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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
import torch
from torch import nn
import torch.nn.functional as F
from .adaptor_base import AdaptorBase, AdaptorInput, RadioOutput
from .adaptor_mlp import create_mlp_from_state, create_mlp_from_config
class GenericAdaptor(AdaptorBase):
def __init__(self, main_config: Namespace, adaptor_config, state, mlp_config=None):
super().__init__()
if state is not None:
self.head_mlp = create_mlp_from_state(main_config.mlp_version, state, 'summary.')
self.feat_mlp = create_mlp_from_state(main_config.mlp_version, state, 'feature.')
else:
assert mlp_config is not None, "Config must not be None if state is None"
self.head_mlp = create_mlp_from_config(
main_config.mlp_version,
mlp_config["summary"]["input_dim"],
mlp_config["summary"]["hidden_dim"],
mlp_config["summary"]["output_dim"],
mlp_config["summary"]["num_inner"],
)
self.feat_mlp = create_mlp_from_config(
main_config.mlp_version,
mlp_config["feature"]["input_dim"],
mlp_config["feature"]["hidden_dim"],
mlp_config["feature"]["output_dim"],
mlp_config["feature"]["num_inner"],
)
def forward(self, input: AdaptorInput) -> RadioOutput:
summary = self.head_mlp(input.summary)
feat = self.feat_mlp(input.features)
return RadioOutput(summary, feat)
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