_and_requantize_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name, Context ctx)

object quantized_conv2d_and_relu_and_requantize_eager_fallback_dyn(object input, object filter, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name, object ctx)

object quantized_conv2d_and_relu_dyn(object input, object filter, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name)

object quantized_conv2d_and_relu_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name, Context ctx)

object quantized_conv2d_and_relu_eager_fallback_dyn(object input, object filter, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name, object ctx)

object quantized_conv2d_and_requantize(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name)

object quantized_conv2d_and_requantize_dyn(object input, object filter, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name)

object quantized_conv2d_and_requantize_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name, Context ctx)

object quantized_conv2d_and_requantize_eager_fallback_dyn(object input, object filter, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name, object ctx)

object quantized_conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IEnumerable<int> strides, string padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, string name, Context ctx)

object quantized_conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, string name, Context ctx)

object quantized_conv2d_eager_fallback_dyn(object input, object filter, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, object name, object ctx)

object quantized_conv2d_per_channel(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, string name)

object quantized_conv2d_per_channel_dyn(object input, object filter, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, object name)

object quantized_conv2d_per_channel_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, string name, Context ctx)

object quantized_conv2d_per_channel_eager_fallback_dyn(object input, object filter, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, object name, object ctx)

object quantized_conv2d_with_bias(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name)

object quantized_conv2d_with_bias_and_relu(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name)

object quantized_conv2d_with_bias_and_relu_and_requantize(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name)

object quantized_conv2d_with_bias_and_relu_and_requantize_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name)

object quantized_conv2d_with_bias_and_relu_and_requantize_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name, Context ctx)

object quantized_conv2d_with_bias_and_relu_and_requantize_eager_fallback_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name, object ctx)

object quantized_conv2d_with_bias_and_relu_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name)

object quantized_conv2d_with_bias_and_relu_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name, Context ctx)

object quantized_conv2d_with_bias_and_relu_eager_fallback_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name, object ctx)

object quantized_conv2d_with_bias_and_requantize(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name)

object quantized_conv2d_with_bias_and_requantize_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name)

object quantized_conv2d_with_bias_and_requantize_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name, Context ctx)

object quantized_conv2d_with_bias_and_requantize_eager_fallback_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name, object ctx)

object quantized_conv2d_with_bias_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name)

object quantized_conv2d_with_bias_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name, Context ctx)

object quantized_conv2d_with_bias_eager_fallback_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name, object ctx)

object quantized_conv2d_with_bias_signed_sum_and_relu_and_requantize(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, IGraphNodeBase summand, IGraphNodeBase min_summand, IGraphNodeBase max_summand, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name)

object quantized_conv2d_with_bias_signed_sum_and_relu_and_requantize_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object summand, object min_summand, object max_summand, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name)

object quantized_conv2d_with_bias_signed_sum_and_relu_and_requantize_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, IGraphNodeBase summand, IGraphNodeBase min_summand, IGraphNodeBase max_summand, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name, Context ctx)

object quantized_conv2d_with_bias_signed_sum_and_relu_and_requantize_eager_fallback_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object summand, object min_summand, object max_summand, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name, object ctx)

object quantized_conv2d_with_bias_sum_and_relu(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase summand, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name)

object quantized_conv2d_with_bias_sum_and_relu_and_requantize(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, IGraphNodeBase summand, IGraphNodeBase min_summand, IGraphNodeBase max_summand, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name)

object quantized_conv2d_with_bias_sum_and_relu_and_requantize_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object summand, object min_summand, object max_summand, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name)

object quantized_conv2d_with_bias_sum_and_relu_and_requantize_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, IGraphNodeBase summand, IGraphNodeBase min_summand, IGraphNodeBase max_summand, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name, Context ctx)

object quantized_conv2d_with_bias_sum_and_relu_and_requantize_eager_fallback_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object summand, object min_summand, object max_summand, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name, object ctx)

object quantized_conv2d_with_bias_sum_and_relu_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object summand, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name)

object quantized_conv2d_with_bias_sum_and_relu_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase summand, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, string name, Context ctx)

