size_t tensorflow::ThreadOptions::stack_size Thread stack size to use (in bytes).

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

tf.contrib.distributions.Distribution.param_shapes(cls, sample_shape, name='DistributionParamShapes') Shapes of parameters given the desired shape of a call to sample(). Subclasses should override static method _param_shapes. Args: sample_shape: Tensor or python list/tuple. Desired shape of a call to sample(). name: name to prepend ops with. Returns: dict of parameter name to Tensor shapes.

void tensorflow::TensorShape::DumpRep() const

tf.contrib.distributions.Binomial.variance(name='variance') Variance.

tf.contrib.distributions.Normal.mean(name='mean') Mean.

tf.image.transpose_image(image) Transpose an image by swapping the first and second dimension. See also transpose(). Args: image: 3-D tensor of shape [height, width, channels] Returns: A 3-D tensor of shape [width, height, channels] Raises: ValueError: if the shape of image not supported.

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

tf.nn.rnn_cell.RNNCell.output_size Integer or TensorShape: size of outputs produced by this cell.

tf.contrib.learn.monitors.CheckpointSaver.end(session=None)