sanchit-gandhi commited on
Commit
77ac2cf
·
1 Parent(s): 7bd1e74
Files changed (3) hide show
  1. app.py +9 -9
  2. assets/example_1.wav +2 -2
  3. assets/example_2.wav +2 -2
app.py CHANGED
@@ -78,32 +78,32 @@ def transcribe(inputs):
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  inputs = {"array": inputs, "sampling_rate": pipe.feature_extractor.sampling_rate}
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  def _forward_distil_time(*args, **kwargs):
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- global distil_runtime
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  start_time = time.time()
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  result = distil_pipe_forward(*args, **kwargs)
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- distil_runtime = time.time() - start_time
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- distil_runtime = round(distil_runtime, 2)
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  return result
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  distil_pipe._forward = _forward_distil_time
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  distil_text = distil_pipe(inputs.copy(), batch_size=BATCH_SIZE)["text"]
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- yield distil_text, distil_runtime, None, None
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  def _forward_time(*args, **kwargs):
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- global runtime
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  start_time = time.time()
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  result = pipe_forward(*args, **kwargs)
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- runtime = time.time() - start_time
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- runtime = round(runtime, 2)
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  return result
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  pipe._forward = _forward_time
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  text = pipe(inputs, batch_size=BATCH_SIZE)["text"]
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- yield distil_text, distil_runtime, text, runtime
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  else:
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- input_features = processor(inputs, sampling_rate=processor.feature_extractor.sampling_rate, return_tensors="pt").input_features
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  # Run the generation in a separate thread, so that we can fetch the generated text in a non-blocking way.
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  generation_kwargs = dict(input_features, streamer=streamer, max_new_tokens=128, language="en", task="transcribe")
 
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  inputs = {"array": inputs, "sampling_rate": pipe.feature_extractor.sampling_rate}
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  def _forward_distil_time(*args, **kwargs):
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+ global distil_runtime_pipeline
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  start_time = time.time()
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  result = distil_pipe_forward(*args, **kwargs)
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+ distil_runtime_pipeline = time.time() - start_time
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+ distil_runtime_pipeline = round(distil_runtime_pipeline, 2)
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  return result
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  distil_pipe._forward = _forward_distil_time
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  distil_text = distil_pipe(inputs.copy(), batch_size=BATCH_SIZE)["text"]
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+ yield distil_text, distil_runtime_pipeline, None, None
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  def _forward_time(*args, **kwargs):
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+ global runtime_pipeline
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  start_time = time.time()
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  result = pipe_forward(*args, **kwargs)
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+ runtime_pipeline = time.time() - start_time
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+ runtime_pipeline = round(runtime_pipeline, 2)
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  return result
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  pipe._forward = _forward_time
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  text = pipe(inputs, batch_size=BATCH_SIZE)["text"]
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+ yield distil_text, distil_runtime_pipeline, text, runtime_pipeline
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  else:
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+ input_features = processor(inputs, sampling_rate=processor.feature_extractor.sampling_rate, return_tensors="pt")
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  # Run the generation in a separate thread, so that we can fetch the generated text in a non-blocking way.
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  generation_kwargs = dict(input_features, streamer=streamer, max_new_tokens=128, language="en", task="transcribe")
assets/example_1.wav CHANGED
@@ -1,3 +1,3 @@
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- oid sha256:1e938b9f81dea096ec7d3752e90afca8d370f7a461d3a08e1a559f4440ed055d
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- size 1963810
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:d96fece5c0c24d039801e9e39e9985982ad63becdab6c1a141992aa6dd37a615
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+ size 802110
assets/example_2.wav CHANGED
@@ -1,3 +1,3 @@
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  version https://git-lfs.github.com/spec/v1
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- oid sha256:81fc0857f7fe11416ede431db713a02fdb787bbc049802fe74c791f3b44e5bf4
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- size 1920044
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:1e938b9f81dea096ec7d3752e90afca8d370f7a461d3a08e1a559f4440ed055d
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+ size 1963810