vision_charts/recon.py [216:223]:
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	parser.add_argument('--loss_coeff', type=float, default=9000., help='Coefficient for loss term.')
	parser.add_argument('--num_img_blocks', type=int, default=6, help='Number of image block in the image encoder.')
	parser.add_argument('--num_img_layers', type=int, default=3, help='Number of image layer in each blocl in the image encoder.')
	parser.add_argument('--size_img_ker', type=int, default=5, help='Size of the image kernel in each Image encoder layer')
	parser.add_argument('--num_gcn_layers', type=int, default=20, help='Number of GCN layer in the mesh deformation network.')
	parser.add_argument('--hidden_gcn_layers', type=int, default=300, help='Size of the feature vector for each  GCN layer in the mesh deformation network.')
	parser.add_argument('--num_grasps', type=int, default=1, help='Number of grasps in each instance to train with')
	parser.add_argument('--pretrained', type=str, default='no', help='String indicating which pretrained model to use.',
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vision_charts/runner.py [25:32]:
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parser.add_argument('--loss_coeff', type=float, default=9000., help='Coefficient for loss term.')
parser.add_argument('--num_img_blocks', type=int, default=6, help='Number of image block in the image encoder.')
parser.add_argument('--num_img_layers', type=int, default=3, help='Number of image layer in each blocl in the image encoder.')
parser.add_argument('--size_img_ker', type=int, default=5, help='Size of the image kernel in each Image encoder layer')
parser.add_argument('--num_gcn_layers', type=int, default=20, help='Number of GCN layer in the mesh deformation network.')
parser.add_argument('--hidden_gcn_layers', type=int, default=300, help='Size of the feature vector for each  GCN layer in the mesh deformation network.')
parser.add_argument('--num_grasps', type=int, default=1, help='Number of grasps in each instance to train with')
parser.add_argument('--pretrained', type=str, default='no', help='String indicating which pretrained model to use.',
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