fix deepspeed version

This commit is contained in:
hiyouga 2024-06-11 16:52:36 +08:00
parent 53b74361d3
commit cca6f35108
1 changed files with 14 additions and 9 deletions

View File

@ -1,5 +1,6 @@
from typing import TYPE_CHECKING
from typing import TYPE_CHECKING, Sequence
import torch
from transformers.integrations import is_deepspeed_zero3_enabled
from transformers.utils.versions import require_version
@ -10,6 +11,13 @@ if TYPE_CHECKING:
from ...hparams import ModelArguments
def _set_z3_leaf_modules(model: "PreTrainedModel", leaf_modules: Sequence["torch.nn.Module"]) -> None:
require_version("deepspeed>=0.13.0", "To fix: pip install deepspeed>=0.13.0")
from deepspeed.utils import set_z3_leaf_modules # type: ignore
set_z3_leaf_modules(model, leaf_modules)
def add_z3_leaf_module(model: "PreTrainedModel") -> None:
r"""
Sets module as a leaf module to skip partitioning in deepspeed zero3.
@ -17,33 +25,30 @@ def add_z3_leaf_module(model: "PreTrainedModel") -> None:
if not is_deepspeed_zero3_enabled():
return
require_version("deepspeed>=0.13.0", "To fix: pip install deepspeed>=0.13.0")
from deepspeed.utils import set_z3_leaf_modules # type: ignore
if getattr(model.config, "model_type", None) == "dbrx":
from transformers.models.dbrx.modeling_dbrx import DbrxFFN
set_z3_leaf_modules(model, [DbrxFFN])
_set_z3_leaf_modules(model, [DbrxFFN])
if getattr(model.config, "model_type", None) == "jamba":
from transformers.models.jamba.modeling_jamba import JambaSparseMoeBlock
set_z3_leaf_modules(model, [JambaSparseMoeBlock])
_set_z3_leaf_modules(model, [JambaSparseMoeBlock])
if getattr(model.config, "model_type", None) == "jetmoe":
from transformers.models.jetmoe.modeling_jetmoe import JetMoeMoA, JetMoeMoE
set_z3_leaf_modules(model, [JetMoeMoA, JetMoeMoE])
_set_z3_leaf_modules(model, [JetMoeMoA, JetMoeMoE])
if getattr(model.config, "model_type", None) == "mixtral":
from transformers.models.mixtral.modeling_mixtral import MixtralSparseMoeBlock
set_z3_leaf_modules(model, [MixtralSparseMoeBlock])
_set_z3_leaf_modules(model, [MixtralSparseMoeBlock])
if getattr(model.config, "model_type", None) == "qwen2moe":
from transformers.models.qwen2_moe.modeling_qwen2_moe import Qwen2MoeSparseMoeBlock
set_z3_leaf_modules(model, [Qwen2MoeSparseMoeBlock])
_set_z3_leaf_modules(model, [Qwen2MoeSparseMoeBlock])
def configure_moe(config: "PretrainedConfig", model_args: "ModelArguments", is_trainable: bool) -> None: