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  1. args.json +60 -0
  2. v1-inference.yaml +70 -0
args.json ADDED
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+ {
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+ "pretrained_model_name_or_path": "runwayml/stable-diffusion-v1-5",
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+ "pretrained_vae_name_or_path": "stabilityai/sd-vae-ft-mse",
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+ "revision": "fp16",
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+ "tokenizer_name": null,
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+ "instance_data_dir": null,
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+ "class_data_dir": null,
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+ "instance_prompt": null,
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+ "class_prompt": null,
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+ "save_sample_prompt": "photo of melaura person",
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+ "save_sample_negative_prompt": null,
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+ "n_save_sample": 4,
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+ "save_guidance_scale": 7.5,
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+ "save_infer_steps": 20,
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+ "pad_tokens": false,
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+ "with_prior_preservation": true,
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+ "prior_loss_weight": 1.0,
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+ "num_class_images": 460,
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+ "output_dir": "/content/stable_diffusion_models/melaura",
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+ "seed": 1337,
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+ "resolution": 512,
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+ "center_crop": false,
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+ "train_text_encoder": true,
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+ "train_batch_size": 1,
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+ "sample_batch_size": 4,
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+ "num_train_epochs": 11,
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+ "max_train_steps": 5040,
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+ "gradient_accumulation_steps": 1,
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+ "gradient_checkpointing": false,
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+ "learning_rate": 1e-06,
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+ "scale_lr": false,
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+ "lr_scheduler": "constant",
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+ "lr_warmup_steps": 0,
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+ "use_8bit_adam": true,
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+ "adam_beta1": 0.9,
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+ "adam_beta2": 0.999,
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+ "adam_weight_decay": 0.01,
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+ "adam_epsilon": 1e-08,
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+ "max_grad_norm": 1.0,
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+ "push_to_hub": false,
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+ "hub_token": null,
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+ "hub_model_id": null,
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+ "logging_dir": "logs",
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+ "log_interval": 10,
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+ "save_interval": 10000,
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+ "save_min_steps": 0,
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+ "mixed_precision": "fp16",
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+ "not_cache_latents": false,
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+ "hflip": false,
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+ "local_rank": -1,
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+ "concepts_list": [
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+ {
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+ "instance_prompt": "photo of melaura person",
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+ "class_prompt": "photo of person",
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+ "instance_data_dir": "/content/data/training_images",
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+ "class_data_dir": "/content/data/person"
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+ }
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+ ],
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+ "read_prompts_from_txts": false
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+ }
v1-inference.yaml ADDED
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+ model:
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+ base_learning_rate: 1.0e-04
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+ target: ldm.models.diffusion.ddpm.LatentDiffusion
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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: "jpg"
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+ cond_stage_key: "txt"
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+ image_size: 64
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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: crossattn
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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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+
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+ scheduler_config: # 10000 warmup steps
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+ target: ldm.lr_scheduler.LambdaLinearScheduler
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+ params:
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+ warm_up_steps: [ 10000 ]
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+ cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
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+ f_start: [ 1.e-6 ]
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+ f_max: [ 1. ]
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+ f_min: [ 1. ]
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+
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+ unet_config:
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+ target: ldm.modules.diffusionmodules.openaimodel.UNetModel
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+ params:
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+ image_size: 32 # unused
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+ in_channels: 4
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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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+
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+ first_stage_config:
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+ target: ldm.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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+
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+ cond_stage_config:
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+ target: ldm.modules.encoders.modules.FrozenCLIPEmbedder