fix: correct misspellings in code comments (#21217)

- emdeddings → embeddings (gemma3.cpp, gemma3n-iswa.cpp,
gemma-embedding.cpp)
- imlpemented → implemented (llama-adapter.cpp)
- interere → interfere (llama-graph.cpp)
- overridde → overridden (chat.cpp)
- stastistics → statistics (ngram-map.h)
- layed → laid (llama-kv-cache.h)
- worster → worst (llama-context.cpp)
- sequantial → sequential (llama-batch.h)

diff --git a/common/chat.cpp b/common/chat.cpp
index bb76fbbb060dedb50ffb4d33b58d892424da7a50..bf43087285c21ae7bbb52ac76a682c1112e3e88f 100644 (file)
--- a/common/chat.cpp
+++ b/common/chat.cpp
@@ -221,7 +221,7 @@ using chat_template_caps = jinja::caps;
 struct common_chat_templates {
     bool add_bos;
     bool add_eos;
-    bool has_explicit_template;  // Model had builtin template or template overridde was specified.
+    bool has_explicit_template;  // Model had builtin template or template overridden was specified.
     std::unique_ptr<common_chat_template> template_default;  // always set (defaults to chatml)
     std::unique_ptr<common_chat_template> template_tool_use;
 };

diff --git a/common/ngram-map.h b/common/ngram-map.h
index d84e71915154c868ac9baaee93cc063d09b1a2cc..97608ef170f25783ba78347ebb63b50c4d2e638f 100644 (file)
--- a/common/ngram-map.h
+++ b/common/ngram-map.h
@@ -51,7 +51,7 @@ struct common_ngram_map_value {
 // statistics of a n-gram
 struct common_ngram_map_key {
     size_t   key_idx;   // index of key n-gram in token-history
-    size_t   stat_idx;  // index of last token of stastistics computation (key_num, values)
+    size_t   stat_idx;  // index of last token of statistics computation (key_num, values)
 
     uint16_t key_num;   // number of occurrences of this key n-gram in token-history
     common_ngram_map_value values[COMMON_NGRAM_MAX_VALUES]; // some known values after the key

diff --git a/src/llama-adapter.cpp b/src/llama-adapter.cpp
index 2f2cc12af04ea7eca827bf9dd1a6c5f007354755..4a1aaa955a87d6d8e9c6a1c49abf6879784668b6 100644 (file)
--- a/src/llama-adapter.cpp
+++ b/src/llama-adapter.cpp
@@ -294,7 +294,7 @@ static void llama_adapter_lora_init_impl(llama_model & model, const char * path_
     }
 
     // get extra buffer types of the CPU
-    // TODO: a more general solution for non-CPU extra buft should be imlpemented in the future
+    // TODO: a more general solution for non-CPU extra buft should be implemented in the future
     //       ref: https://github.com/ggml-org/llama.cpp/pull/12593#pullrequestreview-2718659948
     std::vector<ggml_backend_buffer_type_t> buft_extra;
     {

diff --git a/src/llama-batch.h b/src/llama-batch.h
index 8e6fac0efabba3d5f1b3dd528ebb9e3d2c9ec99a..f77520e86c3ca45ffb5541597790005b76d5d4cd 100644 (file)
--- a/src/llama-batch.h
+++ b/src/llama-batch.h
@@ -18,7 +18,7 @@ struct llama_ubatch {
     }
 
     // typical for M-RoPE cases:
-    //   0 - sequantial position of the tokens/embeddings in the sequence
+    //   0 - sequential position of the tokens/embeddings in the sequence
     //   1 - y position in the image
     //   2 - x position in the image
     //   3 - other

diff --git a/src/llama-context.cpp b/src/llama-context.cpp
index f6ce2817a85d0c0c222272431f9bf44ba1c8ec4c..a808e3e454294d3a15593409c423933eae231dad 100644 (file)
--- a/src/llama-context.cpp
+++ b/src/llama-context.cpp
@@ -586,7 +586,7 @@ void llama_context::sched_reserve() {
 
