model: target: cldm.cldm.ControlLDM params: linear_start: 0.00085 linear_end: 0.0120 num_timesteps_cond: 1 log_every_t: 200 timesteps: 1000 first_stage_key: "img" cond_stage_key: "caption" control_key: "hint" glyph_key: "glyphs" position_key: "positions" image_size: 64 channels: 4 cond_stage_trainable: true # need be true when embedding_manager is valid conditioning_key: crossattn monitor: val/loss_simple_ema scale_factor: 0.18215 use_ema: False only_mid_control: False loss_alpha: 0 # perceptual loss, 0.003 loss_beta: 0 # ctc loss latin_weight: 1.0 # latin text line may need smaller weigth with_step_weight: true use_vae_upsample: true embedding_manager_config: target: cldm.embedding_manager.EmbeddingManager params: valid: true # v6 emb_type: ocr # ocr, vit, conv glyph_channels: 1 position_channels: 1 add_pos: false placeholder_string: '*' control_stage_config: target: cldm.cldm.ControlNet params: image_size: 32 # unused in_channels: 4 model_channels: 320 glyph_channels: 1 position_channels: 1 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 unet_config: target: cldm.cldm.ControlledUnetModel params: image_size: 32 # unused in_channels: 4 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.FrozenCLIPEmbedderT3 params: version: ./models/clip-vit-large-patch14 use_vision: false # v6