57 lines
1.9 KiB
57 lines
1.9 KiB
# Copyright (c) 2018 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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from __future__ import print_function
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import paddle.fluid as fluid
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import paddle.fluid.layers as layers
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import op_test
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import numpy
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import unittest
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import paddle.fluid.framework as framework
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class TestAssignValueOp(op_test.OpTest):
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def setUp(self):
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self.op_type = "assign_value"
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x = numpy.random.random(size=(2, 5)).astype(numpy.float32)
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self.inputs = {}
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self.outputs = {'Out': x}
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self.attrs = {
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'shape': x.shape,
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'dtype': framework.convert_np_dtype_to_dtype_(x.dtype),
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'fp32_values': [float(v) for v in x.flat]
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}
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def test_forward(self):
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self.check_output()
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def test_assign(self):
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val = (
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-100 + 200 * numpy.random.random(size=(2, 5))).astype(numpy.int32)
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x = layers.create_tensor(dtype="float32")
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layers.assign(input=val, output=x)
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exe = fluid.Executor(fluid.CPUPlace())
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fetched_x = exe.run(fluid.default_main_program(),
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feed={},
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fetch_list=[x])[0]
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self.assertTrue(
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numpy.array_equal(fetched_x, val),
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"fetch_x=%s val=%s" % (fetched_x, val))
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self.assertEqual(fetched_x.dtype, val.dtype)
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if __name__ == '__main__':
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unittest.main()
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