llama : DeepSeek V2/V3 MLA implementation (#12801)

* Merged using squash to remove all noise commit messages

* Force flash attention off for `LLM_ARCH_DEEPSEEK2` - embedding too large

* Removed 3 conts (2x RoPE and 1x RMS-norm)

* Changed to use `<cmath>` instead of `<math.h>`

* Reverted removal of the 3 conts

* Used `reshape` in `llm_graph_context::build_attn_mha()`

* Use `k_pe = ggml_reshape`

* Removed the 3 conts again

* Removed the 3D views of `wk_b` and `wv_b`, and just save and 3D in GGUF

* Removed MQA optimisation from `build_attn_mha()` as no gains now

* Simplified `is_mla` branch in `llm_build_deepseek2()`

* Removed `build_attn_mla` and added `nullptr` to all `build_atnn` calls

* Fixed call to `build_attn` in `llm_build_t5_enc`

gguf-py/gguf/tensor_mapping.py

@@ -677,6 +677,14 @@ class TensorNameMap:
             "model.layers.{bid}.self_attn.kv_b_proj", # deepseek2
         ),
 
+        MODEL_TENSOR.ATTN_K_B: (
+            "model.layers.{bid}.self_attn.k_b_proj",  # deepseek2
+        ),
+
+        MODEL_TENSOR.ATTN_V_B: (
+            "model.layers.{bid}.self_attn.v_b_proj",  # deepseek2
+        ),
+
         MODEL_TENSOR.ATTN_Q_A_NORM: (
             "model.layers.{bid}.self_attn.q_a_layernorm", # deepseek2
         ),