# Copyright 2017 The TensorFlow Authors. All Rights Reserved.

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

# http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

# ==============================================================================

"""Graph-only versions of a few op functions, for internal use only."""

# Must be separate from array_ops to avoid a cyclic dependency.

from tensorflow.core.framework import attr_value_pb2

from tensorflow.python.framework import op_callbacks

from tensorflow.python.framework import ops

from tensorflow.python.framework import tensor_shape

def graph_placeholder(dtype, shape, name=None):

"""Graph-only version of tf.compat.v1.placeholder(), for internal use only."""

dtype = dtype.base_dtype

dtype_value = attr_value_pb2.AttrValue(type=dtype.as_datatype_enum)

if isinstance(shape, (list, tuple)):

shape = tensor_shape.TensorShape(shape)

shape = attr_value_pb2.AttrValue(shape=shape.as_proto())

g = ops.get_default_graph()

attrs = {"dtype": dtype_value, "shape": shape}

op = g._create_op_internal( # pylint: disable=protected-access

"Placeholder", [], [dtype], input_types=[],

attrs=attrs, name=name)

result, = op.outputs

if op_callbacks.should_invoke_op_callbacks():

# TODO(b/147670703): Once the special-op creation code paths

# are unified. Remove this `if` block.

callback_outputs = op_callbacks.invoke_op_callbacks(

"Placeholder", tuple(), attrs, tuple(op.outputs),

op_name=name, graph=g)

if callback_outputs is not None:

result, = callback_outputs

return result