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Merge branch 'upstream' into concedo_experimental
# Conflicts: # CMakeLists.txt # docs/speculative.md # ggml/src/ggml-cuda/CMakeLists.txt # ggml/src/ggml-hexagon/ggml-hexagon.cpp # ggml/src/ggml-hexagon/htp/hmx-matmul-ops.c # ggml/src/ggml-hexagon/htp/hmx-ops.h # ggml/src/ggml-hexagon/htp/main.c # ggml/src/ggml-hexagon/htp/matmul-ops.c # ggml/src/ggml-hexagon/htp/rope-ops.c # ggml/src/ggml-hexagon/htp/ssm-conv.c # ggml/src/ggml-opencl/ggml-opencl.cpp # scripts/snapdragon/adb/run-bench.sh # scripts/snapdragon/adb/run-cli.sh # scripts/snapdragon/adb/run-completion.sh # scripts/snapdragon/adb/run-mtmd.sh # scripts/snapdragon/windows/run-bench.ps1 # scripts/snapdragon/windows/run-cli.ps1 # scripts/snapdragon/windows/run-completion.ps1 # scripts/snapdragon/windows/run-mtmd.ps1 # src/llama-vocab.cpp # tests/test-backend-ops.cpp # tools/batched-bench/CMakeLists.txt # tools/batched-bench/batched-bench.cpp # tools/cli/CMakeLists.txt # tools/cli/README.md # tools/cli/cli.cpp # tools/completion/CMakeLists.txt # tools/completion/README.md # tools/llama-bench/CMakeLists.txt # tools/llama-bench/llama-bench.cpp # tools/mtmd/CMakeLists.txt # tools/mtmd/tests/test-deepseek-ocr.py # tools/mtmd/tests/tests-requirements.txt # tools/perplexity/CMakeLists.txt # tools/perplexity/perplexity.cpp # tools/quantize/CMakeLists.txt # tools/server/CMakeLists.txt # tools/server/README.md # ty.toml
This commit is contained in:
+25
-12
@@ -500,15 +500,21 @@ bool llm_graph_input_attn_k::can_reuse(const llm_graph_params & params) {
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}
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void llm_graph_input_attn_kv_iswa::set_input(const llama_ubatch * ubatch) {
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mctx->get_base()->set_input_k_idxs(self_k_idxs, ubatch);
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mctx->get_base()->set_input_v_idxs(self_v_idxs, ubatch);
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// base tensors may not be allocated if there are no non-SWA attention layers
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if (self_k_idxs && self_k_idxs->buffer) {
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mctx->get_base()->set_input_k_idxs(self_k_idxs, ubatch);
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mctx->get_base()->set_input_v_idxs(self_v_idxs, ubatch);
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mctx->get_base()->set_input_kq_mask(self_kq_mask, ubatch, cparams.causal_attn);
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mctx->get_base()->set_input_kq_mask(self_kq_mask, ubatch, cparams.causal_attn);
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}
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mctx->get_swa()->set_input_k_idxs(self_k_idxs_swa, ubatch);
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mctx->get_swa()->set_input_v_idxs(self_v_idxs_swa, ubatch);
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// swa tensors may not be allocated if there are no SWA attention layers
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if (self_k_idxs_swa && self_k_idxs_swa->buffer) {
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mctx->get_swa()->set_input_k_idxs(self_k_idxs_swa, ubatch);
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mctx->get_swa()->set_input_v_idxs(self_v_idxs_swa, ubatch);
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mctx->get_swa()->set_input_kq_mask(self_kq_mask_swa, ubatch, cparams.causal_attn);
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mctx->get_swa()->set_input_kq_mask(self_kq_mask_swa, ubatch, cparams.causal_attn);
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}
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if (self_k_rot) {
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mctx->get_base()->set_input_k_rot(self_k_rot);
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@@ -534,14 +540,21 @@ bool llm_graph_input_attn_kv_iswa::can_reuse(const llm_graph_params & params) {
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bool res = true;
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res &= self_k_idxs->ne[0] == params.ubatch.n_tokens;
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//res &= self_v_idxs->ne[0] == params.ubatch.n_tokens; // TODO: need to move this to the unified cache and check there
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// base tensors may not be allocated if there are no non-SWA attention layers
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if (self_k_idxs && self_k_idxs->buffer) {
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res &= self_k_idxs->ne[0] == params.ubatch.n_tokens;
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//res &= self_v_idxs->ne[0] == params.ubatch.n_tokens; // TODO: need to move this to the unified cache and check there
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res &= self_k_idxs_swa->ne[0] == params.ubatch.n_tokens;
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//res &= self_v_idxs_swa->ne[0] == params.ubatch.n_tokens; // TODO: need to move this to the unified cache and check there
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res &= can_reuse_kq_mask(self_kq_mask, mctx->get_base(), params.ubatch, params.cparams);
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}
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res &= can_reuse_kq_mask(self_kq_mask, mctx->get_base(), params.ubatch, params.cparams);
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res &= can_reuse_kq_mask(self_kq_mask_swa, mctx->get_swa(), params.ubatch, params.cparams);
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// swa tensors may not be allocated if there are no SWA attention layers
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if (self_k_idxs_swa && self_k_idxs_swa->buffer) {
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res &= self_k_idxs_swa->ne[0] == params.ubatch.n_tokens;
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//res &= self_v_idxs_swa->ne[0] == params.ubatch.n_tokens; // TODO: need to move this to the unified cache and check there
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res &= can_reuse_kq_mask(self_kq_mask_swa, mctx->get_swa(), params.ubatch, params.cparams);
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}
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return res;
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}
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