sanchit-gandhi HF staff commited on
Commit
fe4f066
1 Parent(s): a3f5584

quick fixes

Browse files
Files changed (1) hide show
  1. app.py +2 -9
app.py CHANGED
@@ -3,7 +3,6 @@ import math
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  import os
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  import tempfile
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  import time
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- from multiprocessing import Pool
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  import gradio as gr
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  import jax.numpy as jnp
@@ -78,7 +77,6 @@ if __name__ == "__main__":
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  chunk_len = round(CHUNK_LENGTH_S * pipeline.feature_extractor.sampling_rate)
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  stride_left = stride_right = round(stride_length_s * pipeline.feature_extractor.sampling_rate)
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  step = chunk_len - stride_left - stride_right
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- pool = Pool(NUM_PROC)
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  # do a pre-compile step so that the first user to use the demo isn't hit with a long transcription time
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  logger.info("compiling forward call...")
@@ -102,11 +100,6 @@ if __name__ == "__main__":
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  ) # Gradio progress bar not compatible with generator, see https://github.com/gradio-app/gradio/issues/3841
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  dataloader = pipeline.preprocess_batch(inputs, chunk_length_s=CHUNK_LENGTH_S, batch_size=BATCH_SIZE)
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- progress(0, desc="Pre-processing audio file...")
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- logger.info("pre-processing audio file...")
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- dataloader = pool.map(identity, dataloader)
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- logger.info("done post-processing")
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-
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  model_outputs = []
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  start_time = time.time()
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  logger.info("transcribing...")
@@ -207,7 +200,7 @@ if __name__ == "__main__":
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  microphone_chunked = gr.Interface(
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  fn=transcribe_chunked_audio,
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  inputs=[
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- gr.Audio(source="microphone", type="filepath"),
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  gr.Radio(["transcribe", "translate"], label="Task", value="transcribe"),
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  gr.Checkbox(value=False, label="Return timestamps"),
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  ],
@@ -224,7 +217,7 @@ if __name__ == "__main__":
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  audio_chunked = gr.Interface(
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  fn=transcribe_chunked_audio,
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  inputs=[
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- gr.Audio(source="upload", label="Audio file", type="filepath"),
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  gr.Radio(["transcribe", "translate"], label="Task", value="transcribe"),
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  gr.Checkbox(value=False, label="Return timestamps"),
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  ],
 
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  import os
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  import tempfile
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  import time
 
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  import gradio as gr
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  import jax.numpy as jnp
 
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  chunk_len = round(CHUNK_LENGTH_S * pipeline.feature_extractor.sampling_rate)
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  stride_left = stride_right = round(stride_length_s * pipeline.feature_extractor.sampling_rate)
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  step = chunk_len - stride_left - stride_right
 
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  # do a pre-compile step so that the first user to use the demo isn't hit with a long transcription time
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  logger.info("compiling forward call...")
 
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  ) # Gradio progress bar not compatible with generator, see https://github.com/gradio-app/gradio/issues/3841
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  dataloader = pipeline.preprocess_batch(inputs, chunk_length_s=CHUNK_LENGTH_S, batch_size=BATCH_SIZE)
 
 
 
 
 
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  model_outputs = []
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  start_time = time.time()
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  logger.info("transcribing...")
 
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  microphone_chunked = gr.Interface(
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  fn=transcribe_chunked_audio,
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  inputs=[
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+ gr.Audio(sources=["microphone"], type="filepath"),
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  gr.Radio(["transcribe", "translate"], label="Task", value="transcribe"),
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  gr.Checkbox(value=False, label="Return timestamps"),
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  ],
 
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  audio_chunked = gr.Interface(
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  fn=transcribe_chunked_audio,
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  inputs=[
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+ gr.Audio(sources=["upload"], label="Audio file", type="filepath"),
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  gr.Radio(["transcribe", "translate"], label="Task", value="transcribe"),
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  gr.Checkbox(value=False, label="Return timestamps"),
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  ],