// 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/x86/search_grnn_compute.h" #include #include #include #include #include "lite/core/op_registry.h" namespace paddle { namespace lite { namespace kernels { namespace x86 { TEST(search_grnn_x86, retrive_op) { auto kernel = KernelRegistry::Global().Create( "search_grnn"); ASSERT_FALSE(kernel.empty()); ASSERT_TRUE(kernel.front()); } TEST(search_grnn_x86, init) { SearchGrnnCompute ssdc; ASSERT_EQ(ssdc.precision(), PRECISION(kFloat)); ASSERT_EQ(ssdc.target(), TARGET(kX86)); } TEST(search_grnn_x86, run_test) { int num_input = 128; int num_hidden = 128; int num_batch = 3; lite::Tensor x, wi, wh, out, idx_sorted_by_width, layout_input, tmp_buffer; x.Resize({num_batch, num_input}); wi.Resize({3, num_hidden, num_input}); wh.Resize({3, num_hidden, num_hidden}); // out.Resize({num_batch, num_hidden}); LoD x_lod{}; x_lod.push_back({0, 1, 3}); x.set_lod(x_lod); auto* x_data = x.mutable_data(); for (int64_t i = 0; i < x.numel(); i++) { x_data[i] = static_cast(i); } auto* wi_data = wi.mutable_data(); for (int64_t i = 0; i < wi.numel(); i++) { wi_data[i] = static_cast(i); } auto* wh_data = wh.mutable_data(); for (int64_t i = 0; i < wh.numel(); i++) { wh_data[i] = static_cast(i); } std::unique_ptr ctx(new KernelContext); ctx->As(); operators::SearchGrnnParam param; param.x = &x; param.wi = &wi; param.wh = &wh; param.out = &out; param.idx_sorted_by_width = &idx_sorted_by_width; param.layout_input = &layout_input; param.tmp_buffer = &tmp_buffer; param.num_input = num_input; param.num_hidden = num_hidden; SearchGrnnCompute sgc; sgc.SetContext(std::move(ctx)); sgc.SetParam(param); sgc.Run(); // std::vector ref_results = {0, 1, 2, 3, 4, 5, 6, 7, 16, 17, 18, 19}; auto* out_data = out.mutable_data(); LOG(INFO) << out.numel(); for (int i = 0; i < out.numel(); i++) { // EXPECT_NEAR(out_data[i], ref_results[i], 1e-3); LOG(INFO) << out_data[i]; } } } // namespace x86 } // namespace kernels } // namespace lite } // namespace paddle USE_LITE_KERNEL(search_grnn, kX86, kFloat, kNCHW, def);