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onnxruntime/tools/ci_build/amd_hipify.py
Weixing Zhang bb1af718b5
fix build failures due to recent change(858040fa) in CUDA EP (#5736) 
Some part of code for reduction kernels has been changed in 858040fa,
which cause failures in rocm build since ROCm EP shares some code with
CUDA EP. This PR is to quick fix this failure by not sharing two files
for now to unblock CI enabling on ROCm EP. Another PR for leveraging
858040fa for ROCm EP will be done later.
2020-11-09 08:41:30 -08:00

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#!/usr/bin/env python3
import os
import subprocess
contrib_ops_path = 'onnxruntime/contrib_ops'
core_ops_path = 'onnxruntime/core/providers'
training_ops_path = 'orttraining/orttraining/training_ops'
contrib_ops_files = [
'bert/attention.cc',
'bert/attention.h',
'bert/attention_impl.cu',
'bert/attention_impl.h',
'bert/embed_layer_norm.cc',
'bert/embed_layer_norm.h',
'bert/embed_layer_norm_impl.cu',
'bert/embed_layer_norm_impl.h',
'bert/fast_gelu_impl.cu',
'bert/layer_norm.cuh',
'bert/skip_layer_norm.cc',
'bert/skip_layer_norm.h',
'bert/skip_layer_norm_impl.cu',
'bert/skip_layer_norm_impl.h',
'math/bias_softmax.cc',
'math/bias_softmax.h',
'math/bias_softmax_impl.cu',
'math/binary_elementwise_ops.cc',
'math/binary_elementwise_ops.h',
'math/binary_elementwise_ops_impl.cu',
'math/binary_elementwise_ops_impl.h',
'math/complex_mul.cc',
'math/complex_mul.h',
'math/complex_mul_impl.cu',
'math/complex_mul_impl.h',
'math/cufft_plan_cache.h',
'math/fft_ops.cc',
'math/fft_ops.h',
'math/fft_ops_impl.cu',
'math/fft_ops_impl.h',
'quantization/attention_quantization.cc',
'quantization/attention_quantization.h',
'quantization/attention_quantization_impl.cu',
'quantization/attention_quantization_impl.cuh',
'quantization/quantize_dequantize_linear.cc',
'tensor/crop.cc',
'tensor/crop.h',
'tensor/crop_impl.cu',
'tensor/crop_impl.h',
'tensor/dynamicslice.cc',
'tensor/image_scaler.cc',
'tensor/image_scaler.h',
'tensor/image_scaler_impl.cu',
'tensor/image_scaler_impl.h',
'conv_transpose_with_dynamic_pads.cc',
'conv_transpose_with_dynamic_pads.h',
'cuda_contrib_kernels.cc',
'cuda_contrib_kernels.h',
'inverse.cc'
]
core_ops_files = [
'atomic/common.cuh',
'controlflow/if.cc',
'controlflow/if.h',
'controlflow/loop.cc',
'controlflow/loop.h',
'controlflow/scan.cc',
'controlflow/scan.h',
'cu_inc/binary_elementwise_impl.cuh',
'cu_inc/common.cuh',
'generator/constant_of_shape.cc',
'generator/constant_of_shape.h',
'generator/range.cc',
'generator/range.h',
'generator/range_impl.cu',
'generator/range_impl.h',
'math/einsum_utils/einsum_auxiliary_ops.cc',
'math/einsum_utils/einsum_auxiliary_ops.h',
'math/einsum_utils/einsum_auxiliary_ops_diagonal.cu',
'math/einsum_utils/einsum_auxiliary_ops_diagonal.h',
'math/binary_elementwise_ops.cc',
