Unit test refactor (#500)
Refactoring and consolidating single-process / multi-process unit testing
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/*************************************************************************
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* Copyright (c) 2022 Advanced Micro Devices, Inc. All rights reserved.
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*
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* See LICENSE.txt for license information
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************************************************************************/
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#include "CollectiveArgs.hpp"
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#include "gtest/gtest.h"
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namespace RcclUnitTesting
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{
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ErrCode CollectiveArgs::SetArgs(int const globalRank,
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int const totalRanks,
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int const deviceId,
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ncclFunc_t const funcType,
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ncclDataType_t const dataType,
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ncclRedOp_t const redOp,
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int const root,
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size_t const numInputElements,
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size_t const numOutputElements,
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ScalarTransport const scalarTransport,
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int const scalarMode)
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{
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// Free scalar based on previous scalarMode
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if (scalarMode != -1)
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{
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if (this->localScalar.ptr != nullptr)
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{
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if (this->scalarMode == 0) this->localScalar.FreeGpuMem();
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if (this->scalarMode == 1) hipHostFree(this->localScalar.ptr);
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}
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}
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this->globalRank = globalRank;
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this->totalRanks = totalRanks;
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this->deviceId = deviceId;
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this->funcType = funcType;
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this->dataType = dataType;
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this->redOp = redOp;
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this->root = root;
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this->numInputElements = numInputElements;
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this->numOutputElements = numOutputElements;
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this->scalarTransport = scalarTransport;
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this->scalarMode = scalarMode;
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if (scalarMode != -1)
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{
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size_t const numBytes = DataTypeToBytes(dataType);
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if (scalarMode == ncclScalarDevice)
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{
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CHECK_CALL(this->localScalar.AllocateGpuMem(numBytes));
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CHECK_HIP(hipMemcpy(this->localScalar.ptr, scalarTransport.ptr + (globalRank * numBytes),
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numBytes, hipMemcpyHostToDevice));
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}
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else if (scalarMode == ncclScalarHostImmediate)
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{
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CHECK_HIP(hipHostMalloc(&this->localScalar.ptr, numBytes, 0));
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memcpy(this->localScalar.ptr, scalarTransport.ptr + (globalRank * numBytes), numBytes);
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}
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}
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return TEST_SUCCESS;
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}
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ErrCode CollectiveArgs::AllocateMem(bool const inPlace,
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bool const useManagedMem)
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{
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this->numInputBytesAllocated = this->numInputElements * DataTypeToBytes(this->dataType);
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this->numOutputBytesAllocated = this->numOutputElements * DataTypeToBytes(this->dataType);
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this->numInputElementsAllocated = this->numInputElements;
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this->numOutputElementsAllocated = this->numOutputElements;
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this->inPlace = inPlace;
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this->useManagedMem = useManagedMem;
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if (hipSetDevice(this->deviceId) != hipSuccess)
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{
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ERROR("Unable to call hipSetDevice to set to GPU %d\n", this->deviceId);
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return TEST_FAIL;
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}
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if (inPlace)
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{
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if (this->funcType == ncclCollScatter)
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{
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CHECK_CALL(this->inputGpu.AllocateGpuMem(this->numInputBytesAllocated, useManagedMem));
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this->outputGpu.Attach(this->inputGpu.U1 + (this->globalRank * this->numOutputBytesAllocated));
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}
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else if (this->funcType == ncclCollGather)
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{
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CHECK_CALL(this->outputGpu.AllocateGpuMem(this->numOutputBytesAllocated, useManagedMem));
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this->inputGpu.Attach(this->outputGpu.U1 + (this->globalRank * this->numInputBytesAllocated));
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}
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else
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{
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size_t const numBytes = std::max(this->numInputBytesAllocated, this->numOutputBytesAllocated);
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CHECK_CALL(this->inputGpu.AllocateGpuMem(numBytes, useManagedMem));
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this->outputGpu.Attach(this->inputGpu.ptr);
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}
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CHECK_CALL(this->expected.AllocateCpuMem(this->numOutputBytesAllocated));
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}
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else
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{
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CHECK_CALL(this->inputGpu.AllocateGpuMem(this->numInputBytesAllocated, useManagedMem));
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CHECK_CALL(this->outputGpu.AllocateGpuMem(this->numOutputBytesAllocated, useManagedMem));
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CHECK_CALL(this->expected.AllocateCpuMem(this->numOutputBytesAllocated));
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}
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CHECK_CALL(this->outputCpu.AllocateCpuMem(this->numOutputBytesAllocated));
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return TEST_SUCCESS;
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}
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ErrCode CollectiveArgs::PrepareData(CollFuncPtr const prepareDataFunc)
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{
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CollFuncPtr prepFunc = (prepareDataFunc == nullptr ? DefaultPrepareDataFunc : prepareDataFunc);
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return prepFunc(*this);
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}
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ErrCode CollectiveArgs::ValidateResults()
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{
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// Ignore non-root outputs for collectives with a root
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if (CollectiveArgs::UsesRoot(this->funcType) && this->root != this->globalRank) return TEST_SUCCESS;
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size_t const numOutputBytes = (this->numOutputElements * DataTypeToBytes(this->dataType));
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CHECK_HIP(hipMemcpy(this->outputCpu.ptr, this->outputGpu.ptr, numOutputBytes, hipMemcpyDeviceToHost));
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bool isMatch = true;
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CHECK_CALL(this->outputCpu.IsEqual(this->dataType,
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this->numOutputElements,
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this->expected,
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true,
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isMatch));
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if (!isMatch) ERROR("Mismatch for %s\n", this->GetDescription().c_str());
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return isMatch ? TEST_SUCCESS : TEST_FAIL;
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}
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ErrCode CollectiveArgs::DeallocateMem()
