# 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 import pdb from op_test import OpTest # class TestReshapeOp1(OpTest): # def setUp(self): # ori_shape = (2, 25) # new_shape = [5, 10] # # self.op_type = "reshape" # self.inputs = {"X": np.random.random(ori_shape).astype("float32")} # self.attrs = {"shape": new_shape} # 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") # class TestReshapeOpDimInfer1(OpTest): # def setUp(self): # self.op_type = "reshape" # self.inputs = {"X": np.random.random((5, 10)).astype("float32")} # self.attrs = {"shape": [5, -1, 5]} # self.outputs = {"Out": self.inputs["X"].reshape(self.attrs["shape"])} # # def test_check_output(self): # self.check_output() # # def test_check_grad(self): # self.check_grad(["X"], "Out") class TestReshapeOp2(OpTest): def setUp(self): ori_shape = (2, 25) new_shape = ([5, 10], ) self.op_type = "reshape" self.inputs = { "X": np.random.random(ori_shape).astype("float32"), "Shape": np.array(new_shape) } self.outputs = {"Out": self.inputs["X"].reshape(new_shape[0])} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out") if __name__ == "__main__": unittest.main()