64 lines
2.5 KiB
Python
64 lines
2.5 KiB
Python
# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Test utility."""
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import numpy as np
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from tensorflow.python.ops import variables
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from tensorflow.python.ops.parallel_for import control_flow_ops as pfor_control_flow_ops
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from tensorflow.python.platform import test
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from tensorflow.python.util import nest
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class PForTestCase(test.TestCase):
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"""Base class for test cases."""
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def _run_targets(self, targets1, targets2=None, run_init=True):
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targets1 = nest.flatten(targets1)
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targets2 = ([] if targets2 is None else nest.flatten(targets2))
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assert len(targets1) == len(targets2) or not targets2
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if run_init:
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init = variables.global_variables_initializer()
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self.evaluate(init)
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return self.evaluate(targets1 + targets2)
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# TODO(agarwal): Allow tests to pass down tolerances.
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def run_and_assert_equal(self, targets1, targets2, rtol=1e-4, atol=1e-5):
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outputs = self._run_targets(targets1, targets2)
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outputs = nest.flatten(outputs) # flatten SparseTensorValues
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n = len(outputs) // 2
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for i in range(n):
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if outputs[i + n].dtype != np.object_:
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self.assertAllClose(outputs[i + n], outputs[i], rtol=rtol, atol=atol)
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else:
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self.assertAllEqual(outputs[i + n], outputs[i])
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def _test_loop_fn(self,
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loop_fn,
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iters,
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parallel_iterations=None,
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fallback_to_while_loop=False,
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rtol=1e-4,
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atol=1e-5):
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t1 = pfor_control_flow_ops.pfor(
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loop_fn,
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iters=iters,
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fallback_to_while_loop=fallback_to_while_loop,
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parallel_iterations=parallel_iterations)
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loop_fn_dtypes = nest.map_structure(lambda x: x.dtype, t1)
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t2 = pfor_control_flow_ops.for_loop(loop_fn, loop_fn_dtypes, iters=iters,
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parallel_iterations=parallel_iterations)
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self.run_and_assert_equal(t1, t2, rtol=rtol, atol=atol)
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