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[ROCm] Fixing build for CIs (#10558)

Browse source 
* fix build

* fix build

* fix win build

* apply same fix for rocm

* fix CI

* update comments

* trigger build

Co-authored-by: Ethan Tao <ettao@microsoft.com@orttrainingdev7.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
This commit is contained in:
ytaous 2022-02-16 15:36:46 -08:00 committed by GitHub
parent 3be3db5180
commit e71d77e974
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GPG key ID: 4AEE18F83AFDEB23
5 changed files with 12 additions and 14 deletions
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8
onnxruntime/core/providers/cuda/cudnn_common.cc
View file

@ -137,15 +137,9 @@ cudnnDataType_t CudnnTensor::GetDataType<half>() {
}
template <>
cudnnDataType_t CudnnTensor::GetDataType<BFloat16>() {
#if CUDNN_VERSION >= 8100
return CUDNN_DATA_BFLOAT16;
#else
ORT_THROW("cuDNN version is too low to support BFloat16.");
// Not reachable but GCC complains
ORT_THROW("cuDNN doesn't support BFloat16.");
return CUDNN_DATA_FLOAT;
#endif
}
template <>

5
onnxruntime/core/providers/cuda/reduction/reduction_ops.cc
View file

@ -511,15 +511,16 @@ Status ReduceComputeCore(CUDAExecutionProvider& cuda_ep, const Tensor& input, Pr
CUDA_RETURN_IF_ERROR(cudaMemsetAsync(output.MutableDataRaw(), 0, output.SizeInBytes(), stream));
IAllocatorUniquePtr<float> temp_X;
cudnnDataType_t cudnn_type_X = CudnnTensor::GetDataType<CudaT>();
cudnnDataType_t cudnn_type_X = CUDNN_DATA_FLOAT;
// Reducesum with BFP16 is not supported by cudnn, so convert input to fp32 then call cudnn
if ((ReduceTensorIndices == CUDNN_REDUCE_TENSOR_FLATTENED_INDICES && std::is_same<T, MLFloat16>::value) ||
(ReduceTensorIndices == CUDNN_REDUCE_TENSOR_NO_INDICES && std::is_same<T, BFloat16>::value)) {
// ArgMax/ArgMin with FP16 are not supported by cudnn, so convert input to fp32 then call cudnn
temp_X = cuda_ep.GetScratchBuffer<float>(input_count);
cudnn_type_X = CUDNN_DATA_FLOAT;
Impl_Cast<CudaT, float>(stream, reinterpret_cast<const CudaT*>(input.template Data<T>()), temp_X.get(), input_shape.Size());
} else {
cudnn_type_X = CudnnTensor::GetDataType<CudaT>();
}
CudnnReduceDescriptor reduce_desc;

3
onnxruntime/core/providers/rocm/miopen_common.cc
View file

@ -93,7 +93,8 @@ miopenDataType_t MiopenTensor::GetDataType<half>() {
template <>
miopenDataType_t MiopenTensor::GetDataType<BFloat16>() {
return miopenBFloat16;
ORT_THROW("miopen doesn't support BFloat16.");
return miopenFloat;
}
template <>

5
onnxruntime/core/providers/rocm/reduction/reduction_ops.cc
View file

@ -509,7 +509,7 @@ Status ReduceComputeCore(ROCMExecutionProvider& rocm_ep, const Tensor& input, Pr
HIP_RETURN_IF_ERROR(hipMemsetAsync(output.MutableDataRaw(), 0, output.SizeInBytes(), stream));
IAllocatorUniquePtr<float> temp_X;
miopenDataType_t miopen_type_X = MiopenTensor::GetDataType<HipT>();
miopenDataType_t miopen_type_X = miopenFloat;
// unlike bfp16 not supported in cudnn, miopen call for bfp16 succeeded below, however, UT shows data error
// so for now, follow the same logic in cudnn and convert input to fp32 then call miopen
@ -517,8 +517,9 @@ Status ReduceComputeCore(ROCMExecutionProvider& rocm_ep, const Tensor& input, Pr
(ReduceTensorIndices == MIOPEN_REDUCE_TENSOR_NO_INDICES && std::is_same<T, BFloat16>::value)) {
// ArgMax/ArgMin with FP16 are not supported by miopen, so convert input to fp32 then call miopen
temp_X = rocm_ep.GetScratchBuffer<float>(input_count);
miopen_type_X = miopenFloat;
Impl_Cast<HipT, float>(stream, reinterpret_cast<const HipT*>(input.template Data<T>()), temp_X.get(), input_shape.Size());
} else {
miopen_type_X = MiopenTensor::GetDataType<HipT>();
}
MiopenReduceDescriptor reduce_desc;

5
onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc
View file

@ -1536,9 +1536,10 @@ TEST(ReductionOpTest, ReduceSumBFloat16) {
// on CUDA - this UT, with axes {0,2}, will go thru cudnn lib only if ATenOp is not initialized
// on ROCM - miopen call succeeded, but results in data error, thus follow the same logic done in cudnn for now
// 4.2 doesn't run properly (data error), thus enable the UT only above 4.3
// TODO - try ROCm 4.5.2 and/or double check the source code on BFloat16 support
#if defined(USE_CUDA) || defined(USE_ROCM)
TEST(ReductionOpTest, DISABLED_ReduceSumBFloat16_2) {
#if defined(USE_CUDA) || (defined(USE_ROCM) && ROCM_VERSION >= 40300)
TEST(ReductionOpTest, ReduceSumBFloat16_2) {
OpTester test("ReduceSum", 14);
test.AddAttribute("keepdims", (int64_t)0);
test.AddInput<BFloat16>("data", {3, 2, 2},