# 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. from . import op_test import unittest import numpy as np import paddle.fluid.core as core class TestCastOp1(op_test.OpTest): def setUp(self): ipt = np.random.random(size=[10, 10]) self.inputs = {'X': ipt.astype('float32')} self.outputs = {'Out': ipt.astype('float64')} self.attrs = { 'in_dtype': int(core.VarDesc.VarType.FP32), 'out_dtype': int(core.VarDesc.VarType.FP64) } self.op_type = 'cast' def test_check_output(self): self.check_output() def test_grad(self): self.check_grad(['X'], ['Out']) class TestCastOp2(op_test.OpTest): def setUp(self): ipt = np.random.random(size=[10, 10]) # numpy float16 is binded to fluid float16 via uint16 self.inputs = {'X': ipt.astype('float16').view(np.uint16)} self.outputs = {'Out': ipt.astype('float32')} self.attrs = { 'in_dtype': int(core.VarDesc.VarType.FP16), 'out_dtype': int(core.VarDesc.VarType.FP32) } self.op_type = 'cast' def test_check_output(self): self.check_output(atol=1e-3) class TestCastOp3(op_test.OpTest): def setUp(self): ipt = np.random.random(size=[10, 10]) self.inputs = {'X': ipt.astype('float32')} self.outputs = {'Out': ipt.astype('float16')} self.attrs = { 'in_dtype': int(core.VarDesc.VarType.FP32), 'out_dtype': int(core.VarDesc.VarType.FP16) } self.op_type = 'cast' def test_check_output(self): self.check_output(atol=1e-3) if __name__ == '__main__': unittest.main()