object quantized_conv2d_with_bias_sum_and_relu_eager_fallback_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object summand, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, ImplicitContainer<T> padding_list, object name, object ctx)

object quantized_depthwise_conv2d(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, string name)

object quantized_depthwise_conv2d_dyn(object input, object filter, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, object name)

object quantized_depthwise_conv2d_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, string name, Context ctx)

object quantized_depthwise_conv2d_eager_fallback_dyn(object input, object filter, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, object name, object ctx)

object quantized_depthwise_conv2d_with_bias(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, string name)

object quantized_depthwise_conv2d_with_bias_and_relu(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, string name)

object quantized_depthwise_conv2d_with_bias_and_relu_and_requantize(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, string name)

object quantized_depthwise_conv2d_with_bias_and_relu_and_requantize_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, object name)

object quantized_depthwise_conv2d_with_bias_and_relu_and_requantize_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, string name, Context ctx)

object quantized_depthwise_conv2d_with_bias_and_relu_and_requantize_eager_fallback_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object min_freezed_output, object max_freezed_output, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, object name, object ctx)

object quantized_depthwise_conv2d_with_bias_and_relu_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, object name)

object quantized_depthwise_conv2d_with_bias_and_relu_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, string name, Context ctx)

object quantized_depthwise_conv2d_with_bias_and_relu_eager_fallback_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, object name, object ctx)

object quantized_depthwise_conv2d_with_bias_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, object name)

object quantized_depthwise_conv2d_with_bias_eager_fallback(IGraphNodeBase input, IGraphNodeBase filter, IGraphNodeBase bias, IGraphNodeBase min_input, IGraphNodeBase max_input, IGraphNodeBase min_filter, IGraphNodeBase max_filter, IEnumerable<int> strides, Byte[] padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, string name, Context ctx)

object quantized_depthwise_conv2d_with_bias_eager_fallback_dyn(object input, object filter, object bias, object min_input, object max_input, object min_filter, object max_filter, object strides, object padding, ImplicitContainer<T> out_type, ImplicitContainer<T> dilations, object name, object ctx)

object quantized_mat_mul_with_bias(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, ImplicitContainer<T> Toutput, bool transpose_a, bool transpose_b, string input_quant_mode, string name)

object quantized_mat_mul_with_bias_and_relu(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, ImplicitContainer<T> Toutput, bool transpose_a, bool transpose_b, string input_quant_mode, string name)

object quantized_mat_mul_with_bias_and_relu_and_requantize(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, ImplicitContainer<T> Toutput, bool transpose_a, bool transpose_b, string input_quant_mode, string name)

object quantized_mat_mul_with_bias_and_relu_and_requantize_dyn(object a, object b, object bias, object min_a, object max_a, object min_b, object max_b, object min_freezed_output, object max_freezed_output, ImplicitContainer<T> Toutput, ImplicitContainer<T> transpose_a, ImplicitContainer<T> transpose_b, ImplicitContainer<T> input_quant_mode, object name)

object quantized_mat_mul_with_bias_and_relu_and_requantize_eager_fallback(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, ImplicitContainer<T> Toutput, bool transpose_a, bool transpose_b, Byte[] input_quant_mode, string name, Context ctx)

object quantized_mat_mul_with_bias_and_relu_and_requantize_eager_fallback(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, int Toutput, bool transpose_a, bool transpose_b, Byte[] input_quant_mode, string name, Context ctx)

object quantized_mat_mul_with_bias_and_relu_and_requantize_eager_fallback(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, ImplicitContainer<T> Toutput, bool transpose_a, bool transpose_b, string input_quant_mode, string name, Context ctx)

object quantized_mat_mul_with_bias_and_relu_and_requantize_eager_fallback(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, IGraphNodeBase min_freezed_output, IGraphNodeBase max_freezed_output, int Toutput, bool transpose_a, bool transpose_b, string input_quant_mode, string name, Context ctx)