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{
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// If in-place, either only inputGpu or outputGpu was allocated
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if (this->inPlace)
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{
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if (this->funcType == ncclCollGather)
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this->outputGpu.FreeGpuMem();
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else
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this->inputGpu.FreeGpuMem();
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}
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else
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{
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this->inputGpu.FreeGpuMem();
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this->outputGpu.FreeGpuMem();
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}
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this->outputCpu.FreeCpuMem();
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this->expected.FreeCpuMem();
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if (this->localScalar.ptr != nullptr)
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{
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if (this->scalarMode == 0) this->localScalar.FreeGpuMem();
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if (this->scalarMode == 1) CHECK_HIP(hipHostFree(this->localScalar.ptr));
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}
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return TEST_SUCCESS;
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}
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std::string CollectiveArgs::GetDescription() const
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{
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std::stringstream ss;
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ss << "(Rank " << this->globalRank << ") ";
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switch (this->funcType)
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{
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case ncclCollBroadcast: ss << "ncclBroadcast"; break;
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case ncclCollReduce: ss << "ncclReduce"; break;
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case ncclCollAllGather: ss << "ncclAllGather"; break;
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case ncclCollReduceScatter: ss << "ncclReduceScatter"; break;
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case ncclCollAllReduce: ss << "ncclAllReduce"; break;
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case ncclCollGather: ss << "ncclGather"; break;
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case ncclCollScatter: ss << "ncclScatter"; break;
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case ncclCollAllToAll: ss << "ncclAllToAll"; break;
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case ncclCollSend: ss << "ncclSend"; break;
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case ncclCollRecv: ss << "ncclRevv"; break;
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default: ss << "[Unknown]"; break;
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}
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ss << " " << ncclDataTypeNames[this->dataType] << " ";
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if (this->funcType == ncclCollReduce ||
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this->funcType == ncclCollReduceScatter ||
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this->funcType == ncclCollAllReduce)
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{
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if (this->redOp < ncclNumOps)
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{
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ss << ncclRedOpNames[this->redOp] << " ";
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}
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else
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{
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ss << "CustomScalar ";
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PtrUnion scalarsPerRank;
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scalarsPerRank.Attach(scalarsPerRank.ptr);
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switch (this->dataType)
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{
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case ncclInt8: ss << scalarsPerRank.I1[this->globalRank]; break;
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case ncclUint8: ss << scalarsPerRank.U1[this->globalRank]; break;
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case ncclInt32: ss << scalarsPerRank.I4[this->globalRank]; break;
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case ncclUint32: ss << scalarsPerRank.U4[this->globalRank]; break;
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case ncclInt64: ss << scalarsPerRank.I8[this->globalRank]; break;
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case ncclUint64: ss << scalarsPerRank.U8[this->globalRank]; break;
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case ncclFloat32: ss << scalarsPerRank.F4[this->globalRank]; break;
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case ncclFloat64: ss << scalarsPerRank.F8[this->globalRank]; break;
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case ncclBfloat16: ss << scalarsPerRank.B2[this->globalRank]; break;
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default: ss << "(UNKNOWN)";
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}
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ss << " ";
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}
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}
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if (this->funcType == ncclCollBroadcast ||
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this->funcType == ncclCollReduce ||
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this->funcType == ncclCollGather ||
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this->funcType == ncclCollScatter)
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{
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ss << "Root " << this->root << " ";
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}
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if (this->funcType == ncclCollSend ||
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this->funcType == ncclCollRecv)
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{
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ss << "Peer " << this->root << " ";
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}
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ss << "#In: " << this->numInputElements;
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ss << " #Out: " << this->numOutputElements;
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return ss.str();
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}
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void CollectiveArgs::GetNumElementsForFuncType(ncclFunc_t const funcType,
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int const N,
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int const totalRanks,
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int* numInputElements,
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int* numOutputElements)
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{
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switch (funcType)
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{
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case ncclCollBroadcast:
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case ncclCollReduce:
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case ncclCollAllReduce:
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*numInputElements = N;
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*numOutputElements = N;
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break;
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case ncclCollGather:
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case ncclCollAllGather:
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*numInputElements = N;
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*numOutputElements = totalRanks * N;
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break;
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case ncclCollScatter:
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case ncclCollReduceScatter:
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*numInputElements = totalRanks * N;
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*numOutputElements = N;
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break;
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case ncclCollAllToAll:
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*numInputElements = totalRanks * N;
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*numOutputElements = totalRanks * N;
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break;
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default:
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*numInputElements = N;
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*numOutputElements = N;
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break;
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}
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}
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bool CollectiveArgs::UsesReduce(ncclFunc_t const funcType)
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{
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return (funcType == ncclCollReduce ||
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funcType == ncclCollAllReduce ||
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funcType == ncclCollReduceScatter);
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}
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bool CollectiveArgs::UsesRoot(ncclFunc_t const funcType)
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{
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return (funcType == ncclCollBroadcast ||
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funcType == ncclCollReduce ||
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funcType == ncclCollGather ||
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funcType == ncclCollScatter);
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}
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}
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