mirror of
https://github.com/likelovewant/ollama-for-amd.git
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update llama.cpp to e782c9e735f93ab4767ffc37462c523b73a17ddc
This commit is contained in:
51
llama/ggml.h
51
llama/ggml.h
@@ -1,5 +1,5 @@
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/**
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* llama.cpp - git 5bf2a2771886ee86137e01dbc7492f78fb392066
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* llama.cpp - git e782c9e735f93ab4767ffc37462c523b73a17ddc
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*
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* MIT License
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*
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@@ -227,8 +227,13 @@
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#define GGML_MAX_NAME 48
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#define GGML_DEFAULT_N_THREADS 4
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#define GGML_EXIT_SUCCESS 0
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#define GGML_EXIT_ABORTED 1
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#define GGML_UNUSED(x) (void)(x)
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#define GGML_ASSERT(x) \
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do { \
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if (!(x)) { \
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@@ -389,6 +394,8 @@ extern "C" {
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GGML_OP_CLAMP,
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GGML_OP_CONV_1D,
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GGML_OP_CONV_2D,
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GGML_OP_POOL_1D,
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GGML_OP_POOL_2D,
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GGML_OP_FLASH_ATTN,
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GGML_OP_FLASH_FF,
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@@ -468,6 +475,10 @@ extern "C" {
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// the `n_tasks` of nodes, 1:1 mapping to cgraph nodes
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int n_tasks[GGML_MAX_NODES];
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// abort ggml_graph_compute when true
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bool (*abort_callback)(void * data);
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void * abort_callback_data;
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};
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// computation graph
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@@ -1136,6 +1147,17 @@ extern "C" {
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int mode,
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int n_ctx);
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// custom RoPE, in-place, returns view(a)
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GGML_API struct ggml_tensor * ggml_rope_custom_inplace(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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int n_past,
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int n_dims,
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int mode,
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float freq_base,
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float freq_scale,
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int n_ctx);
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// rotary position embedding backward, i.e compute dx from dy
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// a - dy
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GGML_API struct ggml_tensor * ggml_rope_back(
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@@ -1190,6 +1212,31 @@ extern "C" {
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int s,
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int d);
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enum ggml_op_pool {
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GGML_OP_POOL_MAX,
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GGML_OP_POOL_AVG,
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GGML_OP_POOL_COUNT,
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};
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GGML_API struct ggml_tensor* ggml_pool_1d(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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enum ggml_op_pool op,
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int k0, // kernel size
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int s0, // stride
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int p0); // padding
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GGML_API struct ggml_tensor* ggml_pool_2d(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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enum ggml_op_pool op,
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int k0,
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int k1,
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int s0,
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int s1,
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int p0,
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int p1);
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GGML_API struct ggml_tensor * ggml_flash_attn(
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struct ggml_context * ctx,
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struct ggml_tensor * q,
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@@ -1329,7 +1376,7 @@ extern "C" {
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// ggml_graph_plan() has to be called before ggml_graph_compute()
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// when plan.work_size > 0, caller must allocate memory for plan.work_data
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GGML_API struct ggml_cplan ggml_graph_plan (struct ggml_cgraph * cgraph, int n_threads /*= GGML_DEFAULT_N_THREADS*/);
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GGML_API void ggml_graph_compute(struct ggml_cgraph * cgraph, struct ggml_cplan * cplan);
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GGML_API int ggml_graph_compute(struct ggml_cgraph * cgraph, struct ggml_cplan * cplan);
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GGML_API void ggml_graph_reset (struct ggml_cgraph * cgraph);
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// same as ggml_graph_compute() but the work data is allocated as a part of the context
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