object quantized_mat_mul_with_bias_and_relu_and_requantize_eager_fallback_dyn(object a, object b, object bias, object min_a, object max_a, object min_b, object max_b, object min_freezed_output, object max_freezed_output, ImplicitContainer<T> Toutput, ImplicitContainer<T> transpose_a, ImplicitContainer<T> transpose_b, ImplicitContainer<T> input_quant_mode, object name, object ctx)

object quantized_mat_mul_with_bias_and_relu_dyn(object a, object b, object bias, object min_a, object max_a, object min_b, object max_b, ImplicitContainer<T> Toutput, ImplicitContainer<T> transpose_a, ImplicitContainer<T> transpose_b, ImplicitContainer<T> input_quant_mode, object name)

object quantized_mat_mul_with_bias_and_relu_eager_fallback(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, int Toutput, bool transpose_a, bool transpose_b, Byte[] input_quant_mode, string name, Context ctx)

object quantized_mat_mul_with_bias_and_relu_eager_fallback(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, int Toutput, bool transpose_a, bool transpose_b, string input_quant_mode, string name, Context ctx)

object quantized_mat_mul_with_bias_and_relu_eager_fallback(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, ImplicitContainer<T> Toutput, bool transpose_a, bool transpose_b, string input_quant_mode, string name, Context ctx)

object quantized_mat_mul_with_bias_and_relu_eager_fallback(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, ImplicitContainer<T> Toutput, bool transpose_a, bool transpose_b, Byte[] input_quant_mode, string name, Context ctx)

object quantized_mat_mul_with_bias_and_relu_eager_fallback_dyn(object a, object b, object bias, object min_a, object max_a, object min_b, object max_b, ImplicitContainer<T> Toutput, ImplicitContainer<T> transpose_a, ImplicitContainer<T> transpose_b, ImplicitContainer<T> input_quant_mode, object name, object ctx)

object quantized_mat_mul_with_bias_dyn(object a, object b, object bias, object min_a, object max_a, object min_b, object max_b, ImplicitContainer<T> Toutput, ImplicitContainer<T> transpose_a, ImplicitContainer<T> transpose_b, ImplicitContainer<T> input_quant_mode, object name)

object quantized_mat_mul_with_bias_eager_fallback(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, ImplicitContainer<T> Toutput, bool transpose_a, bool transpose_b, Byte[] input_quant_mode, string name, Context ctx)

object quantized_mat_mul_with_bias_eager_fallback(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, int Toutput, bool transpose_a, bool transpose_b, Byte[] input_quant_mode, string name, Context ctx)

object quantized_mat_mul_with_bias_eager_fallback(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, int Toutput, bool transpose_a, bool transpose_b, string input_quant_mode, string name, Context ctx)

object quantized_mat_mul_with_bias_eager_fallback(IGraphNodeBase a, IGraphNodeBase b, IGraphNodeBase bias, IGraphNodeBase min_a, IGraphNodeBase max_a, IGraphNodeBase min_b, IGraphNodeBase max_b, ImplicitContainer<T> Toutput, bool transpose_a, bool transpose_b, string input_quant_mode, string name, Context ctx)

object quantized_mat_mul_with_bias_eager_fallback_dyn(object a, object b, object bias, object min_a, object max_a, object min_b, object max_b, ImplicitContainer<T> Toutput, ImplicitContainer<T> transpose_a, ImplicitContainer<T> transpose_b, ImplicitContainer<T> input_quant_mode, object name, object ctx)

object quantized_max_pool_eager_fallback(IGraphNodeBase input, IGraphNodeBase min_input, IGraphNodeBase max_input, IEnumerable<int> ksize, IEnumerable<int> strides, Byte[] padding, string name, Context ctx)

object quantized_max_pool_eager_fallback_dyn(object input, object min_input, object max_input, object ksize, object strides, object padding, object name, object ctx)

object quantized_relu(IGraphNodeBase features, IGraphNodeBase min_features, IGraphNodeBase max_features, ImplicitContainer<T> out_type, string name)

object quantized_relu_dyn(object features, object min_features, object max_features, ImplicitContainer<T> out_type, object name)

