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https://github.com/ggerganov/llama.cpp.git
synced 2025-02-07 08:53:16 +01:00
Remove changes not related to softmax
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495e7ea48d
commit
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@ -79,7 +79,7 @@ void ggml_sycl_op_flatten(ggml_backend_sycl_context & ctx, const ggml_tensor *sr
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float * src0_ddf = (float *) src0->data;
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float * src0_ddf = (float *) src0->data;
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float * src1_ddf = use_src1 ? (float *) src1->data : nullptr;
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float * src1_ddf = use_src1 ? (float *) src1->data : nullptr;
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float * dst_ddf = (float *) dst->data;
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float * dst_ddf = (float *) dst->data;
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/* These are never used */
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ggml_sycl_pool_alloc<float> src0_f(ctx.pool());
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ggml_sycl_pool_alloc<float> src0_f(ctx.pool());
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ggml_sycl_pool_alloc<float> src1_f(ctx.pool());
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ggml_sycl_pool_alloc<float> src1_f(ctx.pool());
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ggml_sycl_pool_alloc<float> dst_f(ctx.pool());
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ggml_sycl_pool_alloc<float> dst_f(ctx.pool());
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@ -2,7 +2,6 @@
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#include "dmmv.hpp"
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#include "dmmv.hpp"
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#include "dequantize.hpp"
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#include "dequantize.hpp"
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#include "presets.hpp"
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#include "presets.hpp"
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#include "ggml-impl.h"
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static void convert_f16(const void * vx, const int64_t ib, const int iqs, dfloat2 & v){
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static void convert_f16(const void * vx, const int64_t ib, const int iqs, dfloat2 & v){
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@ -974,7 +973,6 @@ void ggml_sycl_op_dequantize_mul_mat_vec(
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}
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}
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#else
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#else
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const dfloat * src1_dfloat = (const dfloat *) src1_ddf_i; // dfloat == float, no conversion
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const dfloat * src1_dfloat = (const dfloat *) src1_ddf_i; // dfloat == float, no conversion
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GGML_UNUSED(ctx);
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#endif // GGML_SYCL_F16
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#endif // GGML_SYCL_F16
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switch (src0->type) {
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switch (src0->type) {
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@ -1012,7 +1010,7 @@ void ggml_sycl_op_dequantize_mul_mat_vec(
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convert_mul_mat_vec_f16_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream);
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convert_mul_mat_vec_f16_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream);
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break;
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break;
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default:
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default:
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GGML_LOG_ERROR("ggml_sycl_op_dequantize_mul_mat_vec unsupported GGML_TYPE %d\n", src0->type);
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printf("ggml_sycl_op_dequantize_mul_mat_vec unsupported GGML_TYPE %d\n", src0->type);
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GGML_ABORT("fatal error");
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GGML_ABORT("fatal error");
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break;
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break;
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}
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}
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@ -97,6 +97,9 @@ static void rwkv_wkv_f32_kernel(
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void ggml_sycl_op_rwkv_wkv6(ggml_backend_sycl_context& ctx, ggml_tensor* dst) {
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void ggml_sycl_op_rwkv_wkv6(ggml_backend_sycl_context& ctx, ggml_tensor* dst) {
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const ggml_tensor *src0 = dst->src[0];
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const ggml_tensor *src1 = dst->src[1];
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const float* k_d = (const float*)dst->src[0]->data;
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const float* k_d = (const float*)dst->src[0]->data;
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const float* v_d = (const float*)dst->src[1]->data;
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const float* v_d = (const float*)dst->src[1]->data;
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const float* r_d = (const float*)dst->src[2]->data;
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const float* r_d = (const float*)dst->src[2]->data;
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@ -134,4 +137,7 @@ void ggml_sycl_op_rwkv_wkv6(ggml_backend_sycl_context& ctx, ggml_tensor* dst) {
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);
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);
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});
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});
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});
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});
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GGML_UNUSED(src0);
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GGML_UNUSED(src1);
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}
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}
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