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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_transfer1.checkpointer.ema_fsdp_checkpointer import CheckpointConfig
from cosmos_transfer1.diffusion.config.training.registry_extra import register_configs
from cosmos_transfer1.diffusion.config.transfer.model import CtrlModelConfig
from cosmos_transfer1.diffusion.training.models.model_ctrl import VideoDiffusionModelWithCtrl
from cosmos_transfer1.utils import config
from cosmos_transfer1.utils.config_helper import import_all_modules_from_package
from cosmos_transfer1.utils.lazy_config import PLACEHOLDER
from cosmos_transfer1.utils.lazy_config import LazyCall as L
from cosmos_transfer1.utils.lazy_config import LazyDict
from cosmos_transfer1.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},
{"net_ctrl": None},
{"hint_key": "control_input_edge"},
{"conditioner": "ctrlnet_add_fps_image_size_padding_mask"},
{"pixel_corruptor": None},
{"fsdp": None},
{"ema": "power"},
{"checkpoint": "local"},
{"ckpt_klass": "multi_rank"},
{"tokenizer": "vae1"},
# the list is with order, we need global experiment to be the last one
{"experiment": None},
]
)
model_obj: LazyDict = L(VideoDiffusionModelWithCtrl)(
config=PLACEHOLDER,
)
checkpoint: CheckpointConfig = attrs.field(factory=CheckpointConfig)
def make_config():
c = Config(
model=CtrlModelConfig(),
optimizer=None,
scheduler=None,
dataloader_train=None,
dataloader_val=None,
)
c.job.project = "cosmos_transfer1"
c.job.group = "debug"
c.job.name = "delete_${now:%Y-%m-%d}_${now:%H-%M-%S}"
c.trainer.type = Trainer
# c.trainer.straggler_detection.enabled = False
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
register_configs()
import_all_modules_from_package("cosmos_transfer1.diffusion.config.training.experiment", reload=True)
return c
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