object quantized_relu_eager_fallback(IGraphNodeBase features, IGraphNodeBase min_features, IGraphNodeBase max_features, ImplicitContainer<T> out_type, string name, Context ctx)

object quantized_relu_eager_fallback_dyn(object features, object min_features, object max_features, ImplicitContainer<T> out_type, object name, object ctx)

object quantized_relu_x_eager_fallback(IGraphNodeBase features, IGraphNodeBase max_value, IGraphNodeBase min_features, IGraphNodeBase max_features, ImplicitContainer<T> out_type, string name, Context ctx)

object quantized_relu_x_eager_fallback_dyn(object features, object max_value, object min_features, object max_features, ImplicitContainer<T> out_type, object name, object ctx)

object quantized_relu6(IGraphNodeBase features, IGraphNodeBase min_features, IGraphNodeBase max_features, ImplicitContainer<T> out_type, string name)

object quantized_relu6_dyn(object features, object min_features, object max_features, ImplicitContainer<T> out_type, object name)

object quantized_relu6_eager_fallback(IGraphNodeBase features, IGraphNodeBase min_features, IGraphNodeBase max_features, ImplicitContainer<T> out_type, string name, Context ctx)

object quantized_relu6_eager_fallback_dyn(object features, object min_features, object max_features, ImplicitContainer<T> out_type, object name, object ctx)

object relu_eager_fallback(IGraphNodeBase features, string name, Context ctx)

object relu_eager_fallback_dyn(object features, object name, object ctx)

Tensor relu_grad(IGraphNodeBase gradients, IGraphNodeBase features, string name)

object relu_grad_dyn(object gradients, object features, object name)

object relu_grad_eager_fallback(IGraphNodeBase gradients, IGraphNodeBase features, string name, Context ctx)

object relu_grad_eager_fallback_dyn(object gradients, object features, object name, object ctx)

Tensor relu6(IGraphNodeBase features, string name)

Computes Rectified Linear 6: `min(max(features, 0), 6)`.

Source: [Convolutional Deep Belief Networks on CIFAR-10. A. Krizhevsky](http://www.cs.utoronto.ca/~kriz/conv-cifar10-aug2010.pdf)
Parameters
IGraphNodeBase features
A `Tensor` with type `float`, `double`, `int32`, `int64`, `uint8`, `int16`, or `int8`.
string name
A name for the operation (optional).
Returns
Tensor
A `Tensor` with the same type as `features`.

object relu6_dyn(object features, object name)

Computes Rectified Linear 6: `min(max(features, 0), 6)`.

Source: [Convolutional Deep Belief Networks on CIFAR-10. A. Krizhevsky](http://www.cs.utoronto.ca/~kriz/conv-cifar10-aug2010.pdf)
Parameters
object features
A `Tensor` with type `float`, `double`, `int32`, `int64`, `uint8`, `int16`, or `int8`.
object name
A name for the operation (optional).
Returns
object
A `Tensor` with the same type as `features`.

object relu6_eager_fallback(IGraphNodeBase features, string name, Context ctx)

object relu6_eager_fallback_dyn(object features, object name, object ctx)

Tensor relu6_grad(IGraphNodeBase gradients, IGraphNodeBase features, string name)

object relu6_grad_dyn(object gradients, object features, object name)

object relu6_grad_eager_fallback(IGraphNodeBase gradients, IGraphNodeBase features, string name, Context ctx)

object relu6_grad_eager_fallback_dyn(object gradients, object features, object name, object ctx)

object selu_eager_fallback(IGraphNodeBase features, string name, Context ctx)

object selu_eager_fallback_dyn(object features, object name, object ctx)

