wehub-resource-sync
100 lines
3.9 KiB
Python
Executable File
100 lines
3.9 KiB
Python
Executable File
# 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 InferenceCoreBuilder(CUDAOpBuilder):
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BUILD_VAR = "DS_BUILD_INFERENCE_CORE_OPS"
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NAME = "inference_core_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{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 os.environ.get("DS_IGNORE_CUDA_DETECTION"):
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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 = self.cuda_capability_major()
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if cuda_capability is not None and 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 is not None and 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 [cc.split('.') for cc in ccs]:
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if int(cc[0]) >= 6:
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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/core_ops/core_ops.cpp",
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"inference/v2/kernels/core_ops/bias_activations/bias_activation.cpp",
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"inference/v2/kernels/core_ops/bias_activations/bias_activation_cuda.cu",
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"inference/v2/kernels/core_ops/cuda_layer_norm/layer_norm.cpp",
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"inference/v2/kernels/core_ops/cuda_layer_norm/layer_norm_cuda.cu",
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"inference/v2/kernels/core_ops/cuda_rms_norm/rms_norm.cpp",
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"inference/v2/kernels/core_ops/cuda_rms_norm/rms_norm_cuda.cu",
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"inference/v2/kernels/core_ops/gated_activations/gated_activation_kernels.cpp",
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"inference/v2/kernels/core_ops/gated_activations/gated_activation_kernels_cuda.cu",
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"inference/v2/kernels/core_ops/cuda_linear/linear_kernels.cpp",
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"inference/v2/kernels/core_ops/cuda_linear/linear_kernels_cuda.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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return []
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def include_paths(self):
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sources = [
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'inference/v2/kernels/core_ops/bias_activations',
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'inference/v2/kernels/core_ops/blas_kernels',
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'inference/v2/kernels/core_ops/cuda_layer_norm',
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'inference/v2/kernels/core_ops/cuda_rms_norm',
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'inference/v2/kernels/core_ops/gated_activations',
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'inference/v2/kernels/core_ops/cuda_linear',
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'inference/v2/kernels/includes',
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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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