[NPU] Support npu kernel for c sync stream op (#31386)
* sync stream npu op * add with_ascend_acl * update c++ unittestrevert-31562-mean
xiayanming
4 years ago
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GitHub
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e1c33a6d69
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f1fdddfdc8
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/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#ifndef _WIN32
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#include <unistd.h>
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#endif
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#include <stdio.h>
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#include <string>
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#include <thread> // NOLINT
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#include <vector>
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#include "gtest/gtest.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/framework/operator.h"
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/operators/math/math_function.h"
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#include "paddle/fluid/string/printf.h"
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namespace f = paddle::framework;
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namespace p = paddle::platform;
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namespace m = paddle::operators::math;
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USE_OP(elementwise_add);
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USE_OP_DEVICE_KERNEL(elementwise_add, NPU);
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USE_NO_KERNEL_OP(c_sync_calc_stream);
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template <typename T>
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void Compare(f::Scope* scope, const p::DeviceContext& ctx) {
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// init
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auto x = scope->Var("X");
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auto tensor_x = x->GetMutable<f::LoDTensor>();
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auto y = scope->Var("Y");
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auto tensor_y = y->GetMutable<f::LoDTensor>();
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std::vector<T> init_x;
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for (int64_t i = 0; i < 10 * 10; ++i) {
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init_x.push_back(static_cast<T>(1.0));
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}
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std::vector<T> init_y;
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for (int64_t i = 0; i < 10 * 10; ++i) {
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init_y.push_back(static_cast<T>(2.0));
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}
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TensorFromVector(init_x, ctx, tensor_x);
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tensor_x->Resize({10, 10});
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TensorFromVector(init_y, ctx, tensor_y);
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tensor_y->Resize({10, 10});
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f::AttributeMap attrs;
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auto place = ctx.GetPlace();
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auto out = scope->Var("Out");
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auto tensor_out = out->GetMutable<f::LoDTensor>();
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// sync data
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auto sync_op0 = f::OpRegistry::CreateOp("c_sync_calc_stream", {{"X", {"X"}}},
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{{"Out", {"Out"}}}, attrs);
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sync_op0->Run(*scope, place);
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// run
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auto op =
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f::OpRegistry::CreateOp("elementwise_add", {{"X", {"X"}}, {"Y", {"Y"}}},
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{{"Out", {"Out"}}}, attrs);
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op->Run(*scope, place);
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// sync op run
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auto sync_op = f::OpRegistry::CreateOp("c_sync_calc_stream", {{"X", {"X"}}},
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{{"Out", {"Out"}}}, attrs);
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sync_op->Run(*scope, place);
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std::vector<T> out_vec;
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TensorToVector(*tensor_out, ctx, &out_vec);
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// sync op copy
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auto sync_op2 = f::OpRegistry::CreateOp("c_sync_calc_stream", {{"X", {"X"}}},
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{{"Out", {"Out"}}}, attrs);
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sync_op2->Run(*scope, place);
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float expected = 3.0;
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EXPECT_EQ(out_vec.size(), init_x.size());
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for (uint32_t i = 0; i < out_vec.size(); i++) {
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EXPECT_EQ(out_vec[i], static_cast<T>(expected));
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}
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}
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TEST(c_sync_calc_stream, NPU_fp32) {
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f::Scope scope;
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p::NPUDeviceContext ctx(p::NPUPlace(0));
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Compare<float>(&scope, ctx);
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}
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@ -0,0 +1,131 @@
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/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#ifndef _WIN32
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#include <unistd.h>
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#endif
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#include <stdio.h>
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#include <string>
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#include <thread> // NOLINT
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#include <vector>
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#include "gtest/gtest.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/framework/operator.h"
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/operators/dropout_op.h"
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#include "paddle/fluid/operators/math/math_function.h"
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#include "paddle/fluid/string/printf.h"
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#if defined(PADDLE_WITH_ASCEND_CL)
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#include "paddle/fluid/platform/collective_helper.h"
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#include "paddle/fluid/platform/hccl_helper.h"
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#endif
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namespace f = paddle::framework;
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namespace p = paddle::platform;
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namespace m = paddle::operators::math;
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USE_OP(c_broadcast);
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USE_NO_KERNEL_OP(c_sync_comm_stream);
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USE_NO_KERNEL_OP(c_comm_init_hcom);
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USE_OP_DEVICE_KERNEL(c_broadcast, NPU);
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void Prepare(f::Scope* scope, const p::DeviceContext& ctx) {
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int rank_id = atoi(getenv("RANK_ID"));
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int device_id = atoi(getenv("DEVICE_ID"));
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printf("rank_id = %d, device_id = %d\n", rank_id, device_id);
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std::vector<int> rank_ids{0, 1};
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f::AttributeMap comm_init_attrs;
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comm_init_attrs["ring_id"] = 0;
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comm_init_attrs["nranks"] = 2;
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comm_init_attrs["rank"] = rank_id;
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comm_init_attrs["device_id"] = device_id;
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comm_init_attrs["rank_ids"] = rank_ids;
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auto comm_init_op =
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f::OpRegistry::CreateOp("c_comm_init_hcom", {}, {}, comm_init_attrs);
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auto place = ctx.GetPlace();
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comm_init_op->Run(*scope, place);
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ctx.Wait();
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}
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void TestHCCLBroadcastOp(f::Scope* scope, const p::DeviceContext& ctx) {
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std::cout << "BEGIN TEST:" << __FUNCTION__ << std::endl;
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// init
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auto x = scope->Var("X");
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auto tensor_x = x->GetMutable<f::LoDTensor>();
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int num = 2;
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std::vector<float> init;
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int rank_id = atoi(getenv("RANK_ID"));
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std::cout << "rank_id:" << rank_id << std::endl;
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for (int64_t i = 0; i < num * num; ++i) {
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init.push_back(1.0 + rank_id);
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std::cout << init[0];
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}
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std::cout << std::endl;
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TensorFromVector(init, ctx, tensor_x);
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tensor_x->Resize({num, num});
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ctx.Wait();
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auto place = ctx.GetPlace();
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auto out = scope->Var("Out");
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auto tensor_out = out->GetMutable<f::LoDTensor>();
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tensor_out->Resize({num, num});
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tensor_out->mutable_data<float>(place); // allocate
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ctx.Wait();
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// run
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f::AttributeMap attrs;
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attrs["tag"] = std::string("tagx");
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attrs["root"] = 0;
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attrs["ring_id"] = 0;
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auto op = f::OpRegistry::CreateOp("c_broadcast", {{"X", {"X"}}},
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{{"Out", {"Out"}}}, attrs);
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op->Run(*scope, place);
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// comm sync
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auto sync_op = f::OpRegistry::CreateOp("c_sync_comm_stream", {{"X", {"X"}}},
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{{"Out", {"Out"}}}, attrs);
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sync_op->Run(*scope, place);
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// ctx.Wait();
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std::vector<float> out_vec;
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TensorToVector(*tensor_out, ctx, &out_vec);
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EXPECT_EQ(out_vec.size(), init.size());
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for (uint32_t i = 0; i < out_vec.size(); i++) {
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EXPECT_EQ(out_vec[i], 1.0);
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}
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}
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TEST(c_broadcast, NPU) {
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f::Scope scope;
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char* npu_id = getenv("FLAGS_selected_npus");
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p::NPUDeviceContext ctx(p::NPUPlace(atoi(npu_id)));
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Prepare(&scope, ctx);
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TestHCCLBroadcastOp(&scope, ctx);
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}
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