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

tf.contrib.distributions.ExponentialWithSoftplusLam.mode(name='mode') Mode. Additional documentation

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tf.FixedLenFeature.
  • References/Big Data/TensorFlow/TensorFlow Python/Inputs and Readers

tf.FixedLenFeature.__getstate__() Exclude the OrderedDict from pickling

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tf.contrib.metrics.set_union()
  • References/Big Data/TensorFlow/TensorFlow Python/Metrics

tf.contrib.metrics.set_union(a, b, validate_indices=True) Compute set union of elements in last dimension of a and

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tf.contrib.learn.RunConfig.job_name
  • References/Big Data/TensorFlow/TensorFlow Python/Learn

tf.contrib.learn.RunConfig.job_name

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tf.sparse_transpose()
  • References/Big Data/TensorFlow/TensorFlow Python/Sparse Tensors

tf.sparse_transpose(sp_input, perm=None, name=None) Transposes a SparseTensor The

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

tf.cholesky_solve(chol, rhs, name=None) Solves systems of linear eqns A X = RHS, given Cholesky factorizations.

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

tf.acos(x, name=None) Computes acos of x element-wise. Args:

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

tf.contrib.bayesflow.stochastic_tensor.LaplaceWithSoftplusScaleTensor.graph

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

tf.contrib.distributions.TransformedDistribution.name Name prepended to all ops created by this Distribution.

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tf.assert_positive()
  • References/Big Data/TensorFlow/TensorFlow Python/Asserts and boolean checks.

tf.assert_positive(x, data=None, summarize=None, message=None, name=None) Assert the condition x > 0 holds element-wise

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