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Remove pt_to_tf (#35672)

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* rm command

* remove exception
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Joao Gante 2025-01-16 17:03:37 +00:00 committed by GitHub
parent 80dbbd103c
commit aaa969e97d
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3 changed files with 0 additions and 140 deletions
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137
src/transformers/commands/pt_to_tf.py
View file

@ -1,137 +0,0 @@
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
MAX_ERROR = 5e-5 # larger error tolerance than in our internal tests, to avoid flaky user-facing errors
def convert_command_factory(args: Namespace):
"""
Factory function used to convert a model PyTorch checkpoint in a TensorFlow 2 checkpoint.
Returns: ServeCommand
"""
return PTtoTFCommand(
args.model_name,
args.local_dir,
args.max_error,
args.new_weights,
args.no_pr,
args.push,
args.extra_commit_description,
args.override_model_class,
)
class PTtoTFCommand(BaseTransformersCLICommand):
@staticmethod
def register_subcommand(parser: ArgumentParser):
"""
Register this command to argparse so it's available for the transformer-cli
Args:
parser: Root parser to register command-specific arguments
"""
train_parser = parser.add_parser(
"pt-to-tf",
help=(
"CLI tool to run convert a transformers model from a PyTorch checkpoint to a TensorFlow checkpoint."
" Can also be used to validate existing weights without opening PRs, with --no-pr."
),
)
train_parser.add_argument(
"--model-name",
type=str,
required=True,
help="The model name, including owner/organization, as seen on the hub.",
)
train_parser.add_argument(
"--local-dir",
type=str,
default="",
help="Optional local directory of the model repository. Defaults to /tmp/{model_name}",
)
train_parser.add_argument(
"--max-error",
type=float,
default=MAX_ERROR,
help=(
f"Maximum error tolerance. Defaults to {MAX_ERROR}. This flag should be avoided, use at your own risk."
),
)
train_parser.add_argument(
"--new-weights",
action="store_true",
help="Optional flag to create new TensorFlow weights, even if they already exist.",
)
train_parser.add_argument(
"--no-pr", action="store_true", help="Optional flag to NOT open a PR with converted weights."
)
train_parser.add_argument(
"--push",
action="store_true",
help="Optional flag to push the weights directly to `main` (requires permissions)",
)
train_parser.add_argument(
"--extra-commit-description",
type=str,
default="",
help="Optional additional commit description to use when opening a PR (e.g. to tag the owner).",
)
train_parser.add_argument(
"--override-model-class",
type=str,
default=None,
help="If you think you know better than the auto-detector, you can specify the model class here. "
"Can be either an AutoModel class or a specific model class like BertForSequenceClassification.",
)
train_parser.set_defaults(func=convert_command_factory)
def __init__(
self,
model_name: str,
local_dir: str,
max_error: float,
new_weights: bool,
no_pr: bool,
push: bool,
extra_commit_description: str,
override_model_class: str,
*args,
):
self._logger = logging.get_logger("transformers-cli/pt_to_tf")
self._model_name = model_name
self._local_dir = local_dir if local_dir else os.path.join("/tmp", model_name)
self._max_error = max_error
self._new_weights = new_weights
self._no_pr = no_pr
self._push = push
self._extra_commit_description = extra_commit_description
self._override_model_class = override_model_class
def run(self):
# TODO (joao): delete file in v4.47
raise NotImplementedError(
"\n\nConverting PyTorch weights to TensorFlow weights was removed in v4.43. "
"Instead, we recommend that you convert PyTorch weights to Safetensors, an improved "
"format that can be loaded by any framework, including TensorFlow. For more information, "
"please see the Safetensors conversion guide: "
"https://huggingface.co/docs/safetensors/en/convert-weights\n\n"
)

2
src/transformers/commands/transformers_cli.py
View file

@ -20,7 +20,6 @@ from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .run import RunCommand
from .serving import ServeCommand
from .user import UserCommands
@ -39,7 +38,6 @@ def main():
UserCommands.register_subcommand(commands_parser)
AddNewModelLikeCommand.register_subcommand(commands_parser)
LfsCommands.register_subcommand(commands_parser)
PTtoTFCommand.register_subcommand(commands_parser)
# Let's go
args = parser.parse_args()

1
utils/not_doctested.txt
View file

@ -351,7 +351,6 @@ src/transformers/commands/convert.py
src/transformers/commands/download.py
src/transformers/commands/env.py
src/transformers/commands/lfs.py
src/transformers/commands/pt_to_tf.py
src/transformers/commands/run.py
src/transformers/commands/serving.py
src/transformers/commands/train.py