Feature lenghts are sometimes used to identify the data/task (i.e. use a different feature converter depending on which lenghts are expected), for example DecoderFeatureConverter. This works great in training but during evaluation the feature lengths used are the ones present in the dataset not the ones set in the config. This CL makes the task_feature_lenghts to be passed instead of the inferred feature_lengths during evaluation. #228
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…e a different feature converter depending on which lenghts are expected), for example DecoderFeatureConverter. This works great in training but during evaluation the feature lengths used are the ones present in the dataset not the ones set in the config. This CL makes the task_feature_lenghts to be passed instead of the inferred feature_lengths during evaluation. PiperOrigin-RevId: 443334142
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Feature lenghts are sometimes used to identify the data/task (i.e. use a different feature converter depending on which lenghts are expected), for example DecoderFeatureConverter. This works great in training but during evaluation the feature lengths used are the ones present in the dataset not the ones set in the config. This CL makes the task_feature_lenghts to be passed instead of the inferred feature_lengths during evaluation.