Returns true if `this` represents an actual value.

Enter a context where the lock is with group `group_id`. Args: group_id: The group for which to acquire and release the lock. Returns:

Construct a TensorArray for holding Tensors of type 'dtype' with 'N' elements. While the underlying storage is a std::vector and can hold more than M

Returns the `Tensor` with the given `name`. This method may be called concurrently from multiple threads. Args: name: The name of the

Get a mutable tensor data structure. TODO(aselle): Create a safe ArrayHandle interface to avoid exposing this read/write access to structure

Updates the stats accumulator.

Bitwise reduction (logical OR). Arguments: x: Tensor or variable. axis: axis along which to perform the reduction. keepdims: whet

Returns a NumPy array specifying the maximum bounds (inclusive).

idx can be negative for an offset from end of dimensions. idx must be in the range [-1 * s.rank, s.rank).

Enqueues a constant op onto the computation. Args: value: value for the constant, as a np.array with an explicit dtype set to one o

Populate the output layout unless the minor_to_major array contains all -1 value, in which case the layout is considered missing and the API returns f

Returns a new iterator for iterating over the range of elements in this dataset. This method may be called multiple times on the same instance, and t

Returns True iff `self` is fully defined in every dimension.

Broadcast the `tensor` to destinations. Args: tensor: the tensor to broadcast. destinations: the broadcast destinations. Returns

Encoder using LSTM. Args: x: tensor of size [num_children, num_groups, embedding_size] Returns: last_c, last_h: tensors of size

DEPRECATED: Use outputs.

Returns the number of operands to this instruction.

Asserts that a Numpy ndarray and a TensorFlow tensor have the same shape. Args: np_array: A Numpy ndarray or Numpy scalar. tf_tensor:

Return the list of operations in the graph. You can modify the operations in place, but modifications to the list such as inserts/delete have

Deprecated, do NOT use! This is an alias of `self.__call__`. Arguments: inputs: Input tensor(s). *args: additional positional ar

Serialize an accumulator for a remote call.

Runs operations and evaluates tensors in `fetches`. This method runs one "step" of TensorFlow computation, by running the necessary graph fra

Asserts that the two given devices are the same. Args: device1: A string device name or TensorFlow `DeviceSpec` object. device2: A st

Shape of batch dimensions of this operator, determined at runtime. If this operator acts like the batch matrix `A` with `A.shape = [B1,...,Bb

Enqueues zero or more elements to this queue. This operation slices each component tensor along the 0th dimension to make multiple queue elem

Return the index of the source output that produces the data carried by this edge. The special value kControlSlot is used for control dependencies.

Returns a Thread wrapper that asserts 'target' completes successfully. This method should be used to create all threads in test cases, as oth

Adds a child piece to this piece's children.

Returns a serialized `GraphDef` representation of this graph. The serialized `GraphDef` can be imported into another `Graph` (using `tf.impor

Return the sharding protobuf of type xla_data_pb2.OpSharding.

Saves variables. This method runs the ops added by the constructor for saving variables. It requires a session in which the graph was launche

Restore a reader to its initial clean state. Args: name: A name for the operation (optional). Returns: The created Operation.

Context-manager to force placement of operations and Tensors on a device. Args: name: Name of the device or None to get default placement.

Returns MIOpen handle. To be passed directly to MIOpen APIs, don't keep a copy.