Tensor selu_grad(IGraphNodeBase gradients, IGraphNodeBase outputs, string name)

object selu_grad_dyn(object gradients, object outputs, object name)

object selu_grad_eager_fallback(IGraphNodeBase gradients, IGraphNodeBase outputs, string name, Context ctx)

object selu_grad_eager_fallback_dyn(object gradients, object outputs, object name, object ctx)

object softmax_cross_entropy_with_logits(IGraphNodeBase features, IGraphNodeBase labels, string name)

object softmax_cross_entropy_with_logits(IGraphNodeBase features, IGraphNodeBase labels, PythonFunctionContainer name)

object softmax_cross_entropy_with_logits_dyn(object features, object labels, object name)

object softmax_cross_entropy_with_logits_eager_fallback(IGraphNodeBase features, IGraphNodeBase labels, string name, Context ctx)

object softmax_cross_entropy_with_logits_eager_fallback_dyn(object features, object labels, object name, object ctx)

object softmax_eager_fallback(IGraphNodeBase logits, string name, Context ctx)

object softmax_eager_fallback_dyn(object logits, object name, object ctx)

object softplus_eager_fallback(IGraphNodeBase features, string name, Context ctx)

object softplus_eager_fallback_dyn(object features, object name, object ctx)

Tensor softplus_grad(IGraphNodeBase gradients, IGraphNodeBase features, string name)

object softplus_grad_dyn(object gradients, object features, object name)

object softplus_grad_eager_fallback(IGraphNodeBase gradients, IGraphNodeBase features, string name, Context ctx)

object softplus_grad_eager_fallback_dyn(object gradients, object features, object name, object ctx)

object softsign_eager_fallback(IGraphNodeBase features, string name, Context ctx)

object softsign_eager_fallback_dyn(object features, object name, object ctx)

Tensor softsign_grad(IGraphNodeBase gradients, IGraphNodeBase features, string name)

object softsign_grad_dyn(object gradients, object features, object name)

object softsign_grad_eager_fallback(IGraphNodeBase gradients, IGraphNodeBase features, string name, Context ctx)

object softsign_grad_eager_fallback_dyn(object gradients, object features, object name, object ctx)

object sparse_softmax_cross_entropy_with_logits_eager_fallback(IGraphNodeBase features, IGraphNodeBase labels, string name, Context ctx)

object sparse_softmax_cross_entropy_with_logits_eager_fallback_dyn(object features, object labels, object name, object ctx)

object top_k(IGraphNodeBase input, IGraphNodeBase k, bool sorted, string name)

object top_k(IGraphNodeBase input, int k, bool sorted, string name)

object top_k_dyn(object input, object k, ImplicitContainer<T> sorted, object name)

object top_k_eager_fallback(IGraphNodeBase input, IGraphNodeBase k, bool sorted, string name, Context ctx)

object top_k_eager_fallback(IGraphNodeBase input, int k, bool sorted, string name, Context ctx)

object top_k_eager_fallback_dyn(object input, object k, ImplicitContainer<T> sorted, object name, object ctx)

object top_kv2(IGraphNodeBase input, IGraphNodeBase k, bool sorted, string name)

object top_kv2_dyn(object input, object k, ImplicitContainer<T> sorted, object name)

object top_kv2_eager_fallback(IGraphNodeBase input, IGraphNodeBase k, bool sorted, string name, Context ctx)

object top_kv2_eager_fallback_dyn(object input, object k, ImplicitContainer<T> sorted, object name, object ctx)

Public properties

PythonFunctionContainer avg_pool_eager_fallback_fn get;

PythonFunctionContainer avg_pool_fn get;

PythonFunctionContainer avg_pool_grad_eager_fallback_fn get;

PythonFunctionContainer avg_pool_grad_fn get;

PythonFunctionContainer avg_pool3d_eager_fallback_fn get;

PythonFunctionContainer avg_pool3d_fn get;

PythonFunctionContainer avg_pool3d_grad_eager_fallback_fn get;

PythonFunctionContainer avg_pool3d_grad_fn get;

PythonFunctionContainer batch_norm_with_global_normalization_grad_eager_fallback_fn get;

PythonFunctionContainer batch_norm_with_global_normalization_grad_fn get;

PythonFunctionContainer bias_add_eager_fallback_fn get;

PythonFunctionContainer bias_add_fn get;

PythonFunctionContainer bias_add_grad_eager_fallback_fn get;

PythonFunctionContainer bias_add_grad_fn get;

PythonFunctionContainer bias_add_v1_eager_fallback_fn get;

