123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354 |
- from .builder import CUDAOpBuilder, installed_cuda_version
- class InferenceBuilder(CUDAOpBuilder):
- BUILD_VAR = "DS_BUILD_TRANSFORMER_INFERENCE"
- NAME = "transformer_inference"
- def __init__(self, name=None):
- name = self.NAME if name is None else name
- super().__init__(name=name)
- def absolute_name(self):
- return f'deepspeed.ops.transformer.inference.{self.NAME}_op'
- def is_compatible(self, verbose=True):
- try:
- import torch
- except ImportError:
- self.warning(
- "Please install torch if trying to pre-compile inference kernels")
- return False
- cuda_okay = True
- if not self.is_rocm_pytorch() and torch.cuda.is_available():
- sys_cuda_major, _ = installed_cuda_version()
- torch_cuda_major = int(torch.version.cuda.split('.')[0])
- cuda_capability = torch.cuda.get_device_properties(0).major
- if cuda_capability >= 8:
- if torch_cuda_major < 11 or sys_cuda_major < 11:
- self.warning(
- "On Ampere and higher architectures please use CUDA 11+")
- cuda_okay = False
- return super().is_compatible(verbose) and cuda_okay
- def sources(self):
- return [
- 'csrc/transformer/inference/csrc/pt_binding.cpp',
- 'csrc/transformer/inference/csrc/gelu.cu',
- 'csrc/transformer/inference/csrc/relu.cu',
- 'csrc/transformer/inference/csrc/normalize.cu',
- 'csrc/transformer/inference/csrc/softmax.cu',
- 'csrc/transformer/inference/csrc/dequantize.cu',
- 'csrc/transformer/inference/csrc/apply_rotary_pos_emb.cu',
- 'csrc/transformer/inference/csrc/transform.cu',
- ]
- def extra_ldflags(self):
- if not self.is_rocm_pytorch():
- return ['-lcurand']
- else:
- return []
- def include_paths(self):
- return ['csrc/transformer/inference/includes']
|