# 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. """Metric configurations for the tokenizer model. Support for PSNR or SSIM, there are validation only metrics. """ import attrs from cosmos_predict1.tokenizer.training.metrics import CodeUsageMetric, PSNRMetric, SSIMMetric, TokenizerMetric from cosmos_predict1.utils.lazy_config import LazyCall as L from cosmos_predict1.utils.lazy_config import LazyDict @attrs.define(slots=False) class Metric: # The combined loss function, and its reduction mode. PSNR: LazyDict = L(PSNRMetric)() SSIM: LazyDict = L(SSIMMetric)() @attrs.define(slots=False) class DiscreteTokenizerMetric: # with code usage (perplexity PPL), for discrete tokenizers only PSNR: LazyDict = L(PSNRMetric)() SSIM: LazyDict = L(SSIMMetric)() CodeUsage: LazyDict = L(CodeUsageMetric)(codebook_size=64000) MetricConfig: LazyDict = L(TokenizerMetric)(config=Metric()) DiscreteTokenizerMetricConfig: LazyDict = L(TokenizerMetric)(config=DiscreteTokenizerMetric())