# 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 cosmos_predict1.diffusion.training.functional.lr_scheduler import LambdaLinearScheduler from cosmos_predict1.diffusion.training.utils.optim_instantiate import get_base_optimizer 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 FusedAdamWConfig: LazyDict = L(get_base_optimizer)( model=PLACEHOLDER, lr=1e-4, weight_decay=0.3, betas=[0.9, 0.999], optim_type="fusedadam", eps=1e-8, sharding=False, master_weights=True, capturable=True, ) LambdaLinearSchedulerConfig: LazyDict = L(LambdaLinearScheduler)( warm_up_steps=[1000], cycle_lengths=[10000000000000], f_start=[1.0e-6], f_max=[1.0], f_min=[1.0], )