wehub-resource-sync
90 lines
2.7 KiB
Python
90 lines
2.7 KiB
Python
# Copyright (c) 2021 PaddlePaddle 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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import unittest
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import numpy as np
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from op import Operator
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from op_test import OpTest, get_places
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import paddle
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from paddle.base import core
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def api_wrapper(x):
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return paddle._C_ops.share_data(x)
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class TestShareDataOp(OpTest):
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def setUp(self):
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self.op_type = "share_data"
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self.python_api = api_wrapper
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input = np.random.rand(2, 3, 5).astype("float32")
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self.inputs = {'X': input}
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self.outputs = {'Out': input}
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def test_check_output(self):
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self.check_output()
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class TestShareDataOpOnDifferentPlaces(unittest.TestCase):
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def check_with_tensor(self, place):
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scope = core.Scope()
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np_array = np.random.rand(2, 3, 5).astype("float32")
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# initialize input and output variable
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x = scope.var('X').get_tensor()
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x.set(np_array, place)
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out = scope.var("Out").get_tensor()
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op = Operator("share_data", X="X", Out="Out")
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op.run(scope, place)
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np.testing.assert_allclose(np_array, out, rtol=1e-05)
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def check_with_selected_rows(self, place):
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scope = core.Scope()
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x_rows = [0, 1, 5, 4, 19]
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x_height = 20
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row_numel = 2
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np_array = np.ones((len(x_rows), row_numel)).astype("float32")
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# initialize input variable
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x = scope.var('X').get_selected_rows()
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x.set_rows(x_rows)
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x.set_height(x_height)
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x_tensor = x.get_tensor()
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x_tensor.set(np_array, place)
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# initialize the Out variable
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out = scope.var("Out").get_selected_rows()
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out_tensor = out.get_tensor()
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op = Operator("share_data", X="X", Out="Out")
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op.run(scope, place)
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out_height = out.height()
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out_rows = out.rows()
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np.testing.assert_allclose(np_array, out_tensor, rtol=1e-05)
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self.assertEqual(x_height, out_height)
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self.assertEqual(x_rows, out_rows)
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def test_check_output(self):
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for place in get_places():
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self.check_with_selected_rows(place)
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self.check_with_tensor(place)
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if __name__ == '__main__':
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unittest.main()
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