20 lines
769 B
Python
20 lines
769 B
Python
import torch
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from transformers import WhisperProcessor, WhisperForConditionalGeneration
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def get_whisper_encoder():
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processor = WhisperProcessor.from_pretrained("openai/whisper-large-v3")
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model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-large-v3").model.encoder
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return processor, model.eval()
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if __name__=="__main__":
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import numpy as np
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processor, model = get_whisper_encoder()
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model = model.cuda()
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with torch.no_grad():
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input_features = processor(np.random.rand(16000*30,), sampling_rate=16000, return_tensors="pt").input_features.cuda()
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print(input_features.shape)
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out = model(input_features.repeat(10,1,1))
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import pdb;pdb.set_trace()
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print(list(out.values())[0].shape)
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