config.yaml

name: cc12m_256x256
dataset_config: configs/datasets/cc12m.yaml
# sampler_arguments
min_examples: 10000
sample-dir: /mnt/data/samples
# batch-size: 32
sample_image_size: 256
test_file_list: validation.tsv
#reader-config-file: configs/datasets/reader_config_eval.yaml
# shared_arguments
output_dir: /mnt/data/outputs
num_diffusion_steps: 1000
reproject_signal: false
model_output_scale: 0
prediction_type: V_PREDICTION
loss_target_type: DDPM
schedule_type: DEEPFLOYD
prediction_length: 129
use_vdm_loss_weights: false
use_double_loss: true
no_use_residual: true
num_training_steps: 1000000
avg_lm_steps: 0
categorical_conditioning: 0
rescale_signal: 1
schedule_shifted: true
skip_normalization: true
random_low_noise: true
vocab_file: t5.vocab
text_model: google/flan-t5-xl
model: nested_unet
vision_model: nested_unet
#model_config-file: configs/models/model_config_nested256.yaml
unet_config:
  attention_levels: []
  conditioning_feature_dim: -1
  conditioning_feature_proj_dim: -1
  freeze_inner_unet: false
  initialize_inner_with_pretrained: None
  inner_config:
    attention_levels: [1, 2]
    conditioning_feature_dim: -1
    conditioning_feature_proj_dim: 2048
    masked_cross_attention: 0
    micro_conditioning: scale:64
    nesting: true
    num_attention_layers: [0, 1, 5]
    num_lm_head_layers: 0
    num_resnets_per_resolution: [2, 2, 2]
    num_temporal_attention_layers: null
    resnet_config: {dropout: 0.0, num_channels: -1, num_groups_norm: 32, output_channels: -1,
      use_attention_ffn: true}
    resolution_channels: [256, 512, 768]
    skip_cond_emb: false
    skip_mid_blocks: false
    temporal_dim: null
    temporal_mode: false
    temporal_positional_encoding: false
    temporal_spatial_ds: false
  interp_conditioning: false
  masked_cross_attention: 1
  micro_conditioning: scale:256
  nesting: false
  num_attention_layers: [0, 0, 0]
  num_lm_head_layers: 0
  num_resnets_per_resolution: [2, 2, 1]
  num_temporal_attention_layers: null
  resnet_config: {dropout: 0.0, num_channels: -1, num_groups_norm: 32, output_channels: -1,
    use_attention_ffn: false}
  resolution_channels: [64, 128, 256]
  skip_cond_emb: true
  skip_inner_unet_input: false
  skip_mid_blocks: true
  skip_normalization: true
  temporal_dim: 1024
  temporal_mode: false
  temporal_positional_encoding: false
  temporal_spatial_ds: false

reader_config:
  image_size: 256
  smaller_side_size: 256
  random_crop: false
  max_caption_length: -1
  max_token_length: 128
  reader_buffer_size: 2000
  shuffle_buffer_size: 2000

  append_eos: true
  num_readers: 2
  pad_to_max_length: false
  padding_token: <pad>
  prepad_bos: false
  prepad_caption_with_space: true
  random_crop: false
  #reader_buffer_size: 64
  #shuffle_buffer_size: 9600
  use_tokenizer_scores: true

use_lm_mask: 1
#  torchmetrics_arguments:
metrics: fid,clip
#  trainer_arguments:
use_precomputed_text_embeddings: 0
pretrained_vision_file: vis_model_256x256.pth
#batch_size: 24
mixed_ratio: '2:1'
gradient_clip_norm: 2
loss_factor: 1
num_gradient_accumulations: 1
warmup_steps: 10000
# reader-config-file: configs/datasets/reader_config.yaml
log_freq: 50
save_freq: 5000
lr: 5.0e-05
fp16: 0