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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.
# ==============================================================================
"""Tests for the binary ops priority mechanism."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.python.framework import ops
from tensorflow.python.platform import test as test_lib
class TensorPriorityTest(test_lib.TestCase):
def testSupportedRhsWithoutDelegation(self):
class NumpyArraySubclass(np.ndarray):
pass
supported_rhs_without_delegation = (3, 3.0, [1.0, 2.0], np.array(
[1.0, 2.0]), NumpyArraySubclass(
shape=(1, 2), buffer=np.array([1.0, 2.0])),
ops.convert_to_tensor([[1.0, 2.0]]))
for rhs in supported_rhs_without_delegation:
tensor = ops.convert_to_tensor([[10.0, 20.0]])
res = tensor + rhs
self.assertIsInstance(res, ops.Tensor)
def testUnsupportedRhsWithoutDelegation(self):
class WithoutReverseAdd(object):
pass
tensor = ops.convert_to_tensor([[10.0, 20.0]])
rhs = WithoutReverseAdd()
with self.assertRaisesWithPredicateMatch(
TypeError, lambda e: "Expected float" in str(e)):
# pylint: disable=pointless-statement
tensor + rhs
def testUnsupportedRhsWithDelegation(self):
class WithReverseAdd(object):
def __radd__(self, lhs):
return "Works!"
tensor = ops.convert_to_tensor([[10.0, 20.0]])
rhs = WithReverseAdd()
res = tensor + rhs
self.assertEqual(res, "Works!")
def testFullDelegationControlUsingRegistry(self):
class NumpyArraySubclass(np.ndarray):
def __radd__(self, lhs):
return "Works!"
def raise_to_delegate(value, dtype=None, name=None, as_ref=False):
del value, dtype, name, as_ref # Unused.
raise TypeError
ops.register_tensor_conversion_function(
NumpyArraySubclass, raise_to_delegate, priority=0)
tensor = ops.convert_to_tensor([[10.0, 20.0]])
rhs = NumpyArraySubclass(shape=(1, 2), buffer=np.array([1.0, 2.0]))
res = tensor + rhs
self.assertEqual(res, "Works!")
if __name__ == "__main__":
test_lib.main()
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