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# Copyright (c) 2023-2024, NVIDIA CORPORATION. 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 collections import namedtuple
from typing import Optional, List, Union
import torch
from transformers import PretrainedConfig, PreTrainedModel
from .mamba_vision import *
from timm.models import create_model, load_checkpoint
class MambaVisionConfig(PretrainedConfig):
def __init__(
self,
args: Optional[dict] = None,
**kwargs,
):
self.args = args
super().__init__(**kwargs)
class MambaVisionModel(PreTrainedModel):
"""Pretrained Hugging Face model for MambaVision.
This class inherits from PreTrainedModel, which provides
HuggingFace's functionality for loading and saving models.
"""
config_class = MambaVisionConfig
def __init__(self, config):
super().__init__(config)
MambaVisionArgs = namedtuple("MambaVisionArgs", config.args.keys())
args = MambaVisionArgs(**config.args)
self.config = config
self.model = create_model(args.model)
def forward(self, x: torch.Tensor):
return self.model.forward(x)
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