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from transformers import WhisperConfig | |
class WhisperVQConfig(WhisperConfig): | |
def __init__(self, | |
pooling_kernel_size=None, | |
pooling_type="max", | |
pooling_position=0, | |
quantize_vocab_size=None, | |
quantize_position=16, | |
quantize_commit_coefficient=0.25, | |
quantize_loss_scale=1.0, | |
quantize_ema_decay=None, | |
quantize_restart_interval=None, | |
quantize_encoder_only=False, | |
quantize_causal_encoder=False, | |
quantize_causal_block_size=None, | |
skip_language_detection=False, | |
encoder_causal_attention=False, | |
encoder_causal_convolution=False, | |
**kwargs): | |
self.pooling_kernel_size = pooling_kernel_size | |
self.pooling_type = pooling_type | |
self.pooling_position = pooling_position | |
self.quantize_vocab_size = quantize_vocab_size | |
self.quantize_position = quantize_position | |
self.quantize_commit_coefficient = quantize_commit_coefficient | |
self.quantize_loss_scale = quantize_loss_scale | |
self.quantize_ema_decay = quantize_ema_decay | |
self.quantize_restart_interval = quantize_restart_interval | |
self.quantize_encoder_only = quantize_encoder_only | |
self.quantize_causal_encoder = quantize_causal_encoder | |
self.quantize_causal_block_size = quantize_causal_block_size | |
self.skip_language_detection = skip_language_detection | |
self.encoder_causal_attention = encoder_causal_attention | |
self.encoder_causal_convolution = encoder_causal_convolution | |
super().__init__(**kwargs) | |