chore : correct typos [no ci] (#20041)

* fix(docs): correct typos found during code review

Non-functional changes only:
- Fixed minor spelling mistakes in comments
- Corrected typos in user-facing strings
- No variables, logic, or functional code was modified.

Signed-off-by: Marcel Petrick <mail@marcelpetrick.it>

* Update docs/backend/CANN.md

Co-authored-by: Aaron Teo <taronaeo@gmail.com>

* Revert "Auxiliary commit to revert individual files from 846d1c301281178efbc6ce6060ad34c1ebe45af8"

This reverts commit 02fcf0c7db661d5ff3eff96b2b2db9fdb7213256.

* Update tests/test-backend-ops.cpp

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Update tests/test-backend-ops.cpp

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

---------

Signed-off-by: Marcel Petrick <mail@marcelpetrick.it>
Co-authored-by: Aaron Teo <taronaeo@gmail.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

tools/mtmd/clip-impl.h

@@ -68,7 +68,7 @@
 
 #define TN_POS_EMBD        "%s.position_embd.weight"
 #define TN_CLASS_EMBD      "v.class_embd"
-#define TN_PATCH_EMBD      "v.patch_embd.weight"  // not rename tensor with ".0" postfix for backwrad compat
+#define TN_PATCH_EMBD      "v.patch_embd.weight"  // not rename tensor with ".0" postfix for backward compat
 #define TN_PATCH_EMBD_1    "v.patch_embd.weight.1"
 #define TN_PATCH_BIAS      "v.patch_embd.bias"
 #define TN_NORM_EMBD       "v.norm_embd.%s"

tools/mtmd/clip-model.h

@@ -46,7 +46,7 @@ struct clip_hparams {
     float image_std[3];
 
     // for models using dynamic image size, we need to have a smaller image size to warmup
-    // otherwise, user will get OOM everytime they load the model
+    // otherwise, user will get OOM every time they load the model
     int32_t warmup_image_size = 0;
     int32_t warmup_audio_size = 3000;
 
@@ -221,7 +221,7 @@ struct clip_model {
     // embeddings
     ggml_tensor * class_embedding = nullptr;
     ggml_tensor * patch_embeddings_0 = nullptr;
-    ggml_tensor * patch_embeddings_1 = nullptr;  // second Conv2D kernel when we decouple Conv3D along temproal dimension (Qwen2VL)
+    ggml_tensor * patch_embeddings_1 = nullptr;  // second Conv2D kernel when we decouple Conv3D along temporal dimension (Qwen2VL)
     ggml_tensor * patch_bias = nullptr;
     ggml_tensor * position_embeddings = nullptr;
     ggml_tensor * norm_embd_w = nullptr;

tools/mtmd/clip.cpp

@@ -2287,7 +2287,7 @@ static void normalize_image_u8_to_f32(const clip_image_u8 & src, clip_image_f32
     }
 }
 
-// set of tools to manupulate images
+// set of tools to manipulate images
 // in the future, we can have HW acceleration by allowing this struct to access 3rd party lib like imagick or opencv
 struct img_tool {
     enum resize_algo {

tools/mtmd/legacy-models/minicpmv-convert-image-encoder-to-gguf.py

@@ -186,7 +186,7 @@ def trunc_normal_tf_(
     best when :math:`a \\leq \text{mean} \\leq b`.
     NOTE: this 'tf' variant behaves closer to Tensorflow / JAX impl where the
     bounds [a, b] are applied when sampling the normal distribution with mean=0, std=1.0
-    and the result is subsquently scaled and shifted by the mean and std args.
+    and the result is subsequently scaled and shifted by the mean and std args.
     Args:
         tensor: an n-dimensional `torch.Tensor`
         mean: the mean of the normal distribution

tools/mtmd/mtmd-audio.cpp

@@ -560,7 +560,7 @@ bool mtmd_audio_preprocessor_whisper::preprocess(const float *                 s
     for (size_t off = 0; off < (size_t) out_full.n_len; off += frames_per_chunk) {
         int n_len = std::min(frames_per_chunk, (size_t) out_full.n_len - off);
         if ((size_t) n_len < frames_per_chunk) {
-            break;  // last uncomplete chunk will always be a padded chunk, safe to ignore
+            break;  // last incomplete chunk will always be a padded chunk, safe to ignore
         }
 
         mtmd_audio_mel out_chunk;