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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.
import torch
from torch.utils.data import DataLoader
from cosmos_predict1.tokenizer.training.datasets.mock_dataset import CombinedDictDataset, LambdaDataset
from cosmos_predict1.tokenizer.training.datasets.utils import VIDEO_KEY, VIDEO_VAL_CROP_SIZE_INFO, get_crop_size_info
from cosmos_predict1.utils import log
from cosmos_predict1.utils.lazy_config import LazyCall as L
from cosmos_predict1.utils.lazy_config import LazyDict
_IMAGE_ASPECT_RATIO = "1,1"
_VIDEO_ASPECT_RATIO = "16,9"
def get_video_dataset(
is_train: bool,
resolution: str,
crop_height: int,
num_video_frames: int,
):
if is_train:
crop_sizes = get_crop_size_info(crop_height)
log.info(
f"[video] training num_frames={num_video_frames}, crop_height={crop_height} and crop_sizes: {crop_sizes}."
)
else:
if crop_height is None:
crop_sizes = VIDEO_VAL_CROP_SIZE_INFO[resolution]
else:
crop_sizes = get_crop_size_info(crop_height)
log.info(f"[video] validation num_frames={num_video_frames}, crop_sizes: {crop_sizes}")
h = crop_sizes[_VIDEO_ASPECT_RATIO][1]
w = crop_sizes[_VIDEO_ASPECT_RATIO][0]
def video_fn():
return 2 * torch.rand(3, num_video_frames, h, w) - 1
return CombinedDictDataset(
**{
VIDEO_KEY: LambdaDataset(video_fn),
}
)
def get_mock_video_dataloader(
batch_size: int, is_train: bool = True, num_video_frames: int = 9, resolution: str = "720", crop_height: int = 128
) -> LazyDict:
"""A function to get mock video dataloader.
Args:
batch_size: The batch size.
num_video_frames: The number of video frames.
resolution: The resolution. Defaults to "1024".
Returns:
LazyDict: A LazyDict object specifying the video dataloader.
"""
if resolution not in VIDEO_VAL_CROP_SIZE_INFO:
resolution = "720"
return L(DataLoader)(
dataset=L(get_video_dataset)(
is_train=is_train,
resolution=resolution,
crop_height=crop_height,
num_video_frames=num_video_frames,
),
batch_size=batch_size,
shuffle=False,
num_workers=8,
)
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