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Runtime error
| save_path: saved_standard_challenging_context32_nocond_cont_cont_all_cont_eval | |
| model: | |
| base_learning_rate: 8.0e-05 | |
| target: ldm.models.diffusion.ddpm.LatentDiffusion | |
| params: | |
| linear_start: 0.0015 | |
| linear_end: 0.0195 | |
| num_timesteps_cond: 1 | |
| log_every_t: 200 | |
| timesteps: 1000 | |
| first_stage_key: image | |
| cond_stage_key: action_ | |
| scheduler_sampling_rate: 0.0 | |
| hybrid_key: c_concat | |
| image_size: [64, 48] | |
| channels: 3 | |
| cond_stage_trainable: false | |
| conditioning_key: hybrid | |
| monitor: val/loss_simple_ema | |
| unet_config: | |
| target: ldm.modules.diffusionmodules.openaimodel.UNetModel | |
| params: | |
| image_size: [64, 48] | |
| in_channels: 48 | |
| out_channels: 16 | |
| model_channels: 512 | |
| attention_resolutions: [] | |
| num_res_blocks: 2 | |
| channel_mult: | |
| - 1 | |
| - 2 | |
| num_head_channels: 32 | |
| use_spatial_transformer: false | |
| transformer_depth: 1 | |
| temporal_encoder_config: | |
| target: ldm.modules.encoders.temporal_encoder.TemporalEncoder | |
| params: | |
| input_channels: 16 | |
| hidden_size: 4096 | |
| num_layers: 1 | |
| dropout: 0.1 | |
| output_channels: 32 | |
| output_height: 48 | |
| output_width: 64 | |
| first_stage_config: | |
| target: ldm.models.autoencoder.AutoencoderKL | |
| params: | |
| embed_dim: 16 | |
| monitor: val/rec_loss | |
| ddconfig: | |
| double_z: true | |
| z_channels: 16 | |
| resolution: 256 | |
| in_channels: 3 | |
| out_ch: 3 | |
| ch: 128 | |
| ch_mult: | |
| - 1 | |
| - 2 | |
| - 4 | |
| - 4 | |
| num_res_blocks: 2 | |
| attn_resolutions: [] | |
| dropout: 0.0 | |
| lossconfig: | |
| target: torch.nn.Identity | |
| cond_stage_config: __is_unconditional__ | |
| data: | |
| target: data.data_processing.datasets.DataModule | |
| params: | |
| batch_size: 8 | |
| num_workers: 1 | |
| wrap: false | |
| shuffle: True | |
| drop_last: True | |
| pin_memory: True | |
| prefetch_factor: 2 | |
| persistent_workers: True | |
| train: | |
| target: data.data_processing.datasets.ActionsData | |
| params: | |
| data_csv_path: desktop_sequences_filtered_with_desktop_1.5k.challenging.train.target_frames.csv | |
| normalization: standard | |
| context_length: 32 | |
| #validation: | |
| # target: data.data_processing.datasets.ActionsData | |
| # params: | |
| lightning: | |
| trainer: | |
| benchmark: False | |
| max_epochs: 6400 | |
| limit_val_batches: 0 | |
| accelerator: gpu | |
| gpus: 1 | |
| accumulate_grad_batches: 999999 | |
| gradient_clip_val: 1 | |
| checkpoint_callback: True | |