// Copyright (c) 2019 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. #include "lite/kernels/arm/lookup_table_compute.h" #include #include #include #include #include "lite/core/op_registry.h" namespace paddle { namespace lite { namespace kernels { namespace arm { void lookup_table_compute_ref(const operators::LookupTableParam ¶m) { auto *ids_t = param.Ids; auto *output_t = param.Out; int64_t padding_idx = param.padding_idx; auto *ids = ids_t->data(); int64_t ids_numel = ids_t->dims().production(); auto *table_t = param.W; int64_t row_number = table_t->dims()[0]; int64_t row_width = table_t->dims()[1]; auto *table = table_t->data(); auto *output = output_t->mutable_data(); memset(output, 0, output_t->dims().production() * sizeof(float)); for (int64_t i = 0; i < ids_numel; ++i) { if (padding_idx != -1 && ids[i] == padding_idx) { memset(output + i * row_width, 0, row_width * sizeof(float)); } else { CHECK_LT(ids[i], row_number); CHECK_GE(ids[i], 0); memcpy(output + i * row_width, table + ids[i] * row_width, row_width * sizeof(float)); } } } TEST(lookup_table_arm, retrieve_op) { auto lookup_table = KernelRegistry::Global().Create( "lookup_table"); ASSERT_FALSE(lookup_table.empty()); ASSERT_TRUE(lookup_table.front()); } TEST(lookup_table_arm, init) { LookupTableCompute lookup_table; ASSERT_EQ(lookup_table.precision(), PRECISION(kFloat)); ASSERT_EQ(lookup_table.target(), TARGET(kARM)); } TEST(lookup_table_arm, compute) { LookupTableCompute lookup_table; operators::LookupTableParam param; lite::Tensor w, ids, out, out_ref; int64_t padding_idx = -1; auto w_dim = DDim(std::vector({4, 5})); auto ids_dim = DDim(std::vector({3, 2})); auto out_dim = DDim(std::vector({3, 2, 5})); w.Resize(w_dim); ids.Resize(ids_dim); out.Resize(out_dim); out_ref.Resize(out_dim); auto *w_data = w.mutable_data(); auto *ids_data = ids.mutable_data(); auto *out_data = out.mutable_data(); auto *out_ref_data = out_ref.mutable_data(); int w_num = w_dim.production(); for (int i = 0; i < w_num; i++) { w_data[i] = static_cast(i + 1) / (w_num + 1); } int ids_num = ids_dim.production(); for (int i = 0; i < ids_num; i++) { ids_data[i] = i % 4; } int out_num = out_dim.production(); param.W = &w; param.Ids = &ids; param.Out = &out; lookup_table.SetParam(param); lookup_table.Run(); param.Out = &out_ref; lookup_table_compute_ref(param); for (int i = 0; i < out_num; i++) { EXPECT_NEAR(out_data[i], out_ref_data[i], 1e-5); } } } // namespace arm } // namespace kernels } // namespace lite } // namespace paddle USE_LITE_KERNEL(lookup_table, kARM, kFloat, kNCHW, def);