config = dict()

config['gpu'] = '3'
config['name'] = 'abl_pyr_64_128_2'
config['notes'] = 'use offsets as input for higher levels'
config['tags'] = ['pyr_post']

# DON'T FORGET TO RESET SSIM LOSS USAGE
# DON'T FORGET TO CHECK MODEL LOADING
# DON'T FORGET TO CHECK IF STORE IN MEMORY
# DON'T FORGET TO CHECK REG LOSS COEFF
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
# DON'T FORGET TO CHECK IF SKIRT
# DON'T FORGET TO CHECK IF CAPE
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS

config['use_skinning'] =              True # and deshaping
config['remove_global_orientation'] = True
config['use_extra_losses'] =          True # edge, collision, 3d mesh
config['use_offsets'] =               False
config['use_norm_loss'] =             True

config['pretrained_model'] = ''
config['pretrained_model_iteration'] = ''

config['pyramid'] = dict()
config['pyramid']['resolutions'] = [64, 128]
config['pyramid']['pretrained_pyramid'] = 'checkpoints/postabl_pyr_64'
config['pyramid']['final_upscale_enhancer'] = ''

config['train_dir'] = '/home/workspace/local-data/train'
config['valid_dir'] = '/home/workspace/local-data/valid'
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
config['batch_size'] = 4
config['is_skirt'] = False
config['is_cape'] = False

config['dataset_in_memory'] = False
config['resolution'] = None

config['smpl_res'] = 14475
if config['is_cape']:
  config['smpl_res'] = 3638

config['lr'] = 0.0001
config['starting_balancing_coeff'] = 0.001
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
config['avg_garment_path'] = ''

config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
                          'pose_shape': (72 + 11,),
                          'uv_body_posed': (512, 256, 3),
                          'mesh_body_posed': (config['smpl_res'], 3,),
                          'mesh_posed': (config['smpl_res'], 3,),
                          'mesh_unposed': (config['smpl_res'], 3,),
                          'uv_unposed': (512, 256, 3),
                          'uv_curvature': (512, 256, 7),
                        }
config['signature_static'] = { 'uv_static': (512, 256, 3),
                              'mesh_mask': (config['smpl_res'],),
                              'uv_mask': (512, 256,),
                              }

config['pyramid']['is_label'] = False
config['pyramid']['add_noise'] = True
config['pyramid']['noise_amount'] = 0.001

config['pyramid']['loss_weights'] = [1,1,1,1,1]

for res in config['pyramid']['resolutions']:
  if res != 512:
      res_modifier = '_' + str(res)
      config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
      config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
      config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
      config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
      config['signature_static']['uv_mask' + res_modifier] = (res, res//2)

config['pyramid']['static_model'] = 'checkpoints/post/static_post_2'
config['pyramid']['body_model'] = 'checkpoints/post/body_post_2'
config['pyramid']['curvature_model'] = 'checkpoints/post/curv_post_1'
config['pyramid']['freeze_encoders'] = True


