[MODEL] support qwen3.5 series

mlx_vlm/models/base.py

@@ -6,7 +6,11 @@
 
 import mlx.core as mx
 import mlx.nn as nn
-from mlx_lm.models.base import create_attention_mask, scaled_dot_product_attention
+from mlx_lm.models.base import (
+    create_attention_mask,
+    create_ssm_mask,
+    scaled_dot_product_attention,
+)
 from PIL import Image
 
 

mlx_vlm/models/qwen3_5/__init__.py

@@ -0,0 +1,2 @@
+from .config import ModelConfig, TextConfig, VisionConfig
+from .qwen3_5 import LanguageModel, Model, VisionModel

mlx_vlm/models/qwen3_5/config.py

@@ -0,0 +1,101 @@
+import inspect
+from dataclasses import dataclass, field
+from typing import Dict, List, Optional, Union
+
+from ..base import BaseModelConfig
+from ..qwen3_vl.config import VisionConfig as Qwen3VLVisionConfig
+
+
+@dataclass
+class VisionConfig(Qwen3VLVisionConfig):
+    model_type: str = "qwen3_5"
+
+    def __post_init__(self):
+        if (
+            self.deepstack_visual_indexes is not None
+            and len(self.deepstack_visual_indexes) > 0
+        ):
+            raise ValueError(
+                f"deepstack is disabled for qwen3.5 temporally, but it is set to {self.deepstack_visual_indexes}"
+            )
+        self.deepstack_visual_indexes = []
+
+
+@dataclass
+class TextConfig(BaseModelConfig):
+    model_type: str
+    hidden_size: int
+    intermediate_size: int
+    linear_num_value_heads: int
+    linear_num_key_heads: int
+    linear_key_head_dim: int
+    linear_value_head_dim: int
+    linear_conv_kernel_dim: int
+    num_hidden_layers: int
+    num_attention_heads: int
+    rms_norm_eps: float
+    vocab_size: int
+    num_key_value_heads: int
+    max_position_embeddings: int
+    tie_word_embeddings: bool = False
+    attention_bias: bool = False
+    head_dim: Optional[int] = None
+    rope_parameters: Optional[Dict[str, Union[float, str, bool, List[int]]]] = field(
+        default_factory=lambda: {
+            "type": "default",
+            "mrope_section": [11, 11, 10],
+            "rope_theta": 100000,
+            "partial_rotary_factor": 0.25,
+        }
+    )
+    full_attention_interval: int = 4
+
+    def __post_init__(self):
+        if self.rope_parameters:
+            # Normalize rope_parameters keys (accept both 'rope_type' and 'type')
+            if (
+                "type" not in self.rope_parameters
+                and "rope_type" in self.rope_parameters
+            ):
+                self.rope_parameters["type"] = self.rope_parameters.pop("rope_type")
+
+            required_keys = {
+                "mrope_section",
+                "type",
+                "rope_theta",
+                "partial_rotary_factor",
+            }
+            if not all(key in self.rope_parameters for key in required_keys):
+                raise ValueError(f"rope_parameters must contain keys {required_keys}")
+
+
+@dataclass
+class ModelConfig(BaseModelConfig):
+    text_config: TextConfig
+    vision_config: VisionConfig
+    model_type: str
+    ignore_index: int = -100
+    image_token_id: int = 248056
+    video_token_id: int = 248057
+    image_token_index: Optional[int] = None
+    video_token_index: Optional[int] = None
+    vision_start_token_id: int = 248045
+    vision_end_token_id: int = 248046
+    vocab_size: int = 248320
+    eos_token_id: Optional[List[int]] = None
+
+    def __post_init__(self):
+        if self.image_token_index is None:
+            self.image_token_index = self.image_token_id
+        if self.video_token_index is None:
+            self.video_token_index = self.video_token_id
+
+    @classmethod
+    def from_dict(cls, params):
+        return cls(
+            **{
+                k: v
+                for k, v in params.items()
+                if k in inspect.signature(cls).parameters
+            }
+        )