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Traceback (most recent call last):
File "pythonProject/convert.py", line 1, in <module>
from torchtune.utils import FullModelHFCheckpointer
File "python3.8/site-packages/torchtune/__init__.py", line 9, in <module>
from torchtune import datasets, models, modules, utils
File "python3.8/site-packages/torchtune/datasets/__init__.py", line 7, in <module>
from torchtune.datasets._alpaca import alpaca_cleaned_dataset, alpaca_dataset
File "python3.8/site-packages/torchtune/datasets/_alpaca.py", line 10, in <module>
from torchtune.datasets._instruct import InstructDataset
File "python3.8/site-packages/torchtune/datasets/_instruct.py", line 12, in <module>
from torchtune.config._utils import _get_instruct_template
File "python3.8/site-packages/torchtune/config/__init__.py", line 7, in <module>
from ._instantiate import instantiate
File "python3.8/site-packages/torchtune/config/_instantiate.py", line 12, in <module>
from torchtune.config._utils import _get_component_from_path, _has_component
File "python3.8/site-packages/torchtune/config/_utils.py", line 16, in <module>
from torchtune.utils import get_logger, get_world_size_and_rank
File "python3.8/site-packages/torchtune/utils/__init__.py", line 7, in <module>
from ._checkpointing import ( # noqa
File "python3.8/site-packages/torchtune/utils/_checkpointing/__init__.py", line 7, in <module>
from ._checkpointer import ( # noqa
File "python3.8/site-packages/torchtune/utils/_checkpointing/_checkpointer.py", line 17, in <module>
from torchtune.models import convert_weights
File "python3.8/site-packages/torchtune/models/__init__.py", line 7, in <module>
from torchtune.models import convert_weights, gemma, llama2, mistral # noqa
File "python3.8/site-packages/torchtune/models/gemma/__init__.py", line 7, in <module>
from ._component_builders import gemma # noqa
File "python3.8/site-packages/torchtune/models/gemma/_component_builders.py", line 9, in <module>
from torchtune.modules import (
File "python3.8/site-packages/torchtune/modules/__init__.py", line 8, in <module>
from .common_utils import reparametrize_as_dtype_state_dict_post_hook
File "python3.8/site-packages/torchtune/modules/common_utils.py", line 12, in <module>
from torchao.dtypes.nf4tensor import NF4Tensor
File "python3.8/site-packages/torchao/__init__.py", line 2, in <module>
from .quantization.quant_api import apply_dynamic_quant
File "python3.8/site-packages/torchao/quantization/__init__.py", line 7, in <module>
from .smoothquant import * # noqa: F403
File "python3.8/site-packages/torchao/quantization/smoothquant.py", line 18, in <module>
import torchao.quantization.quant_api as quant_api
File "python3.8/site-packages/torchao/quantization/quant_api.py", line 22, in <module>
from .dynamic_quant import DynamicallyPerAxisQuantizedLinear
File "python3.8/site-packages/torchao/quantization/dynamic_quant.py", line 10, in <module>
from .quant_primitives import (
File "python3.8/site-packages/torchao/quantization/quant_primitives.py", line 9, in <module>
from torch._higher_order_ops.out_dtype import out_dtype
ModuleNotFoundError: No module named 'torch._higher_order_ops'
The text was updated successfully, but these errors were encountered:
Thanks for adding all the details to repro. I was not able to reproduce this error. Can you update your torch version to the latest stable? Also, what is your torchao version? I did not have any issues with torch==2.3.0, torchao==0.1, torchtune==0.1.1
System Info
Reproduction
ERROR INFO
The text was updated successfully, but these errors were encountered: