parent
6981745fe4
commit
156af15d1e
2 changed files with 7 additions and 5 deletions
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@ -30,7 +30,8 @@ ggml_tensor_qtype = {"sym_int4": 2, # q4_0 in ggml
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"sym_int5": 6, # q5_0 in ggml
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"asym_int5": 7, # q5_1 in ggml
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"sym_int8": 8, # q8_0 in ggml
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"nf4": 10}
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"nf4": 10,
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"nf3": 11}
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_llama_quantize_type = {"q4_0": 2,
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"q4_1": 3,
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@ -62,6 +62,7 @@ TORCH_LINEAR_THRESHOLD = 96
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SYM_INT4 = ggml_tensor_qtype["sym_int4"]
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SYM_INT8 = ggml_tensor_qtype["sym_int8"]
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NF4 = ggml_tensor_qtype["nf4"]
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NF3 = ggml_tensor_qtype["nf3"]
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def ggml_convert_qtype(tensor: torch.Tensor, qtype: int,
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@ -101,7 +102,7 @@ def ggml_q_format_convet_cpu2xpu(tensor: torch.Tensor, num_elem: int, qtype: int
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src = ctypes.c_void_p(tensor.data.data_ptr())
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if qtype in [SYM_INT4, SYM_INT8, NF4]:
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if qtype in [SYM_INT4, SYM_INT8, NF4, NF3]:
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dst_tensor = torch.empty_like(tensor)
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elif qtype == ggml_tensor_qtype["sym_int5"]:
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QK = ggml.ggml_qk_size(qtype)
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@ -126,7 +127,7 @@ def ggml_q_format_convet_xpu2cpu(tensor: torch.Tensor, num_elem: int, qtype: int
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src = ctypes.c_void_p(tensor.data.data_ptr())
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if qtype in [SYM_INT4, SYM_INT8, NF4]:
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if qtype in [SYM_INT4, SYM_INT8, NF4, NF3]:
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dst_tensor = torch.empty_like(tensor)
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elif qtype == ggml_tensor_qtype["sym_int5"]:
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QK = ggml.ggml_qk_size(ggml_tensor_qtype["asym_int5"])
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@ -363,8 +364,8 @@ class LowBitLinear(nn.Linear):
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else:
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# CPU logic
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# todo may need to set a different number on different platforms
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invalidInputError(self.qtype != ggml_tensor_qtype["nf4"],
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"NF4 quantization is currently not supported on CPU")
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invalidInputError(self.qtype != NF3 and self.qtype != NF4,
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"NF3 and NF4 quantization are currently not supported on CPU")
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if IS_SERVER and (not IS_SPR) and \
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self.qtype == SYM_INT4 and x_2d.shape[0] >= TORCH_LINEAR_THRESHOLD:
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x0_fp32 = ggml_int4_convert_fp32(x0, self.weight_shape, self.weight_length)
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