Feature Extraction
Transformers
Safetensors
custom_code
C-RADIO / adaptor_base.py
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# Copyright (c) 2024, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
from argparse import Namespace
from typing import NamedTuple
import torch
from torch import nn
import torch.nn.functional as F
class AdaptorInput(NamedTuple):
images: torch.Tensor
summary: torch.Tensor
features: torch.Tensor
class RadioOutput(NamedTuple):
summary: torch.Tensor
features: torch.Tensor
def to(self, *args, **kwargs):
return RadioOutput(
self.summary.to(*args, **kwargs) if self.summary is not None else None,
self.features.to(*args, **kwargs) if self.features is not None else None,
)
class AdaptorBase(nn.Module):
def forward(self, input: AdaptorInput) -> RadioOutput:
raise NotImplementedError("Subclasses must implement this!")