124 lines
3.0 KiB
YAML
124 lines
3.0 KiB
YAML
model:
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base_learning_rate: 2.0e-05
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target: custom_net.customnet.CustomNet
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params:
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linear_start: 0.00085
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linear_end: 0.0120
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num_timesteps_cond: 1
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log_every_t: 200
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timesteps: 1000
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first_stage_key: "image_target"
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cond_stage_key: "image_cond"
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image_size: 32
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channels: 4
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cond_stage_trainable: false # Note: different from the one we trained before
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conditioning_key: hybrid
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monitor: val/loss_simple_ema
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scale_factor: 0.18215
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use_ema: false
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use_cond_concat: true
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use_bbox_mask: false
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use_bg_inpainting: false
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learning_rate_scale: 10
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ucg_training:
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txt: 0.15
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sd_15_ckpt: #"v1-5-pruned-emaonly.ckpt"
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unet_config:
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target: custom_net.openaimodel.UNetModel
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params:
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image_size: 32 # unused
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in_channels: 8
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out_channels: 4
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model_channels: 320
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attention_resolutions: [ 4, 2, 1 ]
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num_res_blocks: 2
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channel_mult: [ 1, 2, 4, 4 ]
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num_heads: 8
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use_spatial_transformer: True
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transformer_depth: 1
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context_dim: 768
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use_checkpoint: True
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legacy: False
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first_stage_config:
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target: models.autoencoder.AutoencoderKL
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params:
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embed_dim: 4
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monitor: val/rec_loss
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ddconfig:
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double_z: true
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z_channels: 4
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resolution: 256
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in_channels: 3
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out_ch: 3
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ch: 128
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ch_mult:
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- 1
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- 2
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- 4
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- 4
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num_res_blocks: 2
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attn_resolutions: []
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dropout: 0.0
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lossconfig:
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target: torch.nn.Identity
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cond_stage_config:
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target: customnet_modules.modules.FrozenCLIPImageEmbedder
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text_encoder_config:
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target: customnet_modules.modules.FrozenCLIPEmbedder
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params:
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version: openai/clip-vit-large-patch14
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## this is a template dataset
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train_data:
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target: data.dataset.Dataset
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params:
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image_size: 256
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root: examples/dataset/
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train_dataloader:
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batch_size: 12
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num_workers: 8
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lightning:
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find_unused_parameters: false
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metrics_over_trainsteps_checkpoint: True
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modelcheckpoint:
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params:
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every_n_train_steps: 10000
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save_top_k: -1
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monitor: null
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callbacks:
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image_logger:
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target: main.ImageLogger
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params:
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batch_frequency: 2500
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max_images: 32
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increase_log_steps: False
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log_first_step: True
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log_images_kwargs:
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use_ema_scope: False
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inpaint: False
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plot_progressive_rows: False
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plot_diffusion_rows: False
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N: 32
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unconditional_guidance_scale: 3.0
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unconditional_guidance_label: [""]
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trainer:
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benchmark: True
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limit_val_batches: 0
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num_sanity_val_steps: 0
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accumulate_grad_batches: 1
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