PythonFunctionContainer bias_add_v1_fn get;

PythonFunctionContainer conv2d_backprop_filter_eager_fallback_fn get;

PythonFunctionContainer conv2d_backprop_filter_fn get;

PythonFunctionContainer conv2d_backprop_input_eager_fallback_fn get;

PythonFunctionContainer conv2d_backprop_input_fn get;

PythonFunctionContainer conv2d_eager_fallback_fn get;

PythonFunctionContainer conv2d_fn get;

PythonFunctionContainer conv3d_backprop_filter_eager_fallback_fn get;

PythonFunctionContainer conv3d_backprop_filter_fn get;

PythonFunctionContainer conv3d_backprop_filter_v2_eager_fallback_fn get;

PythonFunctionContainer conv3d_backprop_input_eager_fallback_fn get;

PythonFunctionContainer conv3d_backprop_input_fn get;

PythonFunctionContainer conv3d_backprop_input_v2_eager_fallback_fn get;

PythonFunctionContainer conv3d_backprop_input_v2_fn get;

PythonFunctionContainer conv3d_eager_fallback_fn get;

PythonFunctionContainer conv3d_fn get;

PythonFunctionContainer data_format_dim_map_eager_fallback_fn get;

PythonFunctionContainer data_format_dim_map_fn get;

PythonFunctionContainer data_format_vec_permute_eager_fallback_fn get;

PythonFunctionContainer data_format_vec_permute_fn get;

PythonFunctionContainer depthwise_conv2d_native_backprop_filter_eager_fallback_fn get;

PythonFunctionContainer depthwise_conv2d_native_backprop_input_eager_fallback_fn get;

PythonFunctionContainer depthwise_conv2d_native_eager_fallback_fn get;

PythonFunctionContainer dilation2d_backprop_filter_eager_fallback_fn get;

PythonFunctionContainer dilation2d_backprop_filter_fn get;

PythonFunctionContainer dilation2d_backprop_input_eager_fallback_fn get;

PythonFunctionContainer dilation2d_backprop_input_fn get;

PythonFunctionContainer dilation2d_eager_fallback_fn get;

PythonFunctionContainer dilation2d_fn get;

PythonFunctionContainer elu_eager_fallback_fn get;

PythonFunctionContainer elu_grad_eager_fallback_fn get;

PythonFunctionContainer elu_grad_fn get;

PythonFunctionContainer fractional_avg_pool_eager_fallback_fn get;

PythonFunctionContainer fractional_avg_pool_fn get;

PythonFunctionContainer fractional_avg_pool_grad_eager_fallback_fn get;

PythonFunctionContainer fractional_avg_pool_grad_fn get;

PythonFunctionContainer fractional_max_pool_eager_fallback_fn get;

PythonFunctionContainer fractional_max_pool_fn get;

PythonFunctionContainer fractional_max_pool_grad_eager_fallback_fn get;

PythonFunctionContainer fractional_max_pool_grad_fn get;

PythonFunctionContainer fused_batch_norm_grad_eager_fallback_fn get;

PythonFunctionContainer fused_batch_norm_grad_fn get;

PythonFunctionContainer fused_batch_norm_grad_v2_eager_fallback_fn get;

PythonFunctionContainer fused_batch_norm_grad_v2_fn get;

PythonFunctionContainer fused_batch_norm_grad_v3_eager_fallback_fn get;

PythonFunctionContainer fused_batch_norm_grad_v3_fn get;

PythonFunctionContainer fused_batch_norm_v2_eager_fallback_fn get;

PythonFunctionContainer fused_batch_norm_v2_fn get;

PythonFunctionContainer fused_batch_norm_v3_eager_fallback_fn get;

PythonFunctionContainer fused_batch_norm_v3_fn get;

PythonFunctionContainer fused_pad_conv2d_eager_fallback_fn get;

PythonFunctionContainer fused_pad_conv2d_fn get;

PythonFunctionContainer fused_resize_and_pad_conv2d_eager_fallback_fn get;

PythonFunctionContainer fused_resize_and_pad_conv2d_fn get;

