# Copyright (c) 2021 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 from paddle.framework import core SEED = 2021 np.random.seed(SEED) def get_c_embedding(start, end, table, ids): index = ids.flatten() input_mask = (index < start) | (index >= end) masked_input = index - start masked_input[input_mask] = 0 output = table[masked_input] output[input_mask] = 0.0 return output class TestCEmbeddingCPU(OpTest): def setUp(self): self.init_dtype() self.initcase() if core.is_compiled_with_npu(): self.__class__.use_npu = True elif core.is_compiled_with_xpu(): self.__class__.use_xpu = True elif core.is_compiled_with_cuda(): self.__class__.exist_fp64_check_grad = True def initcase(self): self.op_type = "c_embedding" table = np.random.random((17, 64)).astype(self.dtype) ids = np.random.randint(low=0, high=17 * 2, size=(2, 4)).astype( self.ids_dtype ) self.start_index = 10 self.end_index = self.start_index + 17 self.inputs = {'W': table, 'Ids': ids} np_out = get_c_embedding(self.start_index, self.end_index, table, ids) self.outputs = {'Out': np_out.reshape((2, 4, 64))} self.attrs = {'start_index': self.start_index} if core.is_compiled_with_npu(): self.__class__.use_npu = True elif core.is_compiled_with_xpu(): self.__class__.use_xpu = True def test_check_cpu(self): self.check_output_with_place(core.CPUPlace()) def test_check_cpu_grad(self): self.check_grad_with_place(core.CPUPlace(), ['W'], 'Out') def init_dtype(self): self.dtype = "float32" self.ids_dtype = "int64" class TestCEmbeddingOpBase(TestCEmbeddingCPU): def setUp(self): self.init_dtype() self.initcase() def test_check_output(self): if core.is_compiled_with_cuda(): self.check_output_with_place(core.CUDAPlace(0)) elif core.is_compiled_with_npu(): self.check_output_with_place(core.NPUPlace(0)) elif core.is_compiled_with_xpu(): self.check_output_with_place(core.XPUPlace(0)) def test_check_grad(self): if core.is_compiled_with_cuda(): self.check_grad_with_place(core.CUDAPlace(0), ['W'], 'Out') elif core.is_compiled_with_npu(): self.check_grad_with_place(core.NPUPlace(0), ['W'], 'Out') elif core.is_compiled_with_xpu(): self.check_grad_with_place(core.XPUPlace(0), ['W'], 'Out') def init_dtype(self): if core.is_compiled_with_cuda(): self.dtype = "float64" self.ids_dtype = "int64" elif core.is_compiled_with_npu(): self.dtype = "float32" self.ids_dtype = "int32" elif core.is_compiled_with_xpu(): self.dtype = "float32" self.ids_dtype = "int64" class TestCEmbeddingOpFP32(TestCEmbeddingOpBase): def setUp(self): self.init_dtype() self.initcase() def initcase(self): self.op_type = "c_embedding" table = np.random.random((17, 64)).astype(self.dtype) ids = np.random.randint(low=0, high=17 * 2, size=(2, 4)).astype( self.ids_dtype ) self.start_index = 10 ids[0][1] = 12 ids[0][2] = 12 ids[1][2] = 12 ids[1][3] = 12 self.end_index = self.start_index + 17 self.inputs = {'W': table, 'Ids': ids} np_out = get_c_embedding(self.start_index, self.end_index, table, ids) self.outputs = {'Out': np_out.reshape((2, 4, 64))} self.attrs = {'start_index': self.start_index} if core.is_compiled_with_npu(): self.__class__.use_npu = True elif core.is_compiled_with_xpu(): self.__class__.use_xpu = True elif core.is_compiled_with_cuda(): self.__class__.exist_fp64_check_grad = True def init_dtype(self): self.dtype = "float32" self.ids_dtype = "int32" if __name__ == "__main__": unittest.main()