     // reserve again with pp graph to avoid ggml-alloc reallocations during inference
     {
-        // TODO: not sure if the following graph would be worster case for multi-stream KV caches:
+        // TODO: not sure if the following graph would be worst case for multi-stream KV caches:
         //
         // auto * gf = graph_reserve(n_tokens, 1, n_tokens, mctx.get());
         //

diff --git a/src/llama-graph.cpp b/src/llama-graph.cpp
index 11759ae1e2b1456b8fae2e99aa6b4e80b908ffba..c2833b75ced784f9ff120d9f5adf0c93f61bc9d7 100644 (file)
--- a/src/llama-graph.cpp
+++ b/src/llama-graph.cpp
@@ -1665,7 +1665,7 @@ ggml_tensor * llm_graph_context::build_inp_attn_scale() const {
 
 ggml_tensor * llm_graph_context::build_inp_out_ids() const {
     // note: when all tokens are output, we could skip this optimization to spare the ggml_get_rows() calls,
-    //       but this would make the graph topology depend on the number of output tokens, which can interere with
+    //       but this would make the graph topology depend on the number of output tokens, which can interfere with
     //       features that require constant topology such as pipeline parallelism
     //       ref: https://github.com/ggml-org/llama.cpp/pull/14275#issuecomment-2987424471
     //if (n_outputs < n_tokens) {

diff --git a/src/llama-kv-cache.h b/src/llama-kv-cache.h
index 33c78c5f2107ec7f48b213240a706e589dab8f8d..90a0610c49dd7b1c797fb2b05953b4bbd076f40f 100644 (file)
--- a/src/llama-kv-cache.h
+++ b/src/llama-kv-cache.h
@@ -333,7 +333,7 @@ public:
     ggml_tensor * get_v(ggml_context * ctx, int32_t il) const;
 
     // store k_cur and v_cur in the cache based on the provided head location
-    // note: the heads in k_cur and v_cur should be layed out contiguously in memory
+    // note: the heads in k_cur and v_cur should be laid out contiguously in memory
     //   - k_cur  [n_embd_head_k, n_head_k, n_tokens]
     //   - k_idxs [n_tokens]
     //   - v_cur  [n_embd_head_v, n_head_v, n_tokens]

diff --git a/src/models/gemma-embedding.cpp b/src/models/gemma-embedding.cpp
index 98110d45e3b8d5385d3a9cdc6e146fa7eab57a27..b2499d8e6a57c4205f5798fc7b98bc894d67fd6e 100644 (file)
--- a/src/models/gemma-embedding.cpp
+++ b/src/models/gemma-embedding.cpp
@@ -9,7 +9,7 @@ llm_build_gemma_embedding::llm_build_gemma_embedding(const llama_model & model,
 
     inpL = build_inp_embd(model.tok_embd);
 
-    // important: do not normalize weights for raw embeddings input (i.e. encoded image emdeddings)
+    // important: do not normalize weights for raw embeddings input (i.e. encoded image embeddings)
     inpL = ggml_scale(ctx0, inpL, ubatch.token ? sqrtf(n_embd) : 1.0f);
     cb(inpL, "inp_scaled", -1);
 

diff --git a/src/models/gemma3.cpp b/src/models/gemma3.cpp
index bbb4d9a81e825dc8225f845dda040a31bba485a9..b7697436c75de01cb706541cf6f8812b1b4892ed 100644 (file)
--- a/src/models/gemma3.cpp
+++ b/src/models/gemma3.cpp
@@ -9,7 +9,7 @@ llm_build_gemma3<iswa>::llm_build_gemma3(const llama_model & model, const llm_gr
 
     inpL = build_inp_embd(model.tok_embd);
 
-    // important: do not normalize weights for raw embeddings input (i.e. encoded image emdeddings)
+    // important: do not normalize weights for raw embeddings input (i.e. encoded image embeddings)
     inpL = ggml_scale(ctx0, inpL, ubatch.token ? sqrtf(n_embd) : 1.0f);
     cb(inpL, "inp_scaled", -1);
 

diff --git a/src/models/gemma3n-iswa.cpp b/src/models/gemma3n-iswa.cpp
index 8ce2ae39c2f4c07f30f37835161b1432b1b840ef..f5c922c1dafe6c48bbe1e4f8de9c9c5faae4f375 100644 (file)
--- a/src/models/gemma3n-iswa.cpp
+++ b/src/models/gemma3n-iswa.cpp
@@ -12,7 +12,7 @@ llm_build_gemma3n_iswa::llm_build_gemma3n_iswa(const llama_model & model, const
 
     inpL = build_inp_embd(model.tok_embd);
 
-    // important: do not normalize weights for raw embeddings input (i.e. encoded image emdeddings)
+    // important: do not normalize weights for raw embeddings input (i.e. encoded image embeddings)
     inpL = ggml_scale(ctx0, inpL, ubatch.token ? sqrtf(n_embd) : 1.0f);
     cb(inpL, "inp_scaled", -1);