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149 lines
4.2 KiB
149 lines
4.2 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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import unittest
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import numpy as np
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from op_test import OpTest
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class TestReshapeOp(OpTest):
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def setUp(self):
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ori_shape = (2, 25)
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new_shape = (5, 10)
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self.op_type = "reshape"
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self.inputs = {"X": np.random.random(ori_shape).astype("float32")}
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self.attrs = {"shape": new_shape, "inplace": False}
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self.outputs = {"Out": self.inputs["X"].reshape(new_shape)}
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(["X"], "Out")
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class TestReshapeOpDimInfer1(OpTest):
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def setUp(self):
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ori_shape = (5, 10)
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new_shape = (5, -1, 5)
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self.op_type = "reshape"
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self.inputs = {"X": np.random.random(ori_shape).astype("float32")}
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self.attrs = {"shape": new_shape, "inplace": False}
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self.outputs = {"Out": self.inputs["X"].reshape(self.attrs["shape"])}
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(["X"], "Out")
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class TestReshapeOpDimInfer2(OpTest):
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def setUp(self):
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ori_shape = (2, 2, 6)
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new_shape = (2, 0, 3, -1)
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infered_shape = (2, 2, 3, -1)
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self.op_type = "reshape"
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self.inputs = {"X": np.random.random(ori_shape).astype("float32")}
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self.attrs = {"shape": new_shape, "inplace": False}
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self.outputs = {"Out": self.inputs["X"].reshape(infered_shape)}
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(["X"], "Out")
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class TestReshapeOpInplace(OpTest):
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def setUp(self):
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ori_shape = (2, 25)
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new_shape = (5, 10)
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self.op_type = "reshape"
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self.inputs = {"X": np.random.random(ori_shape).astype("float32")}
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self.attrs = {"shape": new_shape}
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self.outputs = {"Out": self.inputs["X"].reshape(new_shape)}
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(["X"], "Out")
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class TestReshapeOpDimInferInplace1(OpTest):
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def setUp(self):
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ori_shape = (5, 10)
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new_shape = (5, -1, 5)
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self.op_type = "reshape"
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self.inputs = {"X": np.random.random(ori_shape).astype("float32")}
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self.attrs = {"shape": new_shape}
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self.outputs = {"Out": self.inputs["X"].reshape(new_shape)}
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(["X"], "Out")
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class TestReshapeOpDimInferInplace2(OpTest):
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def setUp(self):
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ori_shape = (2, 2, 6)
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new_shape = (2, 0, 3, -1)
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infered_shape = (2, 2, 3, -1)
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self.op_type = "reshape"
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self.inputs = {"X": np.random.random(ori_shape).astype("float32")}
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self.attrs = {"shape": new_shape}
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self.outputs = {"Out": self.inputs["X"].reshape(infered_shape)}
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(["X"], "Out")
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class TestReshapeOpWithInputShape(OpTest):
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def setUp(self):
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ori_shape = (6, 5)
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new_shape = (0, -1, 5)
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actual_shape = (2, 3, 5)
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self.op_type = "reshape"
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self.inputs = {
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"X": np.random.random(ori_shape).astype("float32"),
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"Shape": np.array(
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actual_shape, dtype="int32")
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}
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self.attrs = {"shape": new_shape}
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self.outputs = {"Out": self.inputs["X"].reshape(actual_shape)}
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def test_check_output(self):
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self.check_output()
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# def test_check_grad(self):
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# self.check_grad(["X"], "Out")
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if __name__ == "__main__":
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unittest.main()
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