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https://github.com/dogkeeper886/ollama37.git
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llama: update vendored code to commit 40c6d79f (#7875)
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8
llama/ggml-cuda/mmq.cu
vendored
8
llama/ggml-cuda/mmq.cu
vendored
@@ -1,5 +1,5 @@
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/**
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* llama.cpp - commit 3f1ae2e32cde00c39b96be6d01c2997c29bae555 - do not edit this file
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* llama.cpp - commit 40c6d79fb52f995f47507fedfeaae2ac05d9b35c - do not edit this file
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*
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* MIT License
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*
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@@ -34,8 +34,6 @@ void ggml_cuda_op_mul_mat_q(
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const int64_t ne00 = src0->ne[0];
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const int64_t nb01 = src0->nb[1];
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const int64_t ne10 = src1->ne[0];
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const int64_t ne11 = src1->ne[1];
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GGML_ASSERT(ne10 % QK8_1 == 0);
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@@ -43,7 +41,7 @@ void ggml_cuda_op_mul_mat_q(
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const int64_t ne0 = dst->ne[0];
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const int64_t row_diff = row_high - row_low;
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const int64_t stride00 = nb01 / ggml_type_size(src0->type);
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const int64_t stride00 = ne00 / ggml_blck_size(src0->type);
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int id = ggml_cuda_get_device();
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const int compute_capability = ggml_cuda_info().devices[id].cc;
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@@ -176,5 +174,5 @@ bool ggml_cuda_should_use_mmq(enum ggml_type type, int cc, int64_t ne11) {
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return cc < CC_VOLTA || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
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}
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return cc < CC_RDNA3 || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
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return (cc < CC_RDNA3 && cc != CC_CDNA && cc != CC_VEGA20) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
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}
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