PythonFunctionContainer in_top_k_eager_fallback_fn get;

PythonFunctionContainer in_top_k_fn get;

PythonFunctionContainer in_top_kv2_eager_fallback_fn get;

PythonFunctionContainer in_top_kv2_fn get;

PythonFunctionContainer l2_loss_eager_fallback_fn get;

PythonFunctionContainer leaky_relu_eager_fallback_fn get;

PythonFunctionContainer leaky_relu_fn get;

PythonFunctionContainer leaky_relu_grad_eager_fallback_fn get;

PythonFunctionContainer leaky_relu_grad_fn get;

PythonFunctionContainer log_softmax_eager_fallback_fn get;

PythonFunctionContainer log_softmax_fn get;

PythonFunctionContainer lrn_eager_fallback_fn get;

PythonFunctionContainer lrn_grad_eager_fallback_fn get;

PythonFunctionContainer lrn_grad_fn get;

PythonFunctionContainer max_pool_eager_fallback_fn get;

PythonFunctionContainer max_pool_fn get;

PythonFunctionContainer max_pool_grad_eager_fallback_fn get;

PythonFunctionContainer max_pool_grad_fn get;

PythonFunctionContainer max_pool_grad_grad_eager_fallback_fn get;

PythonFunctionContainer max_pool_grad_grad_fn get;

PythonFunctionContainer max_pool_grad_grad_v2_eager_fallback_fn get;

PythonFunctionContainer max_pool_grad_grad_v2_fn get;

PythonFunctionContainer max_pool_grad_grad_with_argmax_eager_fallback_fn get;

PythonFunctionContainer max_pool_grad_grad_with_argmax_fn get;

PythonFunctionContainer max_pool_grad_v2_eager_fallback_fn get;

PythonFunctionContainer max_pool_grad_v2_fn get;

PythonFunctionContainer max_pool_grad_with_argmax_eager_fallback_fn get;

PythonFunctionContainer max_pool_grad_with_argmax_fn get;

PythonFunctionContainer max_pool_v2_eager_fallback_fn get;

PythonFunctionContainer max_pool_v2_fn get;

PythonFunctionContainer max_pool_with_argmax_eager_fallback_fn get;

PythonFunctionContainer max_pool_with_argmax_fn get;

PythonFunctionContainer max_pool3d_eager_fallback_fn get;

PythonFunctionContainer max_pool3d_fn get;

PythonFunctionContainer max_pool3d_grad_eager_fallback_fn get;

PythonFunctionContainer max_pool3d_grad_fn get;

PythonFunctionContainer max_pool3d_grad_grad_eager_fallback_fn get;

PythonFunctionContainer max_pool3d_grad_grad_fn get;

PythonFunctionContainer nth_element_eager_fallback_fn get;

PythonFunctionContainer nth_element_fn get;

PythonFunctionContainer quantized_avg_pool_eager_fallback_fn get;

PythonFunctionContainer quantized_batch_norm_with_global_normalization_eager_fallback_fn get;

PythonFunctionContainer quantized_batch_norm_with_global_normalization_fn get;

PythonFunctionContainer quantized_bias_add_eager_fallback_fn get;

PythonFunctionContainer quantized_bias_add_fn get;

PythonFunctionContainer quantized_conv2d_and_relu_and_requantize_eager_fallback_fn get;

PythonFunctionContainer quantized_conv2d_and_relu_and_requantize_fn get;

PythonFunctionContainer quantized_conv2d_and_relu_eager_fallback_fn get;

PythonFunctionContainer quantized_conv2d_and_relu_fn get;

PythonFunctionContainer quantized_conv2d_and_requantize_eager_fallback_fn get;

PythonFunctionContainer quantized_conv2d_and_requantize_fn get;

PythonFunctionContainer quantized_conv2d_eager_fallback_fn get;

PythonFunctionContainer quantized_conv2d_per_channel_eager_fallback_fn get;

