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Runtime error
| model: | |
| base_learning_rate: 2.0e-05 | |
| target: customnet.customnet.CustomNet | |
| params: | |
| linear_start: 0.00085 | |
| linear_end: 0.0120 | |
| num_timesteps_cond: 1 | |
| log_every_t: 200 | |
| timesteps: 1000 | |
| first_stage_key: "image_target" | |
| cond_stage_key: "image_cond" | |
| image_size: 32 | |
| channels: 4 | |
| cond_stage_trainable: false # Note: different from the one we trained before | |
| conditioning_key: hybrid | |
| monitor: val/loss_simple_ema | |
| scale_factor: 0.18215 | |
| use_ema: false | |
| use_cond_concat: true | |
| use_bbox_mask: false | |
| use_bg_inpainting: false | |
| learning_rate_scale: 10 | |
| ucg_training: | |
| txt: 0.15 | |
| sd_15_ckpt: #"v1-5-pruned-emaonly.ckpt" | |
| unet_config: | |
| target: customnet.openaimodel.UNetModel | |
| params: | |
| image_size: 32 # unused | |
| in_channels: 8 | |
| out_channels: 4 | |
| model_channels: 320 | |
| attention_resolutions: [ 4, 2, 1 ] | |
| num_res_blocks: 2 | |
| channel_mult: [ 1, 2, 4, 4 ] | |
| num_heads: 8 | |
| use_spatial_transformer: True | |
| transformer_depth: 1 | |
| context_dim: 768 | |
| use_checkpoint: True | |
| legacy: False | |
| first_stage_config: | |
| target: ldm.models.autoencoder.AutoencoderKL | |
| params: | |
| embed_dim: 4 | |
| monitor: val/rec_loss | |
| ddconfig: | |
| double_z: true | |
| z_channels: 4 | |
| 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: | |
| target: ldm.modules.encoders.modules.FrozenCLIPImageEmbedder | |
| text_encoder_config: | |
| target: ldm.modules.encoders.modules.FrozenCLIPEmbedder | |
| params: | |
| version: openai/clip-vit-large-patch14 | |
| ## this is a template dataset | |
| train_data: | |
| target: data.dataset.Dataset | |
| params: | |
| image_size: 256 | |
| root: examples/dataset/ | |
| train_dataloader: | |
| batch_size: 12 | |
| num_workers: 8 | |
| lightning: | |
| find_unused_parameters: false | |
| metrics_over_trainsteps_checkpoint: True | |
| modelcheckpoint: | |
| params: | |
| every_n_train_steps: 10000 | |
| save_top_k: -1 | |
| monitor: null | |
| callbacks: | |
| image_logger: | |
| target: main.ImageLogger | |
| params: | |
| batch_frequency: 2500 | |
| max_images: 32 | |
| increase_log_steps: False | |
| log_first_step: True | |
| log_images_kwargs: | |
| use_ema_scope: False | |
| inpaint: False | |
| plot_progressive_rows: False | |
| plot_diffusion_rows: False | |
| N: 32 | |
| unconditional_guidance_scale: 3.0 | |
| unconditional_guidance_label: [""] | |
| trainer: | |
| benchmark: True | |
| limit_val_batches: 0 | |
| num_sanity_val_steps: 0 | |
| accumulate_grad_batches: 1 | |