LostTech.TensorFlow : API Documentation

Type ModelFunction

Namespace tensorflow_estimator.python.estimator.export.function

Parent AutoTrackable

Interfaces IModelFunction

Methods

Properties

Public instance methods

void __delattr__(string name)

Implement delattr(self, name).

object __delattr___dyn(object name)

Implement delattr(self, name).

object __setattr__(string name, Module value)

Support self.foo = trackable syntax.

object __setattr__(string name, Variable value)

Support self.foo = trackable syntax.

object __setattr__(string name, ValueTuple<PythonClassContainer, PythonClassContainer> value)

Support self.foo = trackable syntax.

object __setattr___dyn(object name, object value)

Support self.foo = trackable syntax.

void add_mode(object fn, string mode, object input_signature)

object add_mode_dyn(object fn, object mode, object input_signature)

Tensor call(IndexedSlices mode, object features, object labels)

Tensor call(IGraphNodeBase mode, IEnumerable<IGraphNodeBase> features, object labels)

Tensor call(IGraphNodeBase mode, PythonClassContainer features, object labels)

Tensor call(IGraphNodeBase mode, object features, object labels)

Tensor call(PythonClassContainer mode, object features, object labels)

Tensor call(PythonClassContainer mode, PythonClassContainer features, object labels)

Tensor call(IndexedSlices mode, PythonClassContainer features, object labels)

Tensor call(string mode, PythonClassContainer features, object labels)

Tensor call(string mode, object features, object labels)

Tensor call(PythonClassContainer mode, IEnumerable<IGraphNodeBase> features, object labels)

Tensor call(string mode, IEnumerable<IGraphNodeBase> features, object labels)

Tensor call(IndexedSlices mode, IEnumerable<IGraphNodeBase> features, object labels)

Tensor call(IEnumerable<IGraphNodeBase> mode, PythonClassContainer features, object labels)

Tensor call(IEnumerable<IGraphNodeBase> mode, IEnumerable<IGraphNodeBase> features, object labels)

Tensor call(IEnumerable<IGraphNodeBase> mode, object features, object labels)

object call_dyn(object mode, object features, object labels)

object evaluate(object features, ndarray labels)

object evaluate(object features, IDictionary<string, object> labels)

object evaluate(object features, HDF5Matrix labels)

object evaluate(object features, IEnumerable<ndarray> labels)

object evaluate(object features, IGraphNodeBase labels)

object evaluate(object features, int labels)

object evaluate_dyn(object features, object labels)

Evaluate on the evaluation data.

Runs evaluation on the evaluation data and returns the result. Runs for `self._eval_steps` steps, or if it's `None`, then run until input is exhausted or another exception is raised. Start the evaluation after `delay_secs` seconds, or if it's `None`, defaults to using `self._eval_delay_secs` seconds.
Returns
object
The result of the `evaluate` call to the `Estimator`.

object predict(IEnumerable<IGraphNodeBase> features)

object predict_dyn(object features)

Computes predictions multiple steps into the future.
Parameters
object features
A dictionary with the following key/value pairs:
Returns
object
A dictionary with keys, "mean", "covariance". The values are Tensors of shape [batch_size, predict window size, num_features] and correspond to the values passed in `TIMES`.

Tensor train(IGraphNodeBase features, IGraphNodeBase labels)

object train_dyn(object features, object labels)

Public static methods

ModelFunction from_function(PythonFunctionContainer model_fn, object all_modes, object config, object params)

object from_function_dyn(object model_fn, object all_modes, object config, object params)

Public properties

object PythonObject get;

object variables get;

object variables_dyn get;