old_contents: # 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
  
new_contents: # 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)
    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
  
subject: Remove failing assertion