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87 lines
2.8 KiB
87 lines
2.8 KiB
from typing import Optional
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class TensorParallelEnv(object):
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_instance = None
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def __new__(cls, *args, **kwargs):
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if cls._instance is None:
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cls._instance = object.__new__(cls, *args, **kwargs)
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return cls._instance
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def __init__(self, *args, **kwargs):
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self.load(*args, **kwargs)
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def load(self,
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mode: Optional[str] = None,
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vocab_parallel: bool = False,
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parallel_input_1d: bool = False,
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summa_dim: int = None,
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tesseract_dim: int = None,
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tesseract_dep: int = None,
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depth_3d: int = None,
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input_group_3d=None,
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weight_group_3d=None,
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output_group_3d=None):
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self.mode = mode
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self.vocab_parallel = vocab_parallel
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self.parallel_input_1d = parallel_input_1d
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self.summa_dim = summa_dim
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self.tesseract_dim = tesseract_dim
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self.tesseract_dep = tesseract_dep
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self.depth_3d = depth_3d
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self.input_group_3d = input_group_3d
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self.weight_group_3d = weight_group_3d
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self.output_group_3d = output_group_3d
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def save(self):
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return dict(mode=self.mode,
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vocab_parallel=self.vocab_parallel,
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parallel_input_1d=self.parallel_input_1d,
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summa_dim=self.summa_dim,
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tesseract_dim=self.tesseract_dim,
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tesseract_dep=self.tesseract_dep,
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depth_3d=self.depth_3d,
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input_group_3d=self.input_group_3d,
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weight_group_3d=self.weight_group_3d,
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output_group_3d=self.output_group_3d)
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class MoeEnv:
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"""Moe enviroment variables.
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"""
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def __init__(self):
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self.data_parallel_size = None
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self.model_parallel_size = None
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self.aux_loss = None
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def setup(self, moe_model_size):
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from .core import global_context as gpc
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if gpc.tensor_parallel_size > 1 or gpc.pipeline_parallel_size > 1:
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raise NotImplementedError("Moe is not compatible with tensor or pipeline parallel")
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assert gpc.data_parallel_size % moe_model_size == 0, \
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"The size of data parallel needs to be divided by moe model parallel size"
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self.data_parallel_size = gpc.data_parallel_size // moe_model_size
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self.model_parallel_size = moe_model_size
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def is_initialized(self):
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return self.model_parallel_size is not None
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def reset_loss(self):
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self.aux_loss = 0
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def add_loss(self, loss):
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self.aux_loss += loss
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def get_loss(self):
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return self.aux_loss
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tensor_parallel_env = TensorParallelEnv()
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moe_env = MoeEnv()
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