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# ------------------------------------------------------------------------------
# Copyright 2025 2toINF (https://github.com/2toINF)
#
# 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 .configuration_florence2 import Florence2Config
from transformers.configuration_utils import PretrainedConfig
class XVLAConfig(PretrainedConfig):
"""
Configuration class for the **XVLA (Extended Vision-Language-Action)** model.
This configuration defines all submodules of XVLA in a single place:
- The visual-language backbone (Florence2)
- The temporal/action transformer
- The action/proprio setup
"""
model_type = "xvla"
def __init__(
# === Florence backbone ===
self,
florence_config: dict | None = None,
# === Transformer head ===
hidden_size: int = 1024,
depth: int = 24,
num_heads: int = 16,
mlp_ratio: float = 4.0,
num_domains: int = 30,
len_soft_prompts: int = 32,
dim_time: int = 32,
max_len_seq: int = 512,
use_hetero_proj: bool = False,
soft_prompt_length: int = 32,
# === Action & proprio ===
num_actions: int = 30,
action_mode: str = "ee6d",
use_proprio: bool = True,
**kwargs,
):
# Florence2 backbone configuration
if isinstance(florence_config, dict):
self.florence_config = Florence2Config(**florence_config)
elif isinstance(florence_config, Florence2Config):
self.florence_config = florence_config
else:
self.florence_config = Florence2Config()
# Transformer hyperparameters
self.hidden_size = hidden_size
self.depth = depth
self.num_heads = num_heads
self.mlp_ratio = mlp_ratio
self.num_domains = num_domains
self.len_soft_prompts = len_soft_prompts
self.dim_time = dim_time
self.max_len_seq = max_len_seq
self.use_hetero_proj = use_hetero_proj
self.soft_prompt_length = soft_prompt_length
# Action/proprioception settings
self.num_actions = num_actions
self.action_mode = action_mode
self.use_proprio = use_proprio
# Initialize base HF config attributes (e.g. name_or_path)
super().__init__(**kwargs)
# -------------------------------------------------------------------------
# Serialization helpers
# -------------------------------------------------------------------------
def to_dict(self):
"""
Convert this configuration (and its Florence sub-config)
into a fully serializable dictionary for HF save/load.
"""
output = super().to_dict()
output["florence_config"] = self.florence_config.to_dict()
return output
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