PythonFunctionContainer quantized_conv2d_per_channel_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_and_relu_and_requantize_eager_fallback_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_and_relu_and_requantize_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_and_relu_eager_fallback_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_and_relu_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_and_requantize_eager_fallback_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_and_requantize_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_eager_fallback_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_signed_sum_and_relu_and_requantize_eager_fallback_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_signed_sum_and_relu_and_requantize_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_sum_and_relu_and_requantize_eager_fallback_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_sum_and_relu_and_requantize_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_sum_and_relu_eager_fallback_fn get;

PythonFunctionContainer quantized_conv2d_with_bias_sum_and_relu_fn get;

PythonFunctionContainer quantized_depthwise_conv2d_eager_fallback_fn get;

PythonFunctionContainer quantized_depthwise_conv2d_fn get;

PythonFunctionContainer quantized_depthwise_conv2d_with_bias_and_relu_and_requantize_eager_fallback_fn get;

PythonFunctionContainer quantized_depthwise_conv2d_with_bias_and_relu_and_requantize_fn get;

PythonFunctionContainer quantized_depthwise_conv2d_with_bias_and_relu_eager_fallback_fn get;

PythonFunctionContainer quantized_depthwise_conv2d_with_bias_and_relu_fn get;

PythonFunctionContainer quantized_depthwise_conv2d_with_bias_eager_fallback_fn get;

PythonFunctionContainer quantized_depthwise_conv2d_with_bias_fn get;

PythonFunctionContainer quantized_mat_mul_with_bias_and_relu_and_requantize_eager_fallback_fn get;

PythonFunctionContainer quantized_mat_mul_with_bias_and_relu_and_requantize_fn get;

PythonFunctionContainer quantized_mat_mul_with_bias_and_relu_eager_fallback_fn get;

PythonFunctionContainer quantized_mat_mul_with_bias_and_relu_fn get;

PythonFunctionContainer quantized_mat_mul_with_bias_eager_fallback_fn get;

PythonFunctionContainer quantized_mat_mul_with_bias_fn get;

PythonFunctionContainer quantized_max_pool_eager_fallback_fn get;

PythonFunctionContainer quantized_relu_eager_fallback_fn get;

PythonFunctionContainer quantized_relu_fn get;

PythonFunctionContainer quantized_relu_x_eager_fallback_fn get;

PythonFunctionContainer quantized_relu6_eager_fallback_fn get;

PythonFunctionContainer quantized_relu6_fn get;

PythonFunctionContainer relu_eager_fallback_fn get;

PythonFunctionContainer relu_grad_eager_fallback_fn get;

PythonFunctionContainer relu_grad_fn get;

PythonFunctionContainer relu6_eager_fallback_fn get;

PythonFunctionContainer relu6_fn get;

PythonFunctionContainer relu6_grad_eager_fallback_fn get;

PythonFunctionContainer relu6_grad_fn get;

PythonFunctionContainer selu_eager_fallback_fn get;

PythonFunctionContainer selu_grad_eager_fallback_fn get;

PythonFunctionContainer selu_grad_fn get;

PythonFunctionContainer softmax_cross_entropy_with_logits_eager_fallback_fn get;

PythonFunctionContainer softmax_cross_entropy_with_logits_fn get;

PythonFunctionContainer softmax_eager_fallback_fn get;

PythonFunctionContainer softmax_fn get;

PythonFunctionContainer softplus_eager_fallback_fn get;

PythonFunctionContainer softplus_grad_eager_fallback_fn get;

PythonFunctionContainer softplus_grad_fn get;

PythonFunctionContainer softsign_eager_fallback_fn get;

PythonFunctionContainer softsign_grad_eager_fallback_fn get;

PythonFunctionContainer softsign_grad_fn get;

PythonFunctionContainer sparse_softmax_cross_entropy_with_logits_eager_fallback_fn get;

PythonFunctionContainer sparse_softmax_cross_entropy_with_logits_fn get;

PythonFunctionContainer top_k_eager_fallback_fn get;

PythonFunctionContainer top_k_fn get;

PythonFunctionContainer top_kv2_eager_fallback_fn get;

PythonFunctionContainer top_kv2_fn get;