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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 omegaconf
from .pretrained_vae import JITVAE, JointImageVideoSharedJITTokenizer, VideoJITTokenizer
from .lazy_config_init import LazyCall as L
TOKENIZER_OPTIONS = {}
def tokenizer_register(key):
def decorator(func):
TOKENIZER_OPTIONS[key] = func
return func
return decorator
@tokenizer_register("cosmos_diffusion_tokenizer_comp8x8x8")
def get_cosmos_diffusion_tokenizer_comp8x8x8(resolution: str, chunk_duration: int) -> omegaconf.dictconfig.DictConfig:
assert resolution in ["720"]
pixel_chunk_duration = chunk_duration
temporal_compression_factor = 8
spatial_compression_factor = 8
return L(JointImageVideoSharedJITTokenizer)(
video_vae=L(VideoJITTokenizer)(
name="cosmos_1_0_diffusion_tokenizer",
latent_ch=16,
is_bf16=True,
pixel_chunk_duration=pixel_chunk_duration,
temporal_compression_factor=temporal_compression_factor,
spatial_compression_factor=spatial_compression_factor,
spatial_resolution=resolution,
),
image_vae=L(JITVAE)(
name="cosmos_1_0_diffusion_tokenizer",
latent_ch=16,
is_image=False,
is_bf16=True,
),
name="cosmos_1_0_diffusion_tokenizer",
latent_ch=16,
)
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