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[MLU] add int64 support for allgather. #46830

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Oct 11, 2022
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[MLU] add int64 support for allgather. #46830

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50 changes: 44 additions & 6 deletions paddle/fluid/operators/collective/c_allgather_op_mlu.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */

#include "paddle/fluid/operators/collective/c_allgather_op.h"
#include "paddle/fluid/operators/mlu/mlu_baseop.h"

#if defined(PADDLE_WITH_CNCL)
#include "paddle/fluid/platform/collective_helper.h"
Expand All @@ -27,15 +28,14 @@ template <typename T>
class CAllGatherOpMLUKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
auto place = ctx.GetPlace();
auto dev_ctx = platform::DeviceContextPool::Instance().Get(place);
#if defined(PADDLE_WITH_CNCL)
auto x = ctx.Input<phi::DenseTensor>("X");
auto out = ctx.Output<phi::DenseTensor>("Out");
cnclDataType_t dtype =
platform::ToCNCLDataType(framework::TransToProtoVarType(x->dtype()));

int nranks = ctx.Attr<int>("nranks");
int rid = ctx.Attr<int>("ring_id");
auto place = ctx.GetPlace();
auto comm = platform::CNCLCommContext::Instance().Get(rid, place);
PADDLE_ENFORCE_EQ(
nranks,
Expand All @@ -48,19 +48,56 @@ class CAllGatherOpMLUKernel : public framework::OpKernel<T> {
out->mutable_data<T>(out_dims, place);

uint32_t send_numel = x->numel();
void* send_buff = reinterpret_cast<void*>(const_cast<T*>(x->data<T>()));
void* recv_buff = reinterpret_cast<void*>(out->data<T>());
void* send_buff;
void* recv_buff;
phi::DenseTensor in_tensor, out_tensor;
if (framework::TransToProtoVarType(x->dtype()) ==
framework::proto::VarType::INT64) {
// cast from int64 to int32 since cncl do not support int64
in_tensor.mutable_data<int32_t>(x->dims(), place);
out_tensor.mutable_data<int32_t>(out->dims(), place);
MLUCnnlTensorDesc x_int64_desc(*x);
MLUCnnlTensorDesc x_int32_desc(in_tensor);
cnnlCastDataType_t cast_type = GetCastDataType(VT::INT64, VT::INT32);
MLUCnnl::Cast(ctx,
cast_type,
x_int64_desc.get(),
GetBasePtr(x),
x_int32_desc.get(),
GetBasePtr(&in_tensor));
send_buff = reinterpret_cast<void*>(in_tensor.data<int32_t>());
recv_buff = reinterpret_cast<void*>(out_tensor.data<int32_t>());
} else {
in_tensor.ShareDataWith(*x);
out_tensor.ShareDataWith(*out);
send_buff = reinterpret_cast<void*>(in_tensor.data<T>());
recv_buff = reinterpret_cast<void*>(out_tensor.data<T>());
}

mluStream stream = nullptr;
if (ctx.Attr<bool>("use_calc_stream")) {
auto dev_ctx = platform::DeviceContextPool::Instance().Get(place);
stream = static_cast<platform::MLUDeviceContext*>(dev_ctx)->stream();
} else {
stream = comm->stream();
}
cnclDataType_t dtype = platform::ToCNCLDataType(
framework::TransToProtoVarType(in_tensor.dtype()));

PADDLE_ENFORCE_MLU_SUCCESS(cnclAllGather(
send_buff, recv_buff, send_numel, dtype, comm->comm(), stream));
if (framework::TransToProtoVarType(x->dtype()) ==
framework::proto::VarType::INT64) {
// cast back from int64 out_tensor to out
MLUCnnlTensorDesc out_int64_desc(*out);
MLUCnnlTensorDesc out_int32_desc(out_tensor);
cnnlCastDataType_t cast_type = GetCastDataType(VT::INT32, VT::INT64);
MLUCnnl::Cast(ctx,
cast_type,
out_int32_desc.get(),
GetBasePtr(&out_tensor),
out_int64_desc.get(),
GetBasePtr(out));
}
#else
PADDLE_THROW(platform::errors::PreconditionNotMet(
"PaddlePaddle should compile with MLU."));
Expand All @@ -80,4 +117,5 @@ REGISTER_OP_MLU_KERNEL(c_allgather,
ops::CAllGatherOpMLUKernel<int>,
ops::CAllGatherOpMLUKernel<int8_t>,
ops::CAllGatherOpMLUKernel<int16_t>,
ops::CAllGatherOpMLUKernel<int64_t>,
ops::CAllGatherOpMLUKernel<plat::float16>);