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Fix model downloading in bento (#3803)
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Summary:
Pull Request resolved: #3803

The model checkpoint path can not be created for Squim models. Use the latest download_asset method to fix it.

Reviewed By: moto-meta

Differential Revision: D59061348
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nateanl authored and facebook-github-bot committed Jul 1, 2024
1 parent 7f6209b commit 0875dce
Showing 1 changed file with 10 additions and 30 deletions.
40 changes: 10 additions & 30 deletions src/torchaudio/pipelines/_squim_pipeline.py
Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
from dataclasses import dataclass

from torchaudio._internal import load_state_dict_from_url
import torch
import torchaudio

from torchaudio.models import squim_objective_base, squim_subjective_base, SquimObjective, SquimSubjective

Expand Down Expand Up @@ -42,26 +43,16 @@ class SquimObjectiveBundle:
_path: str
_sample_rate: float

def _get_state_dict(self, dl_kwargs):
url = f"https://download.pytorch.org/torchaudio/models/{self._path}"
dl_kwargs = {} if dl_kwargs is None else dl_kwargs
state_dict = load_state_dict_from_url(url, **dl_kwargs)
return state_dict

def get_model(self, *, dl_kwargs=None) -> SquimObjective:
def get_model(self) -> SquimObjective:
"""Construct the SquimObjective model, and load the pretrained weight.
The weight file is downloaded from the internet and cached with
:func:`torch.hub.load_state_dict_from_url`
Args:
dl_kwargs (dictionary of keyword arguments): Passed to :func:`torch.hub.load_state_dict_from_url`.
Returns:
Variation of :py:class:`~torchaudio.models.SquimObjective`.
"""
model = squim_objective_base()
model.load_state_dict(self._get_state_dict(dl_kwargs))
path = torchaudio.utils.download_asset(f"models/{self._path}")
state_dict = torch.load(path, weights_only=True)
model.load_state_dict(state_dict)
model.eval()
return model

Expand Down Expand Up @@ -128,26 +119,15 @@ class SquimSubjectiveBundle:
_path: str
_sample_rate: float

def _get_state_dict(self, dl_kwargs):
url = f"https://download.pytorch.org/torchaudio/models/{self._path}"
dl_kwargs = {} if dl_kwargs is None else dl_kwargs
state_dict = load_state_dict_from_url(url, **dl_kwargs)
return state_dict

def get_model(self, *, dl_kwargs=None) -> SquimSubjective:
def get_model(self) -> SquimSubjective:
"""Construct the SquimSubjective model, and load the pretrained weight.
The weight file is downloaded from the internet and cached with
:func:`torch.hub.load_state_dict_from_url`
Args:
dl_kwargs (dictionary of keyword arguments): Passed to :func:`torch.hub.load_state_dict_from_url`.
Returns:
Variation of :py:class:`~torchaudio.models.SquimObjective`.
"""
model = squim_subjective_base()
model.load_state_dict(self._get_state_dict(dl_kwargs))
path = torchaudio.utils.download_asset(f"models/{self._path}")
state_dict = torch.load(path, weights_only=True)
model.load_state_dict(state_dict)
model.eval()
return model

Expand Down

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