llama : add support for EmbeddingGemma 300m (#15798)

This commit add support for the EmbeddingGemma 300m. This model supports
sliding window attention (SWA) and a new swq_type is introduced to
support symmetric SWA masking.

This commit also extracts the code from the function
llama_is_masked_swa in llama-impl.h, so that the logic can be shared
by both llm_graph_input_attn_no_cache::set_input and
llama_kv_cache::set_input_kq_mask.

With this commit the EmbeddingGemma 300m model can be converted to
to GGUF and used with llama.cpp.

Once the model has been uploaded to HuggingFace it can be used like
this:
```console
./build/bin/llama-cli -hf ggml-org/embeddinggemma-300m-GGUF:Q8_0
```

convert_hf_to_gguf.py

@@ -5122,6 +5122,15 @@ class Gemma3Model(TextModel):
         return [(self.map_tensor_name(name), data_torch)]
 
 
+@ModelBase.register("Gemma3TextModel")
+class EmbeddingGemma(Gemma3Model):
+    model_arch = gguf.MODEL_ARCH.GEMMA_EMBEDDING
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        self._try_set_pooling_type()
+
+
 @ModelBase.register("Gemma3ForConditionalGeneration")
 class Gemma3VisionModel(MmprojModel):
     def set_gguf_parameters(self):