A file abstraction for sequential writing. The implementation must provide buffering since callers may append small fragments at a time to the file. Member Details tensorflow::WritableFile::WritableFile() tensorflow::WritableFile::~WritableFile() virtual Status tensorflow::WritableFile::Append(const StringPiece &data)=0 virtual Status tensorflow::WritableFile::Close()=0 virtual Status tensorflow::WritableFile::Flush()=0 virtual Status tensorflow::WritableFile::Sync()=0

tf.contrib.distributions.Beta.a Shape parameter.

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

tf.QueueBase.size(name=None) Compute the number of elements in this queue. Args: name: A name for the operation (optional). Returns: A scalar tensor containing the number of elements in this queue.

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

TTypes< T, NDIMS >::ConstTensor tensorflow::Tensor::bit_casted_tensor() const Return the tensor data to an Eigen::Tensor with the same size but a bitwise cast to the specified dtype T. Using a bitcast is useful for move and copy operations. NOTE: this is the same as tensor() except a bitcast is allowed.

tf.contrib.distributions.DirichletMultinomial.entropy(name='entropy') Shanon entropy in nats.

tf.contrib.learn.monitors.StopAtStep.epoch_begin(epoch) Begin epoch. Args: epoch: int, the epoch number. Raises: ValueError: if we've already begun an epoch, or epoch < 0.

void tensorflow::Tensor::AsProtoField(TensorProto *proto) const Fills in proto with *this tensor's content. AsProtoField() fills in the repeated field for proto.dtype(), while AsProtoTensorContent() encodes the content in proto.tensor_content() in a compact form.

tf.contrib.distributions.BetaWithSoftplusAB.is_reparameterized