first

SenseNova-SI-main/sensenova_si/model.py

+import os
+from abc import ABC, abstractmethod
+from pathlib import Path
+from typing import Any
+
+import yaml
+
+
+class Model(ABC):
+    def __init__(
+        self, generation_config: dict[str, Any] | str | os.PathLike | None = None
+    ):
+        if generation_config is None:
+            generation_config = Path(__file__).parents[1] / "config" / "default.yaml"
+        if isinstance(generation_config, str | os.PathLike):
+            with open(generation_config, "r") as f:
+                self.default_generation_config = yaml.safe_load(f).get(
+                    "default_generation_config", {}
+                )
+        elif isinstance(generation_config, dict):
+            self.default_generation_config = generation_config.copy()
+        else:
+            raise ValueError(f"Invalid generation config: {generation_config}")
+
+    @abstractmethod
+    def generate(self, question: str, images: list[str] | None = None, **kwargs) -> str:
+        raise NotImplementedError

SenseNova-SI-main/training/bagel/data/__init__.py

+# Copyright 2025 Bytedance Ltd. and/or its affiliates.
+# SPDX-License-Identifier: Apache-2.0

SenseNova-SI-main/training/bagel/data/configs/sensenova_si_800K.yaml

+sensenova_si_800K:
+  dataset_names:
+  - sensenova_si_800K
+  image_transform_args:
+    image_stride: 14
+    max_image_size: 980
+    min_image_size: 378
+    max_pixels: 2_007_040
+  frame_sampler_args:
+    max_num_frames: 12
+    min_num_frames: 8
+  is_mandatory: true
+  shuffle_lines: True
+  shuffle_seed: 0
+  num_used_data:
+  - 832132
+  weight: 1