tf.test.assert_equal_graph_def()
  • References/Big Data/TensorFlow/TensorFlow Python/Testing

tf.test.assert_equal_graph_def(actual, expected) Asserts that two GraphDefs are (mostly) the same.

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tf.contrib.bayesflow.stochastic_tensor.BernoulliTensor.mean()
  • References/Big Data/TensorFlow/TensorFlow Python/BayesFlow Stochastic Tensors

tf.contrib.bayesflow.stochastic_tensor.BernoulliTensor.mean(name='mean')

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tensorflow::Session
  • References/Big Data/TensorFlow/TensorFlow C++/Session

A Session instance lets a caller drive a TensorFlow graph computation. When a Session is created with a given target, a new Session object is

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tf.contrib.layers.repeat()
  • References/Big Data/TensorFlow/TensorFlow Python/Layers

tf.contrib.layers.repeat(inputs, repetitions, layer, *args, **kwargs) Applies the same layer with the same arguments repeatedly

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tf.contrib.graph_editor.SubGraphView.inputs
  • References/Big Data/TensorFlow/TensorFlow Python/Graph Editor

tf.contrib.graph_editor.SubGraphView.inputs The input tensors of this subgraph view.

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tf.contrib.distributions.Categorical.param_static_shapes()
  • References/Big Data/TensorFlow/TensorFlow Python/Statistical distributions

tf.contrib.distributions.Categorical.param_static_shapes(cls, sample_shape) param_shapes with static (i.e. TensorShape) shapes

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tensorflow::PartialTensorShape::dim_size()
  • References/Big Data/TensorFlow/TensorFlow C++/PartialTensorShape

int64 tensorflow::PartialTensorShape::dim_size(int d) const Returns the number of elements in dimension d. REQUIRES:

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tensorflow::TensorShape::operator=()
  • References/Big Data/TensorFlow/TensorFlow C++/TensorShape

void tensorflow::TensorShape::operator=(const TensorShape &b)

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tf.Session.close()
  • References/Big Data/TensorFlow/TensorFlow Python/Running Graphs

tf.Session.close() Closes this session. Calling this method frees all resources associated with

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tf.contrib.bayesflow.stochastic_tensor.LaplaceTensor.
  • References/Big Data/TensorFlow/TensorFlow Python/BayesFlow Stochastic Tensors

tf.contrib.bayesflow.stochastic_tensor.LaplaceTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

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