Download GeometryForcing/experiments/video_latent_learning.py from BonanDing/worldmem-baseline-evals: direct link, hf CLI and curl.
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https://huggingface.co/BonanDing/worldmem-baseline-evals/resolve/181f4402aeeef8bd63844fcf2146162a5cc5f1b3/GeometryForcing/experiments/video_latent_learning.py
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hf download hf://BonanDing/worldmem-baseline-evals@181f4402aeeef8bd63844fcf2146162a5cc5f1b3/GeometryForcing/experiments/video_latent_learning.py
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curl -L -o video_latent_learning.py https://huggingface.co/BonanDing/worldmem-baseline-evals/resolve/181f4402aeeef8bd63844fcf2146162a5cc5f1b3/GeometryForcing/experiments/video_latent_learning.py
762 Bytes
| from datasets.video import ( | |
| MinecraftAdvancedVideoDataset, | |
| Kinetics600AdvancedVideoDataset, | |
| ) | |
| from algorithms.vae import ImageVAETrainer, VideoVAETrainer | |
| from .base_exp import BaseLightningExperiment | |
| from .data_modules.utils import _data_module_cls | |
| class VideoLatentLearningExperiment(BaseLightningExperiment): | |
| """ | |
| An experiment for training & validating the first stage model (e.g. VAE) | |
| that learns the latent representation of the data | |
| """ | |
| compatible_algorithms = dict( | |
| image_vae=ImageVAETrainer, | |
| video_vae=VideoVAETrainer, | |
| ) | |
| compatible_datasets = dict( | |
| minecraft=MinecraftAdvancedVideoDataset, | |
| kinetics_600=Kinetics600AdvancedVideoDataset, | |
| ) | |
| data_module_cls = _data_module_cls | |