Alignment-Lab-AI
commited on
Commit
•
d952c8a
1
Parent(s):
d721e7b
Update caption.py
Browse files- caption.py +20 -16
caption.py
CHANGED
@@ -26,6 +26,7 @@ def process_file(llm, filepath, sampling_params):
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prev_eps = 0
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batch_texts = []
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df = pd.DataFrame()
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if filepath.endswith('.parquet'):
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print("Reading from a parquet file...")
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@@ -73,27 +74,30 @@ def process_file(llm, filepath, sampling_params):
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executor.submit(df.to_parquet, filepath)
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i += BATCH_SIZE
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# Delete the original parquet file if it is empty
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if df.empty:
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os.remove(filepath)
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print(f"Deleted the original file: {filepath}")
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# Initialize the HuggingFace API
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api = HfApi()
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# Upload the processed file to the repository
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try:
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api.upload_file(
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path_or_fileobj=new_filepath,
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path_in_repo=new_filepath,
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repo_id="AlignmentLab-AI/caption_creation_0.8",
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repo_type="dataset",
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)
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print(f"Uploaded {new_filepath} to AlignmentLab-AI/caption_creation_0.8 repository.")
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except Exception as e:
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print(f"Error uploading file: {e}")
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def main():
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folder_name = 'captionate'
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sampling_params = SamplingParams(temperature=0.7, top_p=0.95, max_tokens=100)
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@@ -108,4 +112,4 @@ def main():
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if __name__ == "__main__":
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main()
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-
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prev_eps = 0
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batch_texts = []
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df = pd.DataFrame()
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batch_counter = 0 # Counter to keep track of batches processed
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if filepath.endswith('.parquet'):
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print("Reading from a parquet file...")
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executor.submit(df.to_parquet, filepath)
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i += BATCH_SIZE
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batch_counter += 1
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# Push to hub every 10 batches
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if batch_counter % 10 == 0:
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# Initialize the HuggingFace API
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api = HfApi()
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# Upload the processed file to the repository
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try:
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api.upload_file(
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path_or_fileobj=new_filepath,
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path_in_repo=new_filepath,
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repo_id="AlignmentLab-AI/caption_creation_0.8",
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repo_type="dataset",
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)
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print(f"Uploaded {new_filepath} to AlignmentLab-AI/caption_creation_0.8 repository.")
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except Exception as e:
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print(f"Error uploading file: {e}")
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# Delete the original parquet file if it is empty
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if df.empty:
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os.remove(filepath)
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print(f"Deleted the original file: {filepath}")
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def main():
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folder_name = 'captionate'
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sampling_params = SamplingParams(temperature=0.7, top_p=0.95, max_tokens=100)
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if __name__ == "__main__":
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main()
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+
`
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