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Initial commit for new Space - pre-built Docker image
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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.
"""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())