87 lines
2.8 KiB
Python
87 lines
2.8 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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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from absl.testing import parameterized
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from tensorflow.python.data.ops import dataset_ops
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from tensorflow.python.eager import def_function
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from tensorflow.python.eager import wrap_function
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from tensorflow.python.framework import config
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from tensorflow.python.framework import constant_op
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from tensorflow.python.framework import dtypes
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from tensorflow.python.framework import importer as graph_def_importer
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from tensorflow.python.framework import ops
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from tensorflow.python.platform import test
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def _dataset_reduce_sum(dataset):
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return dataset.reduce(
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constant_op.constant(0, dtype=dtypes.int64), lambda x, y: x + y)
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def _loop_dataset_sum(dataset):
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value = constant_op.constant(0, dtype=dtypes.int64)
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for d in dataset:
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value += d
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return value
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def _iter_dataset_sum(dataset):
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value = constant_op.constant(0, dtype=dtypes.int64)
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for d in iter(dataset):
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value += d
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return value
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class WrappedGraphTest(test.TestCase, parameterized.TestCase):
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@parameterized.named_parameters(
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('cpu_reduce', 'CPU', _dataset_reduce_sum),
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('gpu_reduce', 'GPU', _dataset_reduce_sum),
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('cpu_loop', 'CPU', _loop_dataset_sum),
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('gpu_loop', 'GPU', _loop_dataset_sum),
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('cpu_iter', 'CPU', _iter_dataset_sum),
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('gpu_iter', 'GPU', _iter_dataset_sum),
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)
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def testWrapFuncDatasetDevice(self, device_type, dataset_reduce_fn):
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devices = config.list_logical_devices(device_type=device_type)
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if not devices:
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self.skipTest('Skip when {} is not detected by TF'.format(device_type))
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@def_function.function
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def comp():
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return dataset_reduce_fn(dataset_ops.Dataset.range(10))
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graph = comp.get_concrete_function().graph
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def function_to_wrap():
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with ops.device(devices[0].name):
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return graph_def_importer.import_graph_def(graph.as_graph_def())
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with ops.device(devices[0].name):
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wrapped_noarg_fn = wrap_function.wrap_function(
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function_to_wrap, signature=[])
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wrapped_noarg_fn()
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if __name__ == '__main__':
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ops.enable_eager_execution()
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test.main()
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