mirror of https://github.com/InternLM/InternLM
fix lint
parent
1bc3c33b75
commit
476a24bd9b
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@ -1,6 +1,6 @@
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from .parallel_context import (
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IS_TENSOR_PARALLEL,
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IS_SEQUENCE_PARALLEL,
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IS_TENSOR_PARALLEL,
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Config,
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ParallelContext,
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global_context,
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@ -9,7 +9,7 @@ from flash_attn.modules.embedding import ParallelGPT2Embeddings
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from flash_attn.modules.mlp import ParallelFusedMLP
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from torch import nn
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from internlm.core.context import IS_TENSOR_PARALLEL, IS_SEQUENCE_PARALLEL, ParallelMode
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from internlm.core.context import IS_SEQUENCE_PARALLEL, IS_TENSOR_PARALLEL, ParallelMode
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from internlm.core.context.parallel_context import global_context as gpc
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from internlm.initialize.initialize_tensor import normal_, scaled_init_method_normal
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from internlm.model.embedding import Embedding1D
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@ -365,7 +365,7 @@ class PackedFlashInternLm1D(nn.Module):
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for param in self.norm.parameters():
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if gpc.config.parallel.sequence_parallel is True:
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setattr(param, IS_SEQUENCE_PARALLEL, True)
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self.parallel_output = parallel_output
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def forward(self, hidden_states=None, cu_seqlens=None, input_ids=None, indexes=None, inference_params=None):
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@ -8,7 +8,7 @@ import torch
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import torch.distributed as dist
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from torch.optim import Optimizer
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from internlm.core.context import Config, ParallelMode, IS_SEQUENCE_PARALLEL
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from internlm.core.context import IS_SEQUENCE_PARALLEL, Config, ParallelMode
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from internlm.core.context import global_context as gpc
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from internlm.monitor import send_alert_message
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from internlm.solver.optimizer.store import (
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@ -296,7 +296,7 @@ class HybridZeroOptimizer(BaseOptimizer):
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param=param,
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reduce_rank=reduce_rank,
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)
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def reduction_sp_func():
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handle = reduce_tensor(
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param.grad,
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@ -312,18 +312,19 @@ class HybridZeroOptimizer(BaseOptimizer):
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def reduce_grad_hook(*args): # pylint: disable=W0613
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if self.skip_grad_reduce is False:
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reduction_func()
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# define hook for sequence_parallel
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def reduce_grad_hook_sp(*args):
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def reduce_grad_hook_sp(*args): # pylint: disable=W0613
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if self.skip_grad_reduce is False:
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reduction_sp_func()
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# if sequence_parallel is True, the grad of norm should be all-reduce across the tp process group
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# if sequence_parallel is True,
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# the grad of norm should be all-reduce across the tp process group
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if gpc.config.parallel.sequence_parallel is True:
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if hasattr(param, IS_SEQUENCE_PARALLEL) and getattr(param, IS_SEQUENCE_PARALLEL) is True:
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accum_grad_obj_sp = get_grad_accumulate_object(param)
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accum_grad_obj_sp.register_hook(reduce_grad_hook_sp)
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accum_grad_obj.register_hook(reduce_grad_hook)
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_define_and_attach(param, reduce_rank)
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