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Set the default value of op_builder/xxx.py/is_compatible()/verbose to False for quite warning. Add verbose judgement before op_builder/xxx.py/is_compatible()/self.warning(...). Otherwise the verbose arg will not work. --------- Co-authored-by: Logan Adams <114770087+loadams@users.noreply.github.com>
96 lines
3.3 KiB
Python
96 lines
3.3 KiB
Python
# Copyright (c) Microsoft Corporation.
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# SPDX-License-Identifier: Apache-2.0
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# DeepSpeed Team
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import os
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from .builder import CUDAOpBuilder, installed_cuda_version
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class InferenceCutlassBuilder(CUDAOpBuilder):
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BUILD_VAR = "DS_BUILD_CUTLASS_OPS"
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NAME = "cutlass_ops"
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def __init__(self, name=None):
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name = self.NAME if name is None else name
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super().__init__(name=name)
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def absolute_name(self):
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return f'deepspeed.inference.v2.kernels.cutlass_ops.{self.NAME}'
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def is_compatible(self, verbose=False):
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try:
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import torch
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except ImportError:
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if verbose:
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self.warning("Please install torch if trying to pre-compile inference kernels")
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return False
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cuda_okay = True
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if not self.is_rocm_pytorch() and torch.cuda.is_available(): #ignore-cuda
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sys_cuda_major, _ = installed_cuda_version()
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torch_cuda_major = int(torch.version.cuda.split('.')[0])
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cuda_capability = torch.cuda.get_device_properties(0).major #ignore-cuda
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if cuda_capability < 6:
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if verbose:
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self.warning("NVIDIA Inference is only supported on Pascal and newer architectures")
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cuda_okay = False
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if cuda_capability >= 8:
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if torch_cuda_major < 11 or sys_cuda_major < 11:
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if verbose:
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self.warning("On Ampere and higher architectures please use CUDA 11+")
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cuda_okay = False
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return super().is_compatible(verbose) and cuda_okay
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def filter_ccs(self, ccs):
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ccs_retained = []
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ccs_pruned = []
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for cc in ccs:
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if int(cc[0]) >= 8:
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# Only support Ampere and newer
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ccs_retained.append(cc)
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else:
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ccs_pruned.append(cc)
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if len(ccs_pruned) > 0:
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self.warning(f"Filtered compute capabilities {ccs_pruned}")
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return ccs_retained
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def get_prefix(self):
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ds_path = self.deepspeed_src_path("deepspeed")
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return "deepspeed" if os.path.isdir(ds_path) else ".."
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def sources(self):
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sources = [
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"inference/v2/kernels/cutlass_ops/cutlass_ops.cpp",
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"inference/v2/kernels/cutlass_ops/mixed_gemm/mixed_gemm.cu",
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"inference/v2/kernels/cutlass_ops/moe_gemm/moe_gemm.cu",
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]
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prefix = self.get_prefix()
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sources = [os.path.join(prefix, src) for src in sources]
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return sources
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def extra_ldflags(self):
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import dskernels
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lib_path = dskernels.library_path()
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prefix = self.get_prefix()
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lib_path = os.path.join(prefix, lib_path)
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lib_path = self.deepspeed_src_path(lib_path)
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args = [f'-L{lib_path}', '-ldeepspeedft']
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if self.jit_load:
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args.append(f'-Wl,-rpath,{lib_path}')
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return args
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def include_paths(self):
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sources = [
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'inference/v2/kernels/includes',
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'inference/v2/kernels/cutlass_ops/mixed_gemm',
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'inference/v2/kernels/cutlass_ops/moe_gemm',
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'inference/v2/kernels/cutlass_ops/shared_resources/',
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]
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prefix = self.get_prefix()
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sources = [os.path.join(prefix, src) for src in sources]
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return sources
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