tf.contrib.distributions.Multinomial.validate_args Python boolean indicated possibly expensive checks are enabled.

void tensorflow::TensorShape::AsProto(TensorShapeProto *proto) const Fill *proto from *this.

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

tf.FixedLengthRecordReader.num_work_units_completed(name=None) Returns the number of work units this reader has finished processing. Args: name: A name for the operation (optional). Returns: An int64 Tensor.

tf.contrib.distributions.Bernoulli.get_batch_shape() Shape of a single sample from a single event index as a TensorShape. Same meaning as batch_shape. May be only partially defined. Returns: batch_shape: TensorShape, possibly unknown.

tf.contrib.learn.TensorFlowRNNRegressor.get_variable_value(name) Returns value of the variable given by name. Args: name: string, name of the tensor. Returns: Numpy array - value of the tensor.

tf.contrib.bayesflow.stochastic_tensor.LaplaceWithSoftplusScaleTensor.graph

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.get_event_shape() Shape of a single sample from a single batch as a TensorShape. Same meaning as event_shape. May be only partially defined. Returns: event_shape: TensorShape, possibly unknown.

tf.contrib.learn.monitors.LoggingTrainable.set_estimator(estimator) A setter called automatically by the target estimator. If the estimator is locked, this method does nothing. Args: estimator: the estimator that this monitor monitors. Raises: ValueError: if the estimator is None.

tf.TensorArray.write(index, value, name=None) Write value into index index of the TensorArray. Args: index: 0-D. int32 scalar with the index to write to. value: N-D. Tensor of type dtype. The Tensor to write to this index. name: A name for the operation (optional). Returns: A new TensorArray object with flow that ensures the write occurs. Use this object all for subsequent operations. Raises: ValueError: if there are more writers than specified.