"""
# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""

from __future__ import annotations

from paddleformers.transformers.configuration_utils import PretrainedConfig

__all__ = [
    "Qwen3VisionTransformerConfig",
]


class Qwen3VisionTransformerConfig(PretrainedConfig):
    r"""Configuration for the Qwen3 vision encoder used in Qwen3-VL."""

    model_type = "qwen3_vision_transformer"

    def __init__(
        self,
        depth: int = 27,
        hidden_size: int = 1152,
        hidden_act: str = "gelu_tanh",
        intermediate_size: int = 4304,
        num_heads: int = 16,
        in_channels: int = 3,
        patch_size: int = 16,
        spatial_merge_size: int = 2,
        temporal_patch_size: int = 2,
        out_hidden_size: int = 3584,
        num_position_embeddings: int = 2304,
        deepstack_visual_indexes: list[int] | None = None,
        initializer_range: float = 0.02,
        tokens_per_second: int = 2,
        **kwargs,
    ) -> None:
        super().__init__(**kwargs)

        self.depth = depth
        self.hidden_size = hidden_size
        self.intermediate_size = intermediate_size
        self.hidden_act = hidden_act
        self.num_heads = num_heads
        self.in_channels = in_channels
        self.patch_size = patch_size
        self.spatial_merge_size = spatial_merge_size
        self.temporal_patch_size = temporal_patch_size
        self.out_hidden_size = out_hidden_size
        self.num_position_embeddings = num_position_embeddings
        self.initializer_range = initializer_range
        self.deepstack_visual_indexes = list(deepstack_visual_indexes or [])
        self.tokens_per_second = tokens_per_second