# 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, )