tf.SparseTensorValue.indices Alias for field number 0

virtual Status tensorflow::WritableFile::Append(const StringPiece &data)=0

tf.contrib.bayesflow.stochastic_tensor.ObservedStochasticTensor.loss(final_loss, name=None)

tf.nn.rnn_cell.MultiRNNCell.state_size

tf.contrib.learn.Estimator.__repr__()

tf.fft2d(input, name=None) Compute the 2-dimensional discrete Fourier Transform over the inner-most 2 dimensions of input. Args: input: A Tensor of type complex64. A complex64 tensor. name: A name for the operation (optional). Returns: A Tensor of type complex64. A complex64 tensor of the same shape as input. The inner-most 2 dimensions of input are replaced with their 2D Fourier Transform.

class tf.nn.rnn_cell.DropoutWrapper Operator adding dropout to inputs and outputs of the given cell.

tf.zeros(shape, dtype=tf.float32, name=None) Creates a tensor with all elements set to zero. This operation returns a tensor of type dtype with shape shape and all elements set to zero. For example: tf.zeros([3, 4], int32) ==> [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]] Args: shape: Either a list of integers, or a 1-D Tensor of type int32. dtype: The type of an element in the resulting Tensor. name: A name for the operation (optional). Returns: A Tensor with all elements set to zero.

tf.TensorArray.__init__(dtype, size=None, dynamic_size=None, clear_after_read=None, tensor_array_name=None, handle=None, flow=None, infer_shape=True, name=None) Construct a new TensorArray or wrap an existing TensorArray handle. A note about the parameter name: The name of the TensorArray (even if passed in) is uniquified: each time a new TensorArray is created at runtime it is assigned its own name for the duration of the run. This avoids name collisions if a TensorArray is created within a w

tf.contrib.distributions.WishartFull.cholesky_input_output_matrices Boolean indicating if Tensor input/outputs are Cholesky factorized.