make the codebook bigger
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@ -454,7 +454,7 @@ class Wav2Vec2GumbelVectorQuantizer(nn.Module):
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GUMBEL-SOFTMAX](https://arxiv.org/pdf/1611.01144.pdf) for more information.
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"""
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def __init__(self, proj_dim=1024, codevector_dim=256, num_codevector_groups=2, num_codevectors_per_group=320):
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def __init__(self, proj_dim=1024, codevector_dim=512, num_codevector_groups=2, num_codevectors_per_group=320):
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super().__init__()
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self.codevector_dim = codevector_dim
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self.num_groups = num_codevector_groups
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@ -501,7 +501,7 @@ class Wav2Vec2GumbelVectorQuantizer(nn.Module):
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hidden_states = hidden_states.view(batch_size * sequence_length * self.num_groups, -1)
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if self.training:
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# sample code vector probs via gumbel in differentiateable way
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# sample code vector probs via gumbel in differentiable way
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codevector_probs = nn.functional.gumbel_softmax(
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hidden_states.float(), tau=self.temperature, hard=True
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).type_as(hidden_states)
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@ -513,7 +513,7 @@ class Wav2Vec2GumbelVectorQuantizer(nn.Module):
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perplexity = self._compute_perplexity(codevector_soft_dist, mask_time_indices)
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else:
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# take argmax in non-differentiable way
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# comptute hard codevector distribution (one hot)
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# compute hard codevector distribution (one hot)
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codevector_idx = hidden_states.argmax(dim=-1)
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codevector_probs = hidden_states.new_zeros(*hidden_states.shape).scatter_(
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-1, codevector_idx.view(-1, 1), 1.0
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