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wenhuach21
reviewed
Apr 25, 2025
auto_round/data_type/int.py
Outdated
| @@ -130,6 +199,86 @@ def quant_tensor_asym_dq(tensor, bits=4, group_size=-1, v=0, min_scale=1.0, max_ | |||
| zp = round_ste(wmin_m / scale) # remove this later | |||
| return qdq_result, {"scale": scale, "d_scale": d_scale}, {"wmin_m": wmin_m, "d_wmin_m": d_wmin_m} | |||
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| def quant_tensor_k_quant_cuda(data, num_bits=4, group_size=32): | |||
| """Quantize tensor per group based on k quant. | |||
| Ref: https://github.com/ggml-org/llama.cpp/blob/64eda5deb9859e87a020e56bab5d2f9ca956f1de/ggml/src/ggml-quants.c | |||
n1ck-guo
reviewed
Apr 25, 2025
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| mad_1 = cp.array(mad) | ||
| best_mad_1 = cp.array(best_mad) | ||
| idx_to_replace = cp.where(mad_1 < best_mad_1)[0] |
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change this line to idx_to_replace = cp.where((mad_1 < best_mad_1) & (D > 0))[0]
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