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author | Robin Schmidt <robin.schmidt.97@web.de> | 2021-11-15 17:27:02 +0100 |
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committer | Robin Schmidt <robin.schmidt.97@web.de> | 2021-11-15 17:27:02 +0100 |
commit | 67a1283501fa24d346f8e8efb4fc888a9ed8d193 (patch) | |
tree | 3b46cf5ac603ba1342565390294fc3c296cbc916 /bitsandbytes | |
parent | 037022e878974b5dfeb354098a467a46618f9d85 (diff) |
[FIX] passing of sparse in StableEmbedding
Diffstat (limited to 'bitsandbytes')
-rw-r--r-- | bitsandbytes/nn/modules.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/bitsandbytes/nn/modules.py b/bitsandbytes/nn/modules.py index bf0945c..ce2f3a4 100644 --- a/bitsandbytes/nn/modules.py +++ b/bitsandbytes/nn/modules.py @@ -15,8 +15,8 @@ from bitsandbytes.optim import GlobalOptimManager class StableEmbedding(torch.nn.Embedding): def __init__(self, num_embeddings: int, embedding_dim: int, padding_idx: Optional[int] = None, max_norm: Optional[float] = None, norm_type: float = 2., scale_grad_by_freq: bool = False, - sparse: bool = True, _weight: Optional[Tensor] = None) -> None: - super(StableEmbedding, self).__init__(num_embeddings, embedding_dim, padding_idx, max_norm, norm_type, scale_grad_by_freq, False, _weight) + sparse: bool = False, _weight: Optional[Tensor] = None) -> None: + super(StableEmbedding, self).__init__(num_embeddings, embedding_dim, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse, _weight) self.norm = torch.nn.LayerNorm(embedding_dim) GlobalOptimManager.get_instance().register_parameters(self.weight) GlobalOptimManager.get_instance().override_config(self.weight, 'optim_bits', 32) |