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# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# 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 dataclasses import dataclass
from typing import Dict, Optional
import torch
from conditioner import BaseVideoCondition, GeneralConditioner
from config_base_conditioner import (
FPSConfig,
ImageSizeConfig,
LatentConditionConfig,
LatentConditionSigmaConfig,
NumFramesConfig,
PaddingMaskConfig,
TextConfig,
)
from lazy_config_init import LazyCall as L
from lazy_config_init import LazyDict
@dataclass
class VideoLatentDiffusionDecoderCondition(BaseVideoCondition):
# latent_condition will concat to the input of network, along channel dim;
# cfg will make latent_condition all zero padding.
latent_condition: Optional[torch.Tensor] = None
latent_condition_sigma: Optional[torch.Tensor] = None
class VideoDiffusionDecoderConditioner(GeneralConditioner):
def forward(
self,
batch: Dict,
override_dropout_rate: Optional[Dict[str, float]] = None,
) -> VideoLatentDiffusionDecoderCondition:
output = super()._forward(batch, override_dropout_rate)
return VideoLatentDiffusionDecoderCondition(**output)
VideoLatentDiffusionDecoderConditionerConfig: LazyDict = L(VideoDiffusionDecoderConditioner)(
text=TextConfig(),
fps=FPSConfig(),
num_frames=NumFramesConfig(),
image_size=ImageSizeConfig(),
padding_mask=PaddingMaskConfig(),
latent_condition=LatentConditionConfig(),
latent_condition_sigma=LatentConditionSigmaConfig(),
)
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