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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.
"""dataloader config options
Available dataloader options:
image_loader_basic
video_loader_basic
joint_image_video_loader_basic
"""
from torch.utils.data import DataLoader
from cosmos_predict1.tokenizer.training.configs.base.mock_data import get_mock_video_dataloader
from cosmos_predict1.tokenizer.training.datasets.dataset_provider import dataset_entry
from cosmos_predict1.utils.lazy_config import LazyCall
DATALOADER_OPTIONS = {}
def dataloader_register(key):
def decorator(func):
DATALOADER_OPTIONS[key] = func
return func
return decorator
@dataloader_register("video_loader_basic")
def get_video_dataloader(
dataset_name,
is_train,
batch_size=1,
num_video_frames=25,
resolution="720",
crop_height=128,
num_workers=8,
):
if dataset_name.startswith("mock"):
return get_mock_video_dataloader(
batch_size=batch_size,
is_train=is_train,
num_video_frames=num_video_frames,
resolution=resolution,
crop_height=crop_height,
)
return LazyCall(DataLoader)(
dataset=LazyCall(dataset_entry)(
dataset_name=dataset_name,
dataset_type="video",
is_train=is_train,
resolution=resolution,
crop_height=crop_height,
num_video_frames=num_video_frames,
),
batch_size=batch_size, # 2
num_workers=num_workers, # 8
prefetch_factor=2,
shuffle=None, # do we need this?
sampler=None,
persistent_workers=False,
pin_memory=True,
)
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