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# Copyright 2016 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.
# ==============================================================================
"""Utilities for type-dependent behavior used in autograph-generated code."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.contrib.autograph.utils.type_check import is_tensor
from tensorflow.python.ops import control_flow_ops
def dynamic_is(left, right):
# TODO(alexbw) if we're sure we should leave 'is' in place,
# then change the semantics in converters/logical_expressions.py
return left is right
def dynamic_is_not(left, right):
return left is not right
def run_cond(condition, true_fn, false_fn):
"""Type-dependent functional conditional.
Args:
condition: A Tensor or Python bool.
true_fn: A Python callable implementing the true branch of the conditional.
false_fn: A Python callable implementing the false branch of the
conditional.
Returns:
result: The result of calling the appropriate branch. If condition is a
Tensor, tf.cond will be used. Otherwise, a standard Python if statement will
be ran.
"""
if is_tensor(condition):
return control_flow_ops.cond(condition, true_fn, false_fn)
else:
return py_cond(condition, true_fn, false_fn)
def py_cond(condition, true_fn, false_fn):
"""Functional version of Python's conditional."""
if condition:
results = true_fn()
else:
results = false_fn()
# The contract for the branch functions is to return tuples, but they should
# be collapsed to a single element when there is only one output.
if len(results) == 1:
return results[0]
return results
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