Merge pull request #120 from VE-FORBRYDERNE/lazy-loader
Fix some lazy loader edge cases
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commit
c873d36374
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@ -9,8 +9,7 @@
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"static_weights": {
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"model.embed_tokens.weight": {"mtj": {"module": "embedding_shard/~/linear", "param": "w", "transforms": ["no_transpose", "vocab_pad"]}},
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"model.layer_norm.weight": {"mtj": {"module": "projection_shard/~/replicated_layer_norm", "param": "scale"}},
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"model.layer_norm.bias": {"mtj": {"module": "projection_shard/~/replicated_layer_norm", "param": "offset"}},
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"lm_head.weight": {"mtj": {"module": "projection_shard/~/linear", "param": "w", "transforms": ["vocab_pad"]}}
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"model.layer_norm.bias": {"mtj": {"module": "projection_shard/~/replicated_layer_norm", "param": "offset"}}
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},
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"layer_weights": {
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"model.layers.{layer}.self_attn.q_proj.weight": {"mtj": {"module": "layer_{layer}/~/linear", "param": "w"}},
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@ -89,7 +89,7 @@ class LazyTensor:
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def __repr__(self):
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return self.__view(repr)
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def materialize(self, checkpoint: Union[zipfile.ZipFile, zipfile.ZipExtFile], map_location=None) -> torch.Tensor:
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def materialize(self, checkpoint: Union[zipfile.ZipFile, zipfile.ZipExtFile], map_location=None, no_grad=True) -> torch.Tensor:
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size = reduce(lambda x, y: x * y, self.shape, 1)
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dtype = self.dtype
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nbytes = size if dtype is torch.bool else size * ((torch.finfo if dtype.is_floating_point else torch.iinfo)(dtype).bits >> 3)
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@ -106,7 +106,7 @@ class LazyTensor:
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storage = torch.serialization._get_restore_location(map_location)(storage, self.location)
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tensor = torch.tensor([], dtype=storage.dtype, device=storage.device)
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tensor.set_(storage, 0, self.shape, self.stride)
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tensor.requires_grad = self.requires_grad
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tensor.requires_grad = not no_grad and self.requires_grad
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tensor._backward_hooks = self.backward_hooks
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return tensor
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