config['pyramid']['levels'] = []
for res in config['pyramid']['resolutions']:
  if res == 512:
    level = dict()
    level['resolution'] = 512
    level['latent_dim'] = config['latent_dim']
    level['kernel_size'] = 7
    level['encoder_depths'] = [3, 3, 9, 3]
    level['encoder_dims'] = [32, 64, 128, 64]
    level['decoder_input'] = (16, 8, 80)
    level['decoder_depths'] = [3, 3, 9, 3]
    level['decoder_dims'] = [256, 128, 64, 16]
    level['avg_garment_path'] = ''
    level['upscale_enhancer'] = ''
    config['pyramid']['levels'].append(level)
  elif res == 256:
    level = dict()
    level['resolution'] = 256
    level['latent_dim'] = config['latent_dim']
    level['kernel_size'] = 7
    level['encoder_depths'] = [9, 9, 9, 9]
    level['encoder_dims'] = [32, 64, 128, 64]
    level['decoder_input'] = (8, 4, 128)
    level['decoder_depths'] = [9, 9, 9, 9]
    level['decoder_dims'] = [256, 128, 64, 16]
    level['avg_garment_path'] = ''
    level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
    level['upscale_enhancer_freeze'] = True
    config['pyramid']['levels'].append(level)
  elif res == 128:
    level = dict()
    level['resolution'] = 128
    level['kernel_size'] = 5
    level['encoder_depths'] = [9, 9, 9]
    level['encoder_dims'] = [32, 64, 64]
    level['decoder_depths'] = level['encoder_depths']
    level['decoder_dims'] = level['encoder_dims']
    level['avg_garment_path'] = ''
    level['upscale_enhancer'] = 'checkpoints/128_512_3'#'checkpoints/up_3_d128_256_2'
    level['upscale_enhancer_freeze'] = True
    level['upscale_enhancer_kernel_size'] = 3
    config['pyramid']['levels'].append(level)
  elif res == 64:
    level = dict()
    level['resolution'] = 64
    level['kernel_size'] = 5
    level['encoder_depths'] = [9, 9]
    level['encoder_dims'] = [64, 64]
    level['decoder_depths'] = level['encoder_depths']
    level['decoder_dims'] = level['encoder_dims']
    level['avg_garment_path'] = ''
    level['upscale_enhancer'] = 'checkpoints/64_512_2'#checkpoints/up_3_d64_128_2'
    level['upscale_enhancer_freeze'] = True
    config['pyramid']['levels'].append(level)
  # elif res == 32:
  #   level = dict()
  #   level['resolution'] = 32
  #   level['latent_dim'] = config['latent_dim']
  #   level['kernel_size'] = 3
  #   level['encoder_depths'] = [9, 9]
  #   level['encoder_dims'] = [256, 256]
  #   level['decoder_input'] = (4, 2, 256)
  #   level['decoder_depths'] = [9, 9]
  #   level['decoder_dims'] = [256, 256]
  #   level['avg_garment_path'] = ''
  #   level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
  #   level['upscale_enhancer_freeze'] = True
  #   config['pyramid']['levels'].append(level)
  else:
    raise NotImplementedError

config['cond_ae_static'] = dict()
config['cond_ae_static']['is_label'] = False
config['cond_ae_static']['kernel_size'] = 7
config['cond_ae_static']['bottleneck_size'] = 8
config['cond_ae_static']['encoder_depths'] = [3, 3, 3, 9, 3]
config['cond_ae_static']['encoder_dims'] = [16, 32, 64, 64, config['cond_ae_static']['bottleneck_size']]
config['cond_ae_static']['decoder_depths'] = config['cond_ae_static']['encoder_depths']
config['cond_ae_static']['decoder_dims'] = config['cond_ae_static']['encoder_dims']
config['cond_ae_static']['activation'] = 'tanh'

config['cond_ae_curv'] = dict()
config['cond_ae_curv']['is_label'] = True
config['cond_ae_curv']['kernel_size'] = 7
config['cond_ae_curv']['bottleneck_size'] = 40
config['cond_ae_curv']['encoder_depths'] = [3, 3, 9, 9, 3]
config['cond_ae_curv']['encoder_dims'] = [16, 32, 64, 128, config['cond_ae_curv']['bottleneck_size']]
config['cond_ae_curv']['decoder_depths'] = config['cond_ae_curv']['encoder_depths']
config['cond_ae_curv']['decoder_dims'] = config['cond_ae_curv']['encoder_dims']
config['cond_ae_curv']['activation'] = 'tanh'

config['cond_ae_body'] = dict()
config['cond_ae_body']['is_label'] = False
config['cond_ae_body']['kernel_size'] = 7
config['cond_ae_body']['bottleneck_size'] = 16
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3]
config['cond_ae_body']['encoder_dims'] = [16, 32, 64, 128, config['cond_ae_body']['bottleneck_size']]
config['cond_ae_body']['decoder_depths'] = config['cond_ae_body']['encoder_depths']
config['cond_ae_body']['decoder_dims'] = config['cond_ae_body']['encoder_dims']
config['cond_ae_body']['activation'] = 'tanh'