// 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. #include "paddle/fluid/operators/shard_index_op.h" #include "paddle/fluid/operators/npu_op_runner.h" namespace paddle { namespace operators { using LoDTensor = framework::LoDTensor; using Tensor = framework::Tensor; template class ShardIndexNPUKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { VLOG(4) << "start kernel"; auto* in = context.Input("X"); auto* out = context.Output("Out"); int index_num = context.Attr("index_num"); int nshards = context.Attr("nshards"); int shard_id = context.Attr("shard_id"); int ignore_value = context.Attr("ignore_value"); PADDLE_ENFORCE_GT( index_num, 0, platform::errors::InvalidArgument( "The value 'index_num' for Op(shard_index) must be greater than 0, " "but the value given is %d.", index_num)); PADDLE_ENFORCE_GT(nshards, 0, platform::errors::InvalidArgument( "The value 'nshard' for Op(shard_index) must be " "greater than 0, but the value given is %d.", nshards)); PADDLE_ENFORCE_GE( shard_id, 0, platform::errors::InvalidArgument( "The value 'shard_id' for Op(shard_index) must be greater or " "equal to 0, but the value given is %d.", shard_id)); PADDLE_ENFORCE_LT( shard_id, nshards, platform::errors::InvalidArgument( "The value 'shard_id' for Op(shard_index) must be less than " "nshards (%d), but the value given is %d.", nshards, shard_id)); int shard_size = (index_num + nshards - 1) / nshards; auto place = context.GetPlace(); out->Resize(in->dims()); out->set_lod(in->lod()); out->mutable_data(place); Tensor tmp(in->type()); tmp.mutable_data(framework::DDim({1}), place); FillNpuTensorWithConstant(&tmp, shard_size); Tensor condition(framework::proto::VarType::BOOL); condition.mutable_data(in->dims(), place); Tensor tmp2(in->type()); tmp2.mutable_data(in->dims(), place); Tensor tmp3(in->type()); tmp3.mutable_data(in->dims(), place); auto stream = context.template device_context() .stream(); NpuOpRunner runner; runner.AddInputs({*in, tmp}); runner.AddOutputs({tmp2}); runner.SetType("Mod"); runner.Run(stream); NpuOpRunner runner1; runner1.AddInputs({*in, tmp}); runner1.AddOutputs({tmp3}); runner1.SetType("FloorDiv"); runner1.Run(stream); FillNpuTensorWithConstant(&tmp, shard_id); NpuOpRunner runner2; runner2.AddInputs({tmp3, tmp}); runner2.AddOutputs({condition}); runner2.SetType("Equal"); runner2.Run(stream); Tensor tmp4(in->type()); tmp4.mutable_data(in->dims(), place); FillNpuTensorWithConstant(&tmp4, ignore_value); tmp4.Resize(in->dims()); NpuOpRunner runner3; runner3.AddInputs({condition, tmp2, tmp4}); runner3.AddOutputs({*out}); runner3.SetType("Select"); runner3.Run(stream); } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; REGISTER_OP_NPU_KERNEL(shard_index, ops::ShardIndexNPUKernel, ops::ShardIndexNPUKernel);