'math/binary_elementwise_ops.h',
'math/binary_elementwise_ops_impl.cu',
'math/binary_elementwise_ops_impl.h',
'math/binary_elementwise_ops_impl_functors.cuh',
'math/cumsum.cc',
'math/cumsum.h',
'math/cumsum_impl.cu',
'math/cumsum_impl.h',
'math/einsum.cc',
'math/einsum.h',
'math/gemm.cc',
'math/matmul.cc',
'math/matmul_integer.cc',
'math/matmul_integer.cu',
'math/matmul_integer.cuh',
'math/matmul_integer.h',
'math/softmax.cc',
'math/topk.cc',
'math/topk.h',
'math/topk_impl.cu',
'math/topk_impl.h',
'math/variadic_elementwise_ops.cc',
'math/variadic_elementwise_ops.h',
'math/variadic_elementwise_ops_impl.cu',
'math/variadic_elementwise_ops_impl.h',
'nn/batch_norm.cc',
'nn/batch_norm.h',
'nn/conv.cc',
'nn/conv.h',
'nn/conv_transpose.cc',
'nn/conv_transpose.h',
'nn/instance_norm.cc',
'nn/instance_norm.h',
'nn/instance_norm_impl.cu',
'nn/instance_norm_impl.h',
'nn/lrn.cc',
'nn/lrn.h',
'nn/max_pool_with_index.cu',
'nn/max_pool_with_index.h',
'nn/pool.cc',
'nn/pool.h',
'nn/shrink.cc',
'nn/shrink.h',
'nn/shrink_impl.cu',
'nn/shrink_impl.h',
'object_detection/non_max_suppression.cc',
'object_detection/non_max_suppression.h',
'object_detection/non_max_suppression_impl.cu',
'object_detection/non_max_suppression_impl.h',
'object_detection/roialign.cc',
'object_detection/roialign.h',
'object_detection/roialign_impl.cu',
'object_detection/roialign_impl.h',
'reduction/reduction_functions.cc',
'reduction/reduction_functions.cu',
'reduction/reduction_functions.h',
'reduction/reduction_ops.cc',
'reduction/reduction_ops.h',
'reduction/reduction_utils.cuh',
'rnn/cudnn_rnn_base.cc',
'rnn/cudnn_rnn_base.h',
'rnn/gru.cc',
'rnn/gru.h',
'rnn/lstm.cc',
'rnn/lstm.h',
'rnn/rnn.cc',
'rnn/rnn.h',
'rnn/rnn_impl.cu',
'rnn/rnn_impl.h',
'shared_inc/cuda_call.h',
'shared_inc/fast_divmod.h',
'shared_inc/fpgeneric.h',
'shared_inc/integer_gemm.h',
'tensor/compress.cc',
'tensor/compress.h',
'tensor/compress_impl.cu',
'tensor/compress_impl.h',
'tensor/eye_like.cc',
'tensor/eye_like.h',
'tensor/eye_like_impl.cu',
'tensor/eye_like_impl.h',
'tensor/flatten.cc',
'tensor/flatten.h',
'tensor/gather_elements.cc',
'tensor/gather_elements.h',
'tensor/gather_elements_impl.cu',
'tensor/gather_elements_impl.h',
'tensor/gather_nd_impl.cu',
'tensor/nonzero_impl.cu',
'tensor/nonzero_impl.h',
'tensor/nonzero_op.cc',
'tensor/nonzero_op.h',
'tensor/pad.cc',
'tensor/pad.h',
'tensor/pad_impl.cu',
'tensor/pad_impl.h',
'tensor/quantize_linear.cc',
'tensor/quantize_linear.cu',
'tensor/quantize_linear.cuh',
'tensor/quantize_linear.h',
'tensor/resize.cc',
'tensor/resize.h',
'tensor/resize_impl.cu',
'tensor/resize_impl.h',
'tensor/reverse_sequence.cc',
'tensor/reverse_sequence.h',
'tensor/reverse_sequence_impl.cu',
'tensor/reverse_sequence_impl.h',
'tensor/size.cc',
'tensor/tile.cc',
'tensor/tile.h',
'tensor/tile_impl.cu',
'tensor/tile_impl.h',
'tensor/transpose_impl.cu',
'tensor/transpose_impl.h',
'tensor/transpose.cc',
'tensor/transpose.h',
'tensor/upsample.cc',
'tensor/upsample.h',
'tensor/upsample_impl.cu',
'tensor/upsample_impl.h',
'cuda_allocator.cc',
'cuda_allocator.h',
'cuda_call.cc',
'cuda_common.h',
'cuda_execution_provider.cc',
'cuda_execution_provider.h',
'cuda_fence.cc',
'cuda_fence.h',
'cuda_fwd.h',
'cuda_pch.cc',
'cuda_pch.h',
'cuda_provider_factory.cc',
'cuda_utils.cu',
'cudnn_common.cc',
'cudnn_common.h',
'fpgeneric.cu',
'gpu_data_transfer.cc',
'gpu_data_transfer.h',
'integer_gemm.cc',
'symbols.txt',
]
training_ops_files = [
'activation/activations_grad.cc',
'collective/horovod_kernels.cc',
'collective/horovod_kernels.h',
'collective/nccl_common.cc',
'collective/ready_event.cc',
'collective/ready_event.h',
'communication/common.h',
'communication/nccl_service.cc',
'communication/nccl_service.h',
'communication/recv.cc',
'communication/recv.h',
'communication/send.cc',
'communication/send.h',
'controlflow/record.cc',
'controlflow/record.h',
'controlflow/wait.cc',
'controlflow/wait.h',
'loss/softmax_cross_entropy_loss_impl.cc',
'loss/softmaxcrossentropy_impl.cc',
'math/div_grad.cc',
'math/div_grad.h',
'math/div_grad_impl.cu',
'math/div_grad_impl.h',
'math/isfinite.cc',
'math/isfinite.cuh',
'math/isfinite.h',
'math/scale.cc',
'math/scale.cu',
'math/scale.h',
'math/softmax_grad.cc',
'nn/batch_norm_grad.cc',
'nn/batch_norm_grad.h',
'optimizer/adam.cc',
'optimizer/adam.cu',
'optimizer/lamb.cc',
'reduction/reduction_all.cc',
'reduction/reduction_all.cu',
'reduction/reduction_ops.cc',
'tensor/gather_elements_grad.cc',
'tensor/gather_elements_grad.h',
'tensor/gather_grad.cc',
'tensor/gather_grad_impl.cu',
'tensor/gather_grad_impl.h',
'tensor/gather_nd_grad_impl.cu',
'cuda_training_kernels.cc',
'cuda_training_kernels.h',
]
HIPIFY_PERL = '/opt/rocm/bin/hipify-perl'
FINDCODE = '/opt/rocm/bin/findcode.sh'
def hipify(src_file_path, dst_file_path):
dst_file_path = dst_file_path.replace('cuda', 'rocm')
dir_name = os.path.dirname(dst_file_path)
if not os.path.exists(dir_name):
os.makedirs(dir_name, exist_ok=True)
with open(dst_file_path, 'w') as f:
subprocess.run([HIPIFY_PERL, src_file_path], stdout=f)
with open(dst_file_path) as f:
s = f.read().replace('kCudaExecutionProvider', 'kRocmExecutionProvider')
s = s.replace('CudaAsyncBuffer', 'RocmAsyncBuffer')
s = s.replace('CudaKernel', 'RocmKernel')
s = s.replace('ToCudaType', 'ToHipType')
s = s.replace('CudaT', 'HipT')
s = s.replace('CUDA_LONG', 'HIP_LONG')
s = s.replace('CUDA_RETURN_IF_ERROR', 'HIP_RETURN_IF_ERROR')
s = s.replace('CUDA_KERNEL_ASSERT', 'HIP_KERNEL_ASSERT')
s = s.replace('CUDA_CALL', 'HIP_CALL')
s = s.replace('SliceCuda', 'SliceRocm')
s = s.replace('cuda', 'rocm')
# s = s.replace('Cuda', 'Rocm')
s = s.replace('CUDA', 'ROCM')
s = s.replace('GPU_WARP_SIZE = 32', 'GPU_WARP_SIZE = 64')
s = s.replace('std::exp', 'expf')
s = s.replace('std::log', 'logf')
s = s.replace('#include <cub/device/device_radix_sort.cuh>', '#include <hipcub/hipcub.hpp>')
s = s.replace('#include <cub/iterator/counting_input_iterator.cuh>', '')
s = s.replace('typedef half MappedType', 'typedef __half MappedType')
# CUBLAS -> ROCBLAS
# s = s.replace('CUBLAS', 'HIPBLAS')
# s = s.replace('Cublas', 'Hipblas')
# s = s.replace('cublas', 'hipblas')
# CURAND -> HIPRAND
s = s.replace('CURAND', 'HIPRAND')
s = s.replace('Curand', 'Hiprand')
s = s.replace('curand', 'hiprand')
# NCCL -> RCCL
# s = s.replace('NCCL_CALL', 'RCCL_CALL')
s = s.replace('#include <nccl.h>', '#include <rccl.h>')
# CUDNN -> MIOpen
s = s.replace('CUDNN', 'MIOPEN')
s = s.replace('Cudnn', 'Miopen')
s = s.replace('cudnn', 'miopen')
# hipify seems to have a bug for MIOpen, cudnn.h -> hipDNN.h, cudnn -> hipdnn
s = s.replace('#include <hipDNN.h>', '#include <miopen/miopen.h>')
s = s.replace('hipdnn', 'miopen')
s = s.replace('HIPDNN_STATUS_SUCCESS', 'miopenStatusSuccess')
s = s.replace('HIPDNN', 'MIOPEN')
# CUSPARSE -> HIPSPARSE
s = s.replace('CUSPARSE', 'HIPSPARSE')
# CUFFT -> HIPFFT
s = s.replace('CUFFT', 'HIPFFT')
with open(dst_file_path, 'w') as f:
f.write(s)
def list_files(prefix, path):
all_files = []
curr_path = os.path.join(prefix, path)
for root, dirs, files in os.walk(curr_path):
for file in files:
full_path = os.path.join(root, file)
all_files.append(os.path.relpath(full_path, curr_path))
return all_files
def amd_hipify(config_build_dir):
cuda_contrib_path = os.path.join(contrib_ops_path, 'cuda')
rocm_contrib_path = os.path.join(config_build_dir, 'amdgpu', contrib_ops_path, 'rocm')
contrib_files = list_files(cuda_contrib_path, '')
for file in contrib_files:
if file not in contrib_ops_files:
src_file_path = os.path.join(cuda_contrib_path, file)
dst_file_path = os.path.join(rocm_contrib_path, file)
hipify(src_file_path, dst_file_path)
cuda_core_path = os.path.join(core_ops_path, 'cuda')
rocm_core_path = os.path.join(config_build_dir, 'amdgpu', core_ops_path, 'rocm')
core_files = list_files(cuda_core_path, '')
for file in core_files:
if file not in core_ops_files:
src_file_path = os.path.join(cuda_core_path, file)
dst_file_path = os.path.join(rocm_core_path, file)
hipify(src_file_path, dst_file_path)
cuda_training_path = os.path.join(training_ops_path, 'cuda')
rocm_training_path = os.path.join(config_build_dir, 'amdgpu', training_ops_path, 'rocm')
training_files = list_files(cuda_training_path, '')
for file in training_files:
if file not in training_ops_files:
src_file_path = os.path.join(cuda_training_path, file)
dst_file_path = os.path.join(rocm_training_path, file)
hipify(src_file_path, dst_file_path)
if __name__ == '__main__':
amd_hipify()
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