tf.QueueBase.from_list()
  • References/Big Data/TensorFlow/TensorFlow Python/Inputs and Readers

tf.QueueBase.from_list(index, queues) Create a queue using the queue reference from queues[index].

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tf.contrib.learn.monitors.StopAtStep.begin()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

tf.contrib.learn.monitors.StopAtStep.begin(max_steps=None) Called at the beginning of training. When

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tf.contrib.graph_editor.select_ops_and_ts()
  • References/Big Data/TensorFlow/TensorFlow Python/Graph Editor

tf.contrib.graph_editor.select_ops_and_ts(*args, **kwargs) Helper to select operations and tensors. Args:

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

tf.contrib.distributions.Categorical.__init__(logits, dtype=tf.int32, validate_args=False, allow_nan_stats=True, name='Categorical') Initialize

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

tf.contrib.distributions.Categorical.entropy(name='entropy') Shanon entropy in nats.

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tf.contrib.distributions.GammaWithSoftplusAlphaBeta.get_event_shape()
  • References/Big Data/TensorFlow/TensorFlow Python/Statistical distributions

tf.contrib.distributions.GammaWithSoftplusAlphaBeta.get_event_shape() Shape of a single sample from a single batch as a TensorShape

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tf.contrib.distributions.ExponentialWithSoftplusLam.param_shapes()
  • References/Big Data/TensorFlow/TensorFlow Python/Statistical distributions

tf.contrib.distributions.ExponentialWithSoftplusLam.param_shapes(cls, sample_shape, name='DistributionParamShapes') Shapes of

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tf.contrib.framework.convert_to_tensor_or_sparse_tensor()
  • References/Big Data/TensorFlow/TensorFlow Python/Framework

tf.contrib.framework.convert_to_tensor_or_sparse_tensor(value, dtype=None, name=None, as_ref=False) Converts value to a

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tf.edit_distance()
  • References/Big Data/TensorFlow/TensorFlow Python/Math

tf.edit_distance(hypothesis, truth, normalize=True, name='edit_distance') Computes the Levenshtein distance between sequences

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

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor.clone(name=None, **dist_args)

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