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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.
"""Config settings for cosmos/tokenizer (basic image and video setting)"""
from hydra.core.config_store import ConfigStore
from cosmos_predict1.utils.lazy_config import LazyDict
CAUSAL_VIDEO_BASIC: LazyDict = LazyDict(
dict(
defaults=[
{"override /network": "continuous_factorized_video"},
{"override /data_train": "mock_video720"},
{"override /data_val": "mock_video720"},
{"override /loss": "video"},
{"override /optimizer": "fused_adam"},
{"override /callbacks": ["basic"]},
"_self_",
],
model=dict(
config=dict(
loss=dict(
config=dict(
perceptual=dict(
config=dict(
lpips_boundaries=[0],
lpips_values=[0.1],
gram_enabled=False,
gram_boundaries=[0],
)
),
video_consistency=dict(
config=dict(
enabled=False,
boundaries=[0],
values=[1.0],
num_frames=32,
step=8,
)
),
flow=dict(
config=dict(
enabled=False,
boundaries=[1_000_000],
values=[0.0, 0.01],
scale=2,
dtype="bfloat16",
checkpoint_activations=False,
)
),
)
)
)
),
dataloader_train=dict(
dataset=dict(
crop_height=256,
num_video_frames=49,
),
batch_size=1,
),
dataloader_val=dict(
dataset=dict(
crop_height=720,
num_video_frames=49,
),
batch_size=1,
),
job=dict(
project="posttraining",
group="tokenizer",
name="basic_${now:%Y-%m-%d}_${now:%H-%M-%S}",
),
checkpoint=dict(load_path=None, jit=dict(input_shape=[1, 3, 17, 512, 512])),
)
)
cs = ConfigStore.instance()
cs.store(group="experiment", package="_global_", name="video_basic", node=CAUSAL_VIDEO_BASIC)
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