# 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 __future__ import absolute_import from __future__ import division from __future__ import print_function from tensorflow.core.framework import attr_value_pb2 from tensorflow.python.framework import ops from tensorflow.python.framework import tensor_shape def graph_zeros_like(tensor): """Graph-only version of tf.zeros_like(), for internal use only.""" g = ops._get_graph_from_inputs([tensor]) # pylint: disable=protected-access with g.as_default(), ops.name_scope(None, "zeros_like", [tensor]) as name: tensor = ops.convert_to_tensor(tensor, name="tensor") dtype = tensor.dtype.base_dtype dtype_value = attr_value_pb2.AttrValue(type=dtype.as_datatype_enum) op = g.create_op("ZerosLike", [tensor], [dtype], input_types=[dtype], attrs={"T": dtype_value}, name=name) result, = op.outputs return result def graph_placeholder(dtype, shape, name=None): """Graph-only version of tf.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) assert isinstance(shape, tensor_shape.TensorShape) shape = attr_value_pb2.AttrValue(shape=shape.as_proto()) g = ops.get_default_graph() with ops.name_scope(name, "placeholder", []) as name: op = g.create_op("Placeholder", [], [dtype], input_types=[], attrs={"dtype": dtype_value, "shape": shape}, name=name) result, = op.outputs return result