Revert ggml_tensor_name addition
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@@ -77,8 +77,7 @@ def gguf_sd_loader(path, handle_prefix="model.diffusion_model.", require_prefix=
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sd[sd_key] = GGMLTensor(
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torch_tensor,
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tensor_type = tensor.tensor_type,
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tensor_shape = shape,
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ggml_tensor_name = tensor_name,
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tensor_shape = shape
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)
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dt[tensor_type_str] = dt.get(tensor_type_str, 0) + 1
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@@ -9,14 +9,13 @@ class GGMLTensor(torch.Tensor):
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"""
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Main tensor-like class for storing quantized weights
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"""
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def __init__(self, *args, tensor_type, tensor_shape, patches=[], ggml_tensor_name=None, **kwargs):
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def __init__(self, *args, tensor_type, tensor_shape, patches=[], **kwargs):
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super().__init__()
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self.tensor_type = tensor_type
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self.tensor_shape = tensor_shape
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self.patches = patches
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self.ggml_tensor_name = ggml_tensor_name
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def __new__(cls, *args, tensor_type, tensor_shape, patches=[], ggml_tensor_name=None, **kwargs):
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def __new__(cls, *args, tensor_type, tensor_shape, patches=[], **kwargs):
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return super().__new__(cls, *args, **kwargs)
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def to(self, *args, **kwargs):
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@@ -24,7 +23,6 @@ class GGMLTensor(torch.Tensor):
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new.tensor_type = getattr(self, "tensor_type", None)
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new.tensor_shape = getattr(self, "tensor_shape", new.data.shape)
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new.patches = getattr(self, "patches", []).copy()
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new.ggml_tensor_name = getattr(self, "ggml_tensor_name", None)
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return new
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def clone(self, *args, **kwargs):
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@@ -46,7 +44,6 @@ class GGMLTensor(torch.Tensor):
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new.tensor_type = getattr(self, "tensor_type", None)
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new.tensor_shape = getattr(self, "tensor_shape", new.data.shape)
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new.patches = getattr(self, "patches", []).copy()
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new.ggml_tensor_name = getattr(self, "ggml_tensor_name", None)
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return new
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@property
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