mtmd: Add DeepSeekOCR 2 Support (#20975)

* mtmd: DeepSeek-OCR 2 support, with multi-tile dynamic resolution

* introduced clip_image_f32::add_viewsep

* address PR review

- drop redundant ggml_cpy ops in both deepseekocr versions build
- drop no-op ggml_cont in build_sam
- assert num_image_tokens deepseekocr2
- view_seperator as (1, n_embd) at conversion (for both versions)
- drop redundant ggml_reshape_2d

* Update tools/mtmd/models/deepseekocr2.cpp

Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>

---------

Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>

conversion/deepseek.py

@@ -16,10 +16,14 @@ from .qwen import QwenModel
 
 @ModelBase.register("DeepseekOCRForCausalLM")
 class DeepseekOCRVisionModel(MmprojModel):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.clip_projector_type = gguf.VisionProjectorType.DEEPSEEKOCR
+
     def set_gguf_parameters(self):
         super().set_gguf_parameters()
         hparams = self.hparams
-        self.gguf_writer.add_clip_projector_type(gguf.VisionProjectorType.DEEPSEEKOCR)
+        self.gguf_writer.add_clip_projector_type(self.clip_projector_type)
         # default values below are taken from HF tranformers code
         self.gguf_writer.add_vision_attention_layernorm_eps(hparams.get("layer_norm_eps", 1e-6))
         self.gguf_writer.add_vision_use_gelu(True)
@@ -49,22 +53,27 @@ class DeepseekOCRVisionModel(MmprojModel):
             raise ValueError("DeepseekOCR model requires 'vision_config' in the model configuration, but it was not found")
 
         vision_config['sam'] = vision_config['width']['sam_vit_b']
-        vision_config.update(vision_config['width']['clip-l-14-224'])
-        vision_config['hidden_size'] = vision_config['width']
-        vision_config['num_heads'] = vision_config['heads']
-        vision_config['intermediate_size'] = vision_config['heads'] * 4
+        if vision_config['width'].get('clip-l-14-224') is not None:
+            vision_config.update(vision_config['width']['clip-l-14-224'])
+        if isinstance(vision_config['width'], int):
+            vision_config['hidden_size'] = vision_config['width']
+        if vision_config.get('heads') is not None:
+            vision_config['num_heads'] = vision_config['heads']
+            vision_config['intermediate_size'] = vision_config['heads'] * 4
 
         return vision_config
 
     def tensor_force_quant(self, name, new_name, bid, n_dims):
-        if ".embeddings." in name or 'pos_embed' in name:
-            return gguf.GGMLQuantizationType.F32
-        if ".rel_pos_h" in name or '.rel_pos_w' in name:
-            return gguf.GGMLQuantizationType.F32
-        if ".neck." in name or ".net_" in name:
-            return gguf.GGMLQuantizationType.F32
+        for nq_name in ('.embeddings.', 'pos_embed', '.rel_pos_h', '.rel_pos_w', '.neck.', '.net_'):
+            if nq_name in name:
+                return gguf.GGMLQuantizationType.F32
         return super().tensor_force_quant(name, new_name, bid, n_dims)
 
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        if name.endswith("view_seperator"):
+            data_torch = data_torch.unsqueeze(0)
+        yield from super().modify_tensors(data_torch, name, bid)
+
     @classmethod
     def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
         name, gen = item
@@ -81,6 +90,33 @@ class DeepseekOCRVisionModel(MmprojModel):
         return super().filter_tensors((name, gen))
 
 
+@ModelBase.register("DeepseekOCR2ForCausalLM")
+class DeepseekOCR2VisionModel(DeepseekOCRVisionModel):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.clip_projector_type = gguf.VisionProjectorType.DEEPSEEKOCR2
+
+    def set_gguf_parameters(self):
+        # the vision tower's qwen2 encoder is built from fixed defaults,
+        # see build_qwen2_decoder_as_encoder() in deepencoderv2.py
+        if self.hparams.get("patch_size") is None:
+            self.hparams["patch_size"] = 16
+        if self.hparams.get("intermediate_size") is None:
+            self.hparams["intermediate_size"] = 4864
+        if self.hparams.get("num_attention_heads") is None:
+            self.hparams["num_attention_heads"] = 14
+        super().set_gguf_parameters()
+        # qwen2 encoder is GQA: 14 Q heads, 2 KV heads
+        self.gguf_writer.add_vision_head_count_kv(2)
+
+    def get_vision_config(self) -> dict[str, Any]:
+        vision_config = super().get_vision_config()
+        vision_config['hidden_size'] = vision_config['width']['qwen2-0-5b']['dim']
+        if vision_config.get('layers') is None:
+            vision_config['layers'] = 24
+        return vision_config
+
+
 @ModelBase.register("DeepseekForCausalLM")
 class DeepseekModel(TextModel):
     model_arch = gguf.MODEL_ARCH.DEEPSEEK
@@ -188,13 +224,21 @@ class DeepseekV2Model(TextModel):
         self.origin_hf_arch = hparams.get('architectures', [None])[0]
 
         # special handling for Deepseek OCR
-        if self.origin_hf_arch == "DeepseekOCRForCausalLM":
+        if self.origin_hf_arch in ("DeepseekOCRForCausalLM", "DeepseekOCR2ForCausalLM"):
             self.model_arch = gguf.MODEL_ARCH.DEEPSEEK2OCR
             self.gguf_writer.arch = gguf.MODEL_ARCH_NAMES[self.model_arch]
             self.gguf_writer.add_architecture()
             # default jinja template
             self.gguf_writer.add_chat_template("{% for m in messages %}{{m['content']}}{% endfor %}")
 
+    @classmethod
+    def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
+        name, _ = item
+        # DeepSeek-OCR vision encoder (SAM + DeepSeek-OCR-2 qwen2 tower)
+        if "sam_model" in name or "qwen2_model" in name:
+            return None
+        return super().filter_tensors(item)
+
     def set_vocab(self):
         try:
             self._set_vocab_gpt2()