train non-pyramid with raw curv inputs
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@@ -1,5 +1,6 @@
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python merge_data.py -fi '/home/workspace/data/dataset/train' -fo '/home/workspace/local-data/train' -s 0 -e 1500
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nohup python auto_encoder_curv.py --name="lhunor_curv_raw_r2" > nohup/review/curv_raw_r2.out 2>&1 &
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nohup python cvae.py --name="lhunor_abl_all_raw_r2" > nohup/review/abl_all_raw_r2.out 2>&1 &
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one final convolutional layer for smoothing, on the final coordinates
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@@ -19,9 +19,10 @@ config['only_curvatures'] = False
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ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
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assert ablation_count == 1 or ablation_count == 0
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config['gpu'] = '1'
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config['name'] = 'al_all_post'
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config['gpu'] = '3'
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config['name'] = 'abl_all_raw_r2'
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config['notes'] = ''
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config['tags'] = ['review_2']
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config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
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if config['use_skinning']:
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@@ -45,7 +46,7 @@ config['test_dir'] = '/home/workspace/data/dataset/test_ready'
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config['static_model'] = 'checkpoints/post/static_post_2'
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config['body_model'] = 'checkpoints/post/body_post_2'
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config['curvature_model'] = 'checkpoints/post/curv_post_1'
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config['curvature_model'] = 'checkpoints/post/curv_raw_r2'
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config['smpl_res'] = 14475
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@@ -45,7 +45,7 @@ from models.cvae_model import CVAENew as CVAE
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def init_wandb():
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run = wandb.init(project='ablation', name=config['name'], notes=config['notes'], dir='/wandb')
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run = wandb.init(project='ablation', name=config['name'], notes=config['notes'], dir='/wandb', tags=config['tags'])
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artifact = wandb.Artifact('code', type='code')
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artifact.add_file('cvae.py')
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artifact.add_file('models/cvae_model.py')
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@@ -58,7 +58,9 @@ def init_wandb():
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artifact.add_file('convnext/models/convnext_tf.py')
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config_file_names = [key for key in sys.modules.keys() if key.startswith('configs.')]
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for config_file_name in config_file_names:
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artifact.add_file('/'.join(config_file_name.split('.')) + '.py')
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file_name = '/'.join(config_file_name.split('.')) + '.py'
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if os.path.exists(file_name):
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artifact.add_file(file_name)
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run.log_artifact(artifact)
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uv2mesh = UV2Mesh(res=256, is_skirt=config['is_skirt'], is_adaptive=False, is_smpl_orig=config['is_cape'])
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@@ -73,7 +75,7 @@ def kl_loss(mean, logvar):
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# 3d loss on posed !!!!!!!!!!!!
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# @tf.function
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@tf.function
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def train_step(batch):
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with tf.GradientTape() as tape:
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@@ -476,7 +478,7 @@ def test():
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if __name__ == '__main__':
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# init_wandb()
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init_wandb()
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parser = argparse.ArgumentParser(description='')
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parser.add_argument('--name', type=str)
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args = vars(parser.parse_args())
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