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

tf.trace(x, name=None) Compute the trace of a tensor x. trace(x) returns

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

class tf.contrib.bayesflow.stochastic_tensor.SampleValue Draw n samples along a new outer dimension. This

2025-01-10 15:47:30
tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagPlusVDVTTensor
  • References/Big Data/TensorFlow/TensorFlow Python/BayesFlow Stochastic Tensors

class tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagPlusVDVTTensor MultivariateNormalDiagPlusVDVTTensor

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

tf.contrib.bayesflow.stochastic_tensor.BetaTensor.graph

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tf.contrib.distributions.DirichletMultinomial.log_prob()
  • References/Big Data/TensorFlow/TensorFlow Python/Statistical distributions

tf.contrib.distributions.DirichletMultinomial.log_prob(value, name='log_prob') Log probability density/mass function (depending

2025-01-10 15:47:30
tf.unique()
  • References/Big Data/TensorFlow/TensorFlow Python/Math

tf.unique(x, out_idx=None, name=None) Finds unique elements in a 1-D tensor. This operation returns

2025-01-10 15:47:30
tf.contrib.learn.monitors.NanLoss
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

class tf.contrib.learn.monitors.NanLoss NaN Loss monitor. Monitors loss and stops training if

2025-01-10 15:47:30
tf.contrib.distributions.BetaWithSoftplusAB.dtype
  • References/Big Data/TensorFlow/TensorFlow Python/Statistical distributions

tf.contrib.distributions.BetaWithSoftplusAB.dtype The DType of Tensors handled by this Distribution

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tf.contrib.learn.monitors.ValidationMonitor.epoch_end()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

tf.contrib.learn.monitors.ValidationMonitor.epoch_end(epoch) End epoch. Args:

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

tf.contrib.graph_editor.copy_with_input_replacements(sgv, replacement_ts, dst_graph=None, dst_scope='', src_scope='', reuse_dst_scope=False)

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