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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 megatron.core import parallel_state
from torch.utils.data import DataLoader, DistributedSampler
from cosmos_predict1.autoregressive.configs.base.dataset import VideoDatasetConfig
from cosmos_predict1.autoregressive.datasets.video_dataset import VideoDataset
from cosmos_predict1.utils import log
from cosmos_predict1.utils.lazy_config import LazyCall as L
DATALOADER_OPTIONS = {}
def get_sampler(dataset):
return DistributedSampler(
dataset,
num_replicas=parallel_state.get_data_parallel_world_size(),
rank=parallel_state.get_data_parallel_rank(),
shuffle=True,
seed=0,
)
def dataloader_register(key):
log.info(f"registering dataloader {key}...")
def decorator(func):
DATALOADER_OPTIONS[key] = func
return func
return decorator
@dataloader_register("tealrobot_video")
def get_tealrobot_video(
batch_size: int = 1,
dataset_dir: str = "datasets/cosmos_nemo_assets/videos/",
sequence_interval: int = 1,
num_frames: int = 33,
video_size: list[int, int] = [640, 848],
start_frame_interval: int = 1,
):
dataset = L(VideoDataset)(
config=VideoDatasetConfig(
dataset_dir=dataset_dir,
sequence_interval=sequence_interval,
num_frames=num_frames,
video_size=video_size,
start_frame_interval=start_frame_interval,
)
)
return L(DataLoader)(
dataset=dataset,
sampler=L(get_sampler)(dataset=dataset),
batch_size=batch_size,
drop_last=True,
pin_memory=True,
num_workers=8,
)
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