Spaces:
Running
Running
Jesse Karmani
commited on
Commit
·
2661eab
1
Parent(s):
a0c5750
Test some default inputs and outputs
Browse files
app.py
CHANGED
@@ -68,13 +68,9 @@ def get_dataloader(
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def main(
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sentences_path: Optional[str],
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sentences_dir: Optional[str],
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files_extension: str,
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output_path: str,
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source_lang: Optional[str],
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target_lang: Optional[str],
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starting_batch_size: int,
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model_name: str = "facebook/m2m100_1.2B",
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lora_weights_name_or_path: str = None,
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force_auto_device_map: bool = False,
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@@ -93,6 +89,8 @@ def main(
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trust_remote_code: bool = False,
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):
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accelerator = Accelerator()
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if force_auto_device_map and starting_batch_size >= 64:
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print(
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@@ -102,16 +100,6 @@ def main(
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f"inference. You should consider using a smaller batch size, i.e '--starting_batch_size 8'"
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)
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if sentences_path is None and sentences_dir is None:
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raise ValueError(
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"You must specify either --sentences_path or --sentences_dir. Use --help for more details."
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)
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if sentences_path is not None and sentences_dir is not None:
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raise ValueError(
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"You must specify either --sentences_path or --sentences_dir, not both. Use --help for more details."
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)
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if precision is None:
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quantization = None
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dtype = None
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@@ -346,20 +334,9 @@ def main(
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os.makedirs(os.path.abspath(os.path.dirname(output_path)), exist_ok=True)
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inference(sentences_path=sentences_path, output_path=output_path)
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if sentences_dir is not None:
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print(
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f"Translating all files in {sentences_dir}, with extension {files_extension}"
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)
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os.makedirs(os.path.abspath(output_path), exist_ok=True)
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for filename in glob.glob(
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os.path.join(
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sentences_dir, f"*.{files_extension}" if files_extension else "*"
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)
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):
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output_filename = os.path.join(output_path, os.path.basename(filename))
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inference(sentences_path=filename, output_path=output_filename)
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print(f"Translation done.\n")
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# if __name__ == "__main__":
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@@ -560,5 +537,5 @@ def main(
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# trust_remote_code=args.trust_remote_code,
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# )
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demo = gradio.Interface(fn=main, inputs="textbox", outputs="textbox")
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demo.launch(share=True)
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def main(
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source_lang: Optional[str],
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target_lang: Optional[str],
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starting_batch_size: int = 8,
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model_name: str = "facebook/m2m100_1.2B",
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lora_weights_name_or_path: str = None,
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force_auto_device_map: bool = False,
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trust_remote_code: bool = False,
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):
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accelerator = Accelerator()
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sentences_path = "sample_text/en.txt"
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output_path = "sample_text/en2es.translation.m2m100_12B.txt"
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if force_auto_device_map and starting_batch_size >= 64:
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print(
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f"inference. You should consider using a smaller batch size, i.e '--starting_batch_size 8'"
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)
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if precision is None:
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quantization = None
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dtype = None
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os.makedirs(os.path.abspath(os.path.dirname(output_path)), exist_ok=True)
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inference(sentences_path=sentences_path, output_path=output_path)
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print(f"Translation done.\n")
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with open(output_path, "r", encoding="utf-8") as f:
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return f.read()
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# if __name__ == "__main__":
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# trust_remote_code=args.trust_remote_code,
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# )
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demo = gradio.Interface(fn=main, inputs=["textbox", "textbox"], outputs="textbox")
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demo.launch(share=True)
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