updated readme. other minor changes

justanhduc · Sep 7, 2020 · 235dd25 · 235dd25
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diff --git a/README.md b/README.md
@@ -5,16  5,17 @@ The official implementation of the ICCV 2019 paper
 
 ![framework](./imgs/framework.jpg)
 
-__Updates:__ We have achieved a better performance with `PointCloudResLowRankGraphXUpDecoder`, 
 __Update 1:__ We have achieved a better performance with `PointCloudResLowRankGraphXUpDecoder`, 
 which is an upgraded version of the best deformation network in the paper. The new network works 
 comparably with the best network in the paper but consumes much less memory.
 
 __Update 2 (Sep 7, 2020):__ Refactor the code to work with the latest [Neuralnet-pytorch](https://github.com/justanhduc/neuralnet-pytorch).
 
 ## Prerequisite
 
 [Pytorch](https://pytorch.org/get-started/locally/) (>=1.0.0)
 
-[Neuralnet-pytorch](https://github.com/justanhduc/neuralnet-pytorch) 
-(branch [fancy](https://github.com/justanhduc/neuralnet-pytorch/tree/fancy))
 [Neuralnet-pytorch](https://github.com/justanhduc/neuralnet-pytorch) (``pip install "neuralnet-pytorch[gin] @ git git://github.com/justanhduc/neuralnet-pytorch.git@6bda19fdc57f176cb82f58d287602f4ccf4cfc23" --global-option="--cuda-ext"``)
 
 [Gin-config](https://github.com/google/gin-config)
 

diff --git a/src/configs/lowrankgraphx-up-final.gin b/src/configs/lowrankgraphx-up-final