mirror of
https://github.com/hanzo-ml/trainer.git
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Tariq HasanandGitHub
9183dfd24f
* chore(scripts): add copyright boilerplate verification system Signed-off-by: tariq-hasan <[email protected]> * chore(ci): add boilerplate verification to CI pipeline Signed-off-by: tariq-hasan <[email protected]> * chore: regenerate files with year-less copyright headers Signed-off-by: tariq-hasan <[email protected]> * refactor(boilerplate): simplify verification logic Signed-off-by: tariq-hasan <[email protected]> * chore(boilerplate): add missing copyright headers Signed-off-by: tariq-hasan <[email protected]> * ci(boilerplate): move verifier to code-quality workflow and run unit tests Signed-off-by: tariq-hasan <[email protected]> * feat(boilerplate): accept license headers with any year and remove year validation logic Signed-off-by: tariq-hasan <[email protected]> * feat(boilerplate): add copyright headers to generated Python API Signed-off-by: tariq-hasan <[email protected]> * refactor(boilerplate): use block-comment header for generated Go files Signed-off-by: tariq-hasan <[email protected]> * feat(boilerplate): verify copyright headers in Rust files Signed-off-by: tariq-hasan <[email protected]> --------- Signed-off-by: tariq-hasan <[email protected]>
58 lines
2.1 KiB
Python
58 lines
2.1 KiB
Python
# Copyright The Kubeflow Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import logging
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from urllib.parse import urlparse
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import huggingface_hub
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import pkg.initializers.types.types as types
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import pkg.initializers.utils.utils as utils
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logging.basicConfig(
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format="%(asctime)s %(levelname)-8s [%(filename)s:%(lineno)d] %(message)s",
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datefmt="%Y-%m-%dT%H:%M:%SZ",
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level=logging.INFO,
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)
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class HuggingFace(utils.ModelProvider):
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def load_config(self):
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config_dict = utils.get_config_from_env(types.HuggingFaceModelInitializer)
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self.config = types.HuggingFaceModelInitializer(**config_dict)
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def download_model(self):
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storage_uri_parsed = urlparse(self.config.storage_uri)
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model_uri = storage_uri_parsed.netloc + storage_uri_parsed.path
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logging.info(f"Downloading model: {model_uri}")
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logging.info("-" * 40)
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if self.config.access_token:
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huggingface_hub.login(self.config.access_token)
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# TODO (andreyvelich): We should consider to follow vLLM approach with allow patterns.
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# Ref: https://github.com/kubeflow/trainer/pull/2303#discussion_r1815913663
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# TODO (andreyvelich): We should update patterns for Mistral model
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# Ref: https://github.com/kubeflow/trainer/pull/2303#discussion_r1815914270
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huggingface_hub.snapshot_download(
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repo_id=model_uri,
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local_dir=utils.MODEL_PATH,
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allow_patterns=["*.json", "*.safetensors", "*.model", "*.txt"],
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ignore_patterns=self.config.ignore_patterns,
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)
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logging.info("Model has been downloaded")
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