# 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. """Default config for cosmos/tokenizer project.""" from typing import Any, List import attrs from cosmos_predict1.tokenizer.training.configs.base.model import DefaultModelConfig from cosmos_predict1.tokenizer.training.configs.registry import register_configs from cosmos_predict1.tokenizer.training.trainer import TokenizerTrainer from cosmos_predict1.utils import config from cosmos_predict1.utils.config_helper import import_all_modules_from_package @attrs.define(slots=False) class Config(config.Config): defaults: List[Any] = attrs.field( factory=lambda: [ "_self_", {"data_train": "mock_video720"}, {"data_val": "mock_video720"}, {"optimizer": "fused_adam"}, {"scheduler": "warmup"}, {"network": "continuous_factorized_video"}, {"loss": "video"}, {"metric": "reconstruction"}, {"checkpoint": "local"}, {"callbacks": "basic"}, {"experiment": None}, ] ) def make_config(): c = Config( model=DefaultModelConfig, optimizer=None, scheduler=None, dataloader_train=None, dataloader_val=None, checkpoint=None, ) c.job.project = "posttraining" c.job.group = "debug" c.job.name = "default_${now:%Y-%m-%d}_${now:%H-%M-%S}" c.trainer.type = TokenizerTrainer c.trainer.run_validation = True c.trainer.seed = 1234 c.trainer.max_iter = 10_000_000 c.trainer.validation_iter = 5000 c.trainer.max_val_iter = 1 c.trainer.logging_iter = 100 c.trainer.callbacks = None c.trainer.ddp.static_graph = True c.trainer.ddp.find_unused_parameters = False register_configs() # experiment config are defined in the experiment folder # call import_all_modules_from_package to register them import_all_modules_from_package("cosmos_predict1.tokenizer.training.configs.experiments") return c