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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.
from typing import Any, List
import attrs
from cosmos_predict1.diffusion.training.config.base.model import DefaultModelConfig
from cosmos_predict1.diffusion.training.config.text2world.registry import (
register_configs as register_configs_text2world,
)
from cosmos_predict1.diffusion.training.config.video2world.registry import (
register_configs as register_configs_video2world,
)
from cosmos_predict1.diffusion.training.config.video2world_action.registry import (
register_configs as register_configs_video2world_action,
)
from cosmos_predict1.diffusion.training.config.video2world_instruction.registry import (
register_configs as register_configs_video2world_instruction,
)
from cosmos_predict1.diffusion.training.models.model import DiffusionModel
from cosmos_predict1.utils import config
from cosmos_predict1.utils.config_helper import import_all_modules_from_package
from cosmos_predict1.utils.lazy_config import PLACEHOLDER
from cosmos_predict1.utils.lazy_config import LazyCall as L
from cosmos_predict1.utils.lazy_config import LazyDict
from cosmos_predict1.utils.trainer import Trainer
@attrs.define(slots=False)
class Config(config.Config):
# default config groups that will be used unless overwritten
# see config groups in registry.py
defaults: List[Any] = attrs.field(
factory=lambda: [
"_self_",
{"data_train": None},
{"data_val": None},
{"optimizer": "fusedadamw"},
{"scheduler": "lambdalinear"},
{"callbacks": None},
{"net": None},
{"conditioner": "add_fps_image_size_padding_mask"},
{"fsdp": None},
{"ema": "power"},
{"vae": "vae1"},
{"checkpoint": "pbss"},
{"ckpt_klass": "fsdp"},
# the list is with order, we need global experiment to be the last one
{"experiment": None},
]
)
model_obj: LazyDict = L(DiffusionModel)(
config=PLACEHOLDER,
)
def make_config():
c = Config(
model=DefaultModelConfig(),
optimizer=None,
scheduler=None,
dataloader_train=None,
dataloader_val=None,
)
# Specifying values through instances of attrs
c.job.project = "cosmos_predict1"
c.job.group = "debug"
c.job.name = "delete_${now:%Y-%m-%d}_${now:%H-%M-%S}"
c.trainer.type = Trainer
c.trainer.max_iter = 400_000
c.trainer.logging_iter = 10
c.trainer.validation_iter = 100
c.trainer.run_validation = False
c.trainer.callbacks = None
c.checkpoint = None
# Call this function to register config groups.
register_configs_text2world()
register_configs_video2world()
register_configs_video2world_instruction()
register_configs_video2world_action()
# experiment config are defined in the experiment folder
# call import_all_modules_from_package to register them
import_all_modules_from_package("cosmos_predict1.diffusion.training.config.text2world", reload=True)
import_all_modules_from_package("cosmos_predict1.diffusion.training.config.video2world", reload=True)
import_all_modules_from_package("cosmos_predict1.diffusion.training.config.video2world_instruction", reload=True)
import_all_modules_from_package("cosmos_predict1.diffusion.training.config.video2world_action", reload=True)
return c
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