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2024-05-21 15:29:04 +08:00
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+model:
+  base_learning_rate: 2.0e-05
+  target: custom_net.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: custom_net.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: 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: customnet_modules.modules.FrozenCLIPImageEmbedder
+
+
+    text_encoder_config:
+      target: customnet_modules.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