LostTech.TensorFlow : API Documentation

Type Sum

Namespace tensorflow.keras.metrics

Parent Reduce

Interfaces ISum

Computes the (weighted) sum of the given values.

For example, if values is [1, 3, 5, 7] then the sum is 16. If the weights were specified as [1, 1, 0, 0] then the sum would be 4.

This metric creates one variable, `total`, that is used to compute the sum of `values`. This is ultimately returned as `sum`.

If `sample_weight` is `None`, weights default to 1. Use `sample_weight` of 0 to mask values.

Usage: Usage with tf.keras API:
Show Example 
m = tf.keras.metrics.Sum()
            m.update_state([1, 3, 5, 7])
            print('Final result: ', m.result().numpy())  # Final result: 16.0

Methods

Properties

Public instance methods

object update_state(IGraphNodeBase values, IGraphNodeBase sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
IGraphNodeBase values
Per-example value.
IGraphNodeBase sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(IGraphNodeBase values, int sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
IGraphNodeBase values
Per-example value.
int sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(IGraphNodeBase values, IEnumerable<object> sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
IGraphNodeBase values
Per-example value.
IEnumerable<object> sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(int values, object sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
int values
Per-example value.
object sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(int values, IGraphNodeBase sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
int values
Per-example value.
IGraphNodeBase sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(int values, int sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
int values
Per-example value.
int sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(int values, IEnumerable<object> sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
int values
Per-example value.
IEnumerable<object> sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(ValueTuple<PythonClassContainer, PythonClassContainer> values, object sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
ValueTuple<PythonClassContainer, PythonClassContainer> values
Per-example value.
object sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(ValueTuple<PythonClassContainer, PythonClassContainer> values, IGraphNodeBase sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
ValueTuple<PythonClassContainer, PythonClassContainer> values
Per-example value.
IGraphNodeBase sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(ValueTuple<PythonClassContainer, PythonClassContainer> values, int sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
ValueTuple<PythonClassContainer, PythonClassContainer> values
Per-example value.
int sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(ValueTuple<PythonClassContainer, PythonClassContainer> values, IEnumerable<object> sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
ValueTuple<PythonClassContainer, PythonClassContainer> values
Per-example value.
IEnumerable<object> sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(IEnumerable<IGraphNodeBase> values, object sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
IEnumerable<IGraphNodeBase> values
Per-example value.
object sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(IEnumerable<IGraphNodeBase> values, IGraphNodeBase sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
IEnumerable<IGraphNodeBase> values
Per-example value.
IGraphNodeBase sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(IEnumerable<IGraphNodeBase> values, int sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
IEnumerable<IGraphNodeBase> values
Per-example value.
int sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(IEnumerable<IGraphNodeBase> values, IEnumerable<object> sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
IEnumerable<IGraphNodeBase> values
Per-example value.
IEnumerable<object> sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state(IGraphNodeBase values, object sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
IGraphNodeBase values
Per-example value.
object sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

object update_state_dyn(object values, object sample_weight)

Accumulates statistics for computing the element-wise mean.
Parameters
object values
Per-example value.
object sample_weight
Optional weighting of each example. Defaults to 1.
Returns
object
Update op.

Public static methods

Sum NewDyn(ImplicitContainer<T> name, object dtype)

Creates a `MeanMetricWrapper` instance.
Parameters
ImplicitContainer<T> name
(Optional) string name of the metric instance.
object dtype
(Optional) data type of the metric result.

Public properties

PythonFunctionContainer activity_regularizer get; set;

object activity_regularizer_dyn get; set;

bool built get; set;

object count get; set;

object dtype get;

object dtype_dyn get;

bool dynamic get;

object dynamic_dyn get;

IList<Node> inbound_nodes get;

object inbound_nodes_dyn get;

IList<object> input get;

object input_dyn get;

object input_mask get;

object input_mask_dyn get;

IList<object> input_shape get;

object input_shape_dyn get;

object input_spec get; set;

object input_spec_dyn get; set;

IList<object> losses get;

object losses_dyn get;

IList<object> metrics get;

object metrics_dyn get;

object name get;

object name_dyn get;

object name_scope get;

object name_scope_dyn get;

IList<object> non_trainable_variables get;

object non_trainable_variables_dyn get;

IList<object> non_trainable_weights get;

object non_trainable_weights_dyn get;

IList<object> outbound_nodes get;

object outbound_nodes_dyn get;

IList<object> output get;

object output_dyn get;

object output_mask get;

object output_mask_dyn get;

object output_shape get;

object output_shape_dyn get;

object PythonObject get;

string reduction get; set;

bool stateful get; set;

ValueTuple<object> submodules get;

object submodules_dyn get;

bool supports_masking get; set;

object total get; set;

bool trainable get; set;

object trainable_dyn get; set;

object trainable_variables get;

object trainable_variables_dyn get;

IList<object> trainable_weights get;

object trainable_weights_dyn get;

IList<object> updates get;

object updates_dyn get;

object variables get;

object variables_dyn get;

IList<object> weights get;

object weights_dyn get;