Proper check for None type for new_name to avoid crash; formatting; revert change to base class write_tensors()
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96695fb96b
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1 changed files with 5 additions and 4 deletions
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@ -164,7 +164,7 @@ class Model(ABC):
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data = data.astype(np.float32)
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# if f16 desired, convert any float32 2-dim weight tensors to float16
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if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and not new_name.endswith("_norm.weight") and n_dims == 2:
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if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2:
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data = data.astype(np.float16)
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print(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}")
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@ -1264,6 +1264,7 @@ class StableLMModel(Model):
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print(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}")
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self.gguf_writer.add_tensor(new_name, data)
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def _stack_qk_norm(self, block_count, name, tensor_map, n_head, norms, n_dims, layer_name="q_layernorm"):
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for bid in range(block_count):
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datas = []
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@ -1275,15 +1276,15 @@ class StableLMModel(Model):
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data_dtype = data.dtype
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merged_name = f"model.layers.{bid}.self_attn.{layer_name}.weight"
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new_name = tensor_map.get_name(merged_name, try_suffixes=(".weight", ".bias"))
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if new_name is None:
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print(f"Can not map tensor {name!r}")
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sys.exit()
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if self.ftype == 1 and data_dtype == np.float16 and (n_dims == 1 or new_name.endswith("_norm.weight")):
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data = data.astype(np.float32)
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# if f16 desired, convert any float32 2-dim weight tensors to float16
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if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and not new_name.endswith("_norm.weight") and n_dims == 2:
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data = data.astype(np.float16)
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if new_name is None:
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print(f"Can not map tensor {name!r}")
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sys.exit()
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print(f"{new_name}, n_dims = {len(data.shape)}, shape = {data.shape} --> {data.dtype}")
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