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name_eye='long_generic_creative_sequential_r6_partstack_aug_eye_unet_largeaug'
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load_from = load_latest(models_dir, name_eye)
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load_from = min(min_step, load_from)
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model_eye = Trainer_cond_unet(name_eye, results_dir, models_dir, n_part=n_part, batch_size=batch_size, image_size=image_size, network_capacity=network_capacity)
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model_eye.load_config()
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model_eye.GAN.load_state_dict(torch.load('%s/%s/model_%d.pt'%(models_dir, name_eye, load_from)))
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name_head='long_generic_creative_sequential_r6_partstack_aug_head_unet_largeaug'
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load_from = load_latest(models_dir, name_head)
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load_from = min(min_step, load_from)
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model_head = Trainer_cond_unet(name_head, results_dir, models_dir, n_part=n_part, batch_size=batch_size, image_size=image_size, network_capacity=network_capacity)
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model_head.load_config()
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model_head.GAN.load_state_dict(torch.load('%s/%s/model_%d.pt'%(models_dir, name_head, load_from)))
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name_body='long_generic_creative_sequential_r6_partstack_aug_body_unet_largeaug'
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load_from = load_latest(models_dir, name_body)
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load_from = min(min_step, load_from)
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model_body = Trainer_cond_unet(name_body, results_dir, models_dir, n_part=n_part, batch_size=batch_size, image_size=image_size, network_capacity=network_capacity)
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model_body.load_config()
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model_body.GAN.load_state_dict(torch.load('%s/%s/model_%d.pt'%(models_dir, name_body, load_from)))
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name_beak='long_generic_creative_sequential_r6_partstack_aug_beak_unet_largeaug'
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load_from = load_latest(models_dir, name_beak)
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load_from = min(min_step, load_from)
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model_beak = Trainer_cond_unet(name_beak, results_dir, models_dir, n_part=n_part, batch_size=batch_size, image_size=image_size, network_capacity=network_capacity)
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model_beak.load_config()
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model_beak.GAN.load_state_dict(torch.load('%s/%s/model_%d.pt'%(models_dir, name_beak, load_from)))
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name_ears='long_generic_creative_sequential_r6_partstack_aug_ears_unet_largeaug'
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load_from = load_latest(models_dir, name_ears)
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load_from = min(min_step, load_from)
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model_ears = Trainer_cond_unet(name_ears, results_dir, models_dir, n_part=n_part, batch_size=batch_size, image_size=image_size, network_capacity=network_capacity)
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model_ears.load_config()
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model_ears.GAN.load_state_dict(torch.load('%s/%s/model_%d.pt'%(models_dir, name_ears, load_from)))
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name_hands='long_generic_creative_sequential_r6_partstack_aug_hands_unet_largeaug'
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load_from = load_latest(models_dir, name_hands)
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load_from = min(min_step, load_from)
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model_hands = Trainer_cond_unet(name_hands, results_dir, models_dir, n_part=n_part, batch_size=batch_size, image_size=image_size, network_capacity=network_capacity)
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model_hands.load_config()
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model_hands.GAN.load_state_dict(torch.load('%s/%s/model_%d.pt'%(models_dir, name_hands, load_from)))
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name_legs='long_generic_creative_sequential_r6_partstack_aug_legs_unet_largeaug'
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load_from = load_latest(models_dir, name_legs)
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load_from = min(min_step, load_from)
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model_legs = Trainer_cond_unet(name_legs, results_dir, models_dir, n_part=n_part, batch_size=batch_size, image_size=image_size, network_capacity=network_capacity)
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model_legs.load_config()
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model_legs.GAN.load_state_dict(torch.load('%s/%s/model_%d.pt'%(models_dir, name_legs, load_from)))
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name_feet='long_generic_creative_sequential_r6_partstack_aug_feet_unet_largeaug'
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load_from = load_latest(models_dir, name_feet)
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load_from = min(min_step, load_from)
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model_feet = Trainer_cond_unet(name_feet, results_dir, models_dir, n_part=n_part, batch_size=batch_size, image_size=image_size, network_capacity=network_capacity)
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model_feet.load_config()
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model_feet.GAN.load_state_dict(torch.load('%s/%s/model_%d.pt'%(models_dir, name_feet, load_from)))
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name_wings='long_generic_creative_sequential_r6_partstack_aug_wings_unet_largeaug'
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load_from = load_latest(models_dir, name_wings)
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load_from = min(min_step, load_from)
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model_wings = Trainer_cond_unet(name_wings, results_dir, models_dir, n_part=n_part, batch_size=batch_size, image_size=image_size, network_capacity=network_capacity)
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model_wings.load_config()
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model_wings.GAN.load_state_dict(torch.load('%s/%s/model_%d.pt'%(models_dir, name_wings, load_from)))
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name_mouth='long_generic_creative_sequential_r6_partstack_aug_mouth_unet_largeaug'
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load_from = load_latest(models_dir, name_mouth)
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load_from = min(min_step, load_from)
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model_mouth = Trainer_cond_unet(name_mouth, results_dir, models_dir, n_part=n_part, batch_size=batch_size, image_size=image_size, network_capacity=network_capacity)
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model_mouth.load_config()
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model_mouth.GAN.load_state_dict(torch.load('%s/%s/model_%d.pt'%(models_dir, name_mouth, load_from)))
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name_nose='long_generic_creative_sequential_r6_partstack_aug_nose_unet_largeaug'
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load_from = load_latest(models_dir, name_nose)
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load_from = min(min_step, load_from)
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model_nose = Trainer_cond_unet(name_nose, results_dir, models_dir, n_part=n_part, batch_size=batch_size, image_size=image_size, network_capacity=network_capacity)
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model_nose.load_config()
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model_nose.GAN.load_state_dict(torch.load('%s/%s/model_%d.pt'%(models_dir, name_nose, load_from)))
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name_hair='long_generic_creative_sequential_r6_partstack_aug_hair_unet_largeaug'
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load_from = load_latest(models_dir, name_hair)
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load_from = min(min_step, load_from)
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model_hair = Trainer_cond_unet(name_hair, results_dir, models_dir, n_part=n_part, batch_size=batch_size, image_size=image_size, network_capacity=network_capacity)
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model_hair.load_config()
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model_hair.GAN.load_state_dict(torch.load('%s/%s/model_%d.pt'%(models_dir, name_hair, load_from)))
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name_tail='long_generic_creative_sequential_r6_partstack_aug_tail_unet_largeaug'
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load_from = load_latest(models_dir, name_tail)
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load_from = min(min_step, load_from)
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