# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import unittest import numpy as np from op_test import OpTest # Correct: General. class TestSqueezeOp1(OpTest): def setUp(self): ori_shape = (1, 3, 1, 5) axes = (0, 2) new_shape = (3, 5) self.op_type = "squeeze" self.inputs = {"X": np.random.random(ori_shape).astype("float32")} self.attrs = {"axes": axes, "inpalce": False} self.outputs = {"Out": self.inputs["X"].reshape(new_shape)} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out") # Correct: There is mins axis. class TestSqueezeOp2(OpTest): def setUp(self): ori_shape = (1, 3, 1, 5) axes = (0, -2) new_shape = (3, 5) self.op_type = "squeeze" self.inputs = {"X": np.random.random(ori_shape).astype("float32")} self.attrs = {"axes": axes, "inpalce": False} self.outputs = {"Out": self.inputs["X"].reshape(new_shape)} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out") # Correct: No axes input. class TestSqueezeOp3(OpTest): def setUp(self): ori_shape = (1, 3, 1, 5) axes = () new_shape = (3, 5) self.op_type = "squeeze" self.inputs = {"X": np.random.random(ori_shape).astype("float32")} self.attrs = {"axes": axes, "inpalce": False} self.outputs = {"Out": self.inputs["X"].reshape(new_shape)} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out") # Correct: Just part of axes be squeezed. class TestSqueezeOp4(OpTest): def setUp(self): ori_shape = (1, 3, 1, 5, 1, 4, 1) axes = (2, 6) new_shape = (1, 3, 5, 1, 4) self.op_type = "squeeze" self.inputs = {"X": np.random.random(ori_shape).astype("float32")} self.attrs = {"axes": axes, "inpalce": False} self.outputs = {"Out": self.inputs["X"].reshape(new_shape)} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out") # Correct: Inplace. class TestSqueezeOpInplace1(OpTest): def setUp(self): ori_shape = (1, 3, 1, 5) axes = (0, 2) new_shape = (3, 5) self.op_type = "squeeze" self.inputs = {"X": np.random.random(ori_shape).astype("float32")} self.attrs = {"axes": axes, "inplace": True} self.outputs = {"Out": self.inputs["X"].reshape(new_shape)} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out") # Correct: Inplace. There is mins axis. class TestSqueezeOpInplace2(OpTest): def setUp(self): ori_shape = (1, 3, 1, 5) axes = (0, -2) new_shape = (3, 5) self.op_type = "squeeze" self.inputs = {"X": np.random.random(ori_shape).astype("float32")} self.attrs = {"axes": axes, "inpalce": True} self.outputs = {"Out": self.inputs["X"].reshape(new_shape)} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out") # Correct: Inplace. No axes input. class TestSqueezeOpInplace3(OpTest): def setUp(self): ori_shape = (1, 3, 1, 5) axes = () new_shape = (3, 5) self.op_type = "squeeze" self.inputs = {"X": np.random.random(ori_shape).astype("float32")} self.attrs = {"axes": axes, "inpalce": True} self.outputs = {"Out": self.inputs["X"].reshape(new_shape)} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out") # Correct: Inpalce. Just part of axes be squeezed. class TestSqueezeOpInplace4(OpTest): def setUp(self): ori_shape = (1, 3, 1, 5, 1, 4, 1) axes = (2, 6) new_shape = (1, 3, 5, 1, 4) self.op_type = "squeeze" self.inputs = {"X": np.random.random(ori_shape).astype("float32")} self.attrs = {"axes": axes, "inpalce": True} self.outputs = {"Out": self.inputs["X"].reshape(new_shape)} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out") if __name__ == "__main__": unittest.main()