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fix: fix scatter and reduce_scatter implementation #40

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Jul 16, 2021
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fix: fix scatter and reduce_scatter implementation #40

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10 changes: 5 additions & 5 deletions bagua-core-internal/src/communicators/mod.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -820,13 +820,13 @@ impl BaguaCommunicatorInner {
cpp::cpp!([send_ptr as "void *", recv_ptr as "void *", count as "size_t", src as "int", communicator_ptr as "Al::NCCLCommunicator *", nccl_tensor_type as "ncclDataType_t"]
{
if (nccl_tensor_type == ncclDataType_t::ncclFloat32) {
Al::Gather<Al::NCCLBackend>(static_cast<float*>(send_ptr), static_cast<float*>(recv_ptr), count, src, *communicator_ptr);
Al::Scatter<Al::NCCLBackend>(static_cast<float*>(send_ptr), static_cast<float*>(recv_ptr), count, src, *communicator_ptr);
} else if (nccl_tensor_type == ncclDataType_t::ncclFloat16) {
Al::Gather<Al::NCCLBackend>(static_cast<__half*>(send_ptr), static_cast<__half*>(recv_ptr), count, src, *communicator_ptr);
Al::Scatter<Al::NCCLBackend>(static_cast<__half*>(send_ptr), static_cast<__half*>(recv_ptr), count, src, *communicator_ptr);
} else if (nccl_tensor_type == ncclDataType_t::ncclUint8) {
Al::Gather<Al::NCCLBackend>(static_cast<unsigned char*>(send_ptr), static_cast<unsigned char*>(recv_ptr), count, src, *communicator_ptr);
Al::Scatter<Al::NCCLBackend>(static_cast<unsigned char*>(send_ptr), static_cast<unsigned char*>(recv_ptr), count, src, *communicator_ptr);
} else if (nccl_tensor_type == ncclDataType_t::ncclInt64) {
Al::Gather<Al::NCCLBackend>(static_cast<long long int*>(send_ptr), static_cast<long long int*>(recv_ptr), count, src, *communicator_ptr);
Al::Scatter<Al::NCCLBackend>(static_cast<long long int*>(send_ptr), static_cast<long long int*>(recv_ptr), count, src, *communicator_ptr);
} else {
fputs("unsupport tensor data type.\n", stderr);
abort();
Expand Down Expand Up @@ -906,7 +906,7 @@ impl BaguaCommunicatorInner {
);
let communicator_ptr = self.comm_ptr;
let tensor_ptr = tensor.data_ptr();
let count = tensor.num_elements_allocated();
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let count = tensor.num_elements_allocated() / self.nranks;
let nccl_tensor_type = tensor.dtype().to_nccl_datatype();
unsafe {
cpp::cpp!([tensor_ptr as "void *", count as "size_t", op as "uint8_t", communicator_ptr as "Al::NCCLCommunicator *", nccl_tensor_type as "ncclDataType_t"]
Expand Down