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Install the requirements pip3 install -r requirements.txt

Run the initial example in python3.9 nca/example_texture_nca.py which is a port of the simple pytorch example for Self-Organising Textures

python3.9 nca/example_texture_nca.py --train_steps=500 run --lr=0.0005
#                                                       /
#  'run' separates trainer args from NCA args ---------/

See all available arguments:

• General Training Arguments

  python3.9 nca/example_texture_nca.py --help

  --train_steps=TRAIN_STEPS
      Type: int
      Default: 5000
  --train_cuda=TRAIN_CUDA
      Type: bool
      Default: False
  --vis_period_plt=VIS_PERIOD_PLT
      Type: int
      Default: 500
  --vis_period_vid=VIS_PERIOD_VID
      Type: int
      Default: 2500
  --vis_im_size=VIS_IM_SIZE
      Type: int
      Default: 256
  --vis_out_dir=VIS_OUT_DIR
      Type: str
      Default: 'out/2021-06-11_22-09-29'
  --plt_show=PLT_SHOW
      Type: bool
      Default: False
  

• NCA Arguments

  python3.9 nca/example_texture_nca.py run --help
  

  --style_img_uri=STYLE_IMG_URI
      Type: str
      Default: 'https://upload.wikimedia.org/wikipedia/commons/thumb/0/04/T...
  --style_img_size=STYLE_IMG_SIZE
      Type: int
      Default: 128
  --nca_img_size=NCA_IMG_SIZE
      Type: int
      Default: 128
  --nca_learn_filters=NCA_LEARN_FILTERS
      Type: bool
      Default: False
  --nca_channels=NCA_CHANNELS
      Type: int
      Default: 12
  --nca_hidden_channels=NCA_HIDDEN_CHANNELS
      Type: int
      Default: 96
  --nca_pad_mode=NCA_PAD_MODE
      Type: str
      Default: 'circular'
  --nca_default_update_ratio=NCA_DEFAULT_UPDATE_RATIO
      Type: float
      Default: 0.5
  --iters=ITERS
      Type: typing.Tuple[int, int]
      Default: (32, 64)
  --batch_size=BATCH_SIZE
      Type: int
      Default: 4
  --lr=LR
      Type: float
      Default: 0.001
  --pool_size=POOL_SIZE
      Type: int
      Default: 1024
  --pool_reset_element_period=POOL_RESET_ELEMENT_PERIOD
      Type: int
      Default: 2
  --pool_on_cpu=POOL_ON_CPU
      Type: bool
      Default: True
  --normalize_gradient=NORMALIZE_GRADIENT
      Type: bool
      Default: True
  --consistency_loss_scale=CONSISTENCY_LOSS_SCALE
      Type: Optional[float]
      Default: None
  --scale_loss=SCALE_LOSS
      Type: Optional[float]
      Default: None