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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 typing import Dict, List, Optional
import attrs
import torch
from .conditioner import BaseConditionEntry, TextAttr, VideoConditioner, VideoExtendConditioner
from .lazy_config_init import LazyCall as L
from .lazy_config_init import LazyDict
@attrs.define(slots=False)
class TextConfig:
obj: LazyDict = L(TextAttr)() # No arguments
dropout_rate: float = 0.2
input_keys: List[str] = attrs.field(factory=lambda: ["t5_text_embeddings", "t5_text_mask"])
class BooleanFlag(BaseConditionEntry):
def __init__(self, output_key: Optional[str] = None):
super().__init__()
self.output_key = output_key
def forward(self, *args, **kwargs) -> Dict[str, torch.Tensor]:
del args, kwargs
key = self.output_key if self.output_key else self.input_key
return {key: self.flag}
def random_dropout_input(
self, in_tensor: torch.Tensor, dropout_rate: Optional[float] = None, key: Optional[str] = None
) -> torch.Tensor:
del key
dropout_rate = dropout_rate if dropout_rate is not None else self.dropout_rate
self.flag = torch.bernoulli((1.0 - dropout_rate) * torch.ones(1)).bool().to(device=in_tensor.device)
return in_tensor
class ReMapkey(BaseConditionEntry):
def __init__(self, output_key: Optional[str] = None, dtype: Optional[str] = None):
super().__init__()
self.output_key = output_key
self.dtype = {
None: None,
"float": torch.float32,
"bfloat16": torch.bfloat16,
"half": torch.float16,
"float16": torch.float16,
"int": torch.int32,
"long": torch.int64,
}[dtype]
def forward(self, element: torch.Tensor) -> Dict[str, torch.Tensor]:
key = self.output_key if self.output_key else self.input_key
if isinstance(element, torch.Tensor):
element = element.to(dtype=self.dtype)
return {key: element}
@attrs.define(slots=False)
class FPSConfig:
"""
Remap the key from the input dictionary to the output dictionary. For `fps`.
"""
obj: LazyDict = L(ReMapkey)(output_key="fps", dtype=None)
dropout_rate: float = 0.0
input_key: str = "fps"
@attrs.define(slots=False)
class PaddingMaskConfig:
"""
Remap the key from the input dictionary to the output dictionary. For `padding_mask`.
"""
obj: LazyDict = L(ReMapkey)(output_key="padding_mask", dtype=None)
dropout_rate: float = 0.0
input_key: str = "padding_mask"
@attrs.define(slots=False)
class ImageSizeConfig:
"""
Remap the key from the input dictionary to the output dictionary. For `image_size`.
"""
obj: LazyDict = L(ReMapkey)(output_key="image_size", dtype=None)
dropout_rate: float = 0.0
input_key: str = "image_size"
@attrs.define(slots=False)
class NumFramesConfig:
"""
Remap the key from the input dictionary to the output dictionary. For `num_frames`.
"""
obj: LazyDict = L(ReMapkey)(output_key="num_frames", dtype=None)
dropout_rate: float = 0.0
input_key: str = "num_frames"
@attrs.define(slots=False)
class VideoCondBoolConfig:
obj: LazyDict = L(BooleanFlag)(output_key="video_cond_bool")
dropout_rate: float = 0.2
input_key: str = "fps" # This is a placeholder, we never use this value
# Config below are for long video generation only
# Sample PPP... from IPPP... sequence
sample_tokens_start_from_p_or_i: bool = False
@attrs.define(slots=False)
class LatentConditionConfig:
"""
Remap the key from the input dictionary to the output dictionary. For `latent condition`.
"""
obj: LazyDict = L(ReMapkey)(output_key="latent_condition", dtype=None)
dropout_rate: float = 0.0
input_key: str = "latent_condition"
@attrs.define(slots=False)
class LatentConditionSigmaConfig:
"""
Remap the key from the input dictionary to the output dictionary. For `latent condition`.
"""
obj: LazyDict = L(ReMapkey)(output_key="latent_condition_sigma", dtype=None)
dropout_rate: float = 0.0
input_key: str = "latent_condition_sigma"
BaseVideoConditionerConfig: LazyDict = L(VideoConditioner)(
text=TextConfig(),
)
VideoConditionerFpsSizePaddingConfig: LazyDict = L(VideoConditioner)(
text=TextConfig(),
fps=FPSConfig(),
num_frames=NumFramesConfig(),
image_size=ImageSizeConfig(),
padding_mask=PaddingMaskConfig(),
)
VideoExtendConditionerConfig: LazyDict = L(VideoExtendConditioner)(
text=TextConfig(),
fps=FPSConfig(),
num_frames=NumFramesConfig(),
image_size=ImageSizeConfig(),
padding_mask=PaddingMaskConfig(),
video_cond_bool=VideoCondBoolConfig(),
)
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