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# Copyright 2015 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.
# ==============================================================================
"""Classes and functions used to construct graphs."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.framework import ops
__all__ = ['get_graph_from_inputs',
'get_name_scope']
def get_graph_from_inputs(op_input_list, graph=None):
"""Returns the appropriate graph to use for the given inputs.
1. If `graph` is provided, we validate that all inputs in `op_input_list` are
from the same graph.
2. Otherwise, we attempt to select a graph from the first Operation- or
Tensor-valued input in `op_input_list`, and validate that all other
such inputs are in the same graph.
3. If the graph was not specified and it could not be inferred from
`op_input_list`, we attempt to use the default graph.
Args:
op_input_list: A list of inputs to an operation, which may include `Tensor`,
`Operation`, and other objects that may be converted to a graph element.
graph: (Optional) The explicit graph to use.
Raises:
TypeError: If `op_input_list` is not a list or tuple, or if graph is not a
Graph.
ValueError: If a graph is explicitly passed and not all inputs are from it,
or if the inputs are from multiple graphs, or we could not find a graph
and there was no default graph.
Returns:
The appropriate graph to use for the given inputs.
"""
# pylint: disable=protected-access
return ops._get_graph_from_inputs(op_input_list, graph)
def get_name_scope():
"""Returns the current name scope of the default graph.
For example:
```python
with tf.name_scope('scope1'):
with tf.name_scope('scope2'):
print(tf.contrib.framework.get_name_scope())
```
would print the string `scope1/scope2`.
Returns:
A string represnting the current name scope.
"""
return ops.get_default_graph().get_name_scope()
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