/* 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. */ #ifndef _WIN32 #include #endif #include #include #include // NOLINT #include #include #include #include "gtest/gtest.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/operator.h" #include "paddle/fluid/framework/program_desc.h" #include "paddle/fluid/operators/dropout_op.h" #include "paddle/fluid/operators/math/math_function.h" #include "paddle/fluid/string/printf.h" namespace f = paddle::framework; namespace p = paddle::platform; namespace m = paddle::operators::math; USE_OP(transpose); USE_OP_DEVICE_KERNEL(transpose, NPU); template void Compare(f::Scope* scope, const p::DeviceContext& ctx) { // init auto x = scope->Var("X"); auto out = scope->Var("Out"); auto* x_t = x->GetMutable(); auto* out_t = out->GetMutable(); auto place = ctx.GetPlace(); int dim0 = 2; int dim1 = 3; TensorFromVector(std::vector({0, 1, 2, 3, 4, 5}), ctx, x_t); ctx.Wait(); x_t->Resize({dim0, dim1}); out_t->Resize({dim0, dim1}); ctx.Wait(); out_t->mutable_data(place); ctx.Wait(); f::AttributeMap attrs = { {"axis", std::vector({1, 0})}, {"data_format", std::string("AnyLayout")} }; auto op = f::OpRegistry::CreateOp("transpose", {{"X", {"X"}}}, {{"Out", {"Out"}}}, attrs); ctx.Wait(); op->Run(*scope, place); ctx.Wait(); std::vector out_v; TensorToVector(*out_t, ctx, &out_v); ctx.Wait(); EXPECT_EQ(out_t->numel(), dim0 * dim1); EXPECT_EQ(out_v[0], 0); EXPECT_EQ(out_v[1], 3); EXPECT_EQ(out_v[2], 1); EXPECT_EQ(out_v[3], 4); EXPECT_EQ(out_v[4], 2); EXPECT_EQ(out_v[5], 5); } template void CompareGrad(f::Scope* scope, const p::DeviceContext& ctx) { // init auto x = scope->Var("X"); auto x_grad = scope->Var("X@GRAD"); auto out = scope->Var("Out"); auto out_grad = scope->Var("Out@GRAD"); auto* x_grad_t = x_grad->GetMutable(); auto* x_t = x->GetMutable(); auto* out_grad_t = out_grad->GetMutable(); auto* out_t = out->GetMutable(); int dim0 = 2; int dim1 = 3; auto place = ctx.GetPlace(); TensorFromVector(std::vector({0, 1, 2, 3, 4, 5}), ctx, out_grad_t); TensorFromVector(std::vector({0, 1, 2, 3, 4, 5}), ctx, x_t); ctx.Wait(); x_grad_t->Resize({dim0, dim1}); x_t->Resize({dim0, dim1}); out_grad_t->Resize({dim0, dim1}); out_t->Resize({dim0, dim1}); x_grad_t->mutable_data(place); out_t->mutable_data(place); ctx.Wait(); f::AttributeMap attrs = { {"axis", std::vector({1, 0})}, {"data_format", std::string("AnyLayout")} }; auto op = f::OpRegistry::CreateOp( "transpose_grad", {{"Out@GRAD", {"Out@GRAD"}}, {"X", {"X"}}, {"Out", {"Out"}}}, {{"X@GRAD", {"X@GRAD"}}}, attrs); op->Run(*scope, place); ctx.Wait(); std::vector out_v; TensorToVector(*x_grad_t, ctx, &out_v); ctx.Wait(); EXPECT_EQ(x_grad_t->numel(), dim0 * dim1); EXPECT_EQ(out_v[0], 0); EXPECT_EQ(out_v[1], 3); EXPECT_EQ(out_v[2], 1); EXPECT_EQ(out_v[3], 4); EXPECT_EQ(out_v[4], 2); EXPECT_EQ(out_v[5], 5); } TEST(transpose, NPU_fp32) { f::Scope scope; p::NPUDeviceContext ctx(p::NPUPlace(0)); Compare(&scope, ctx); } TEST(transpose_grad, NPU_fp32) { f::Scope scope; p::NPUDeviceContext ctx(p::NPUPlace(0)); CompareGrad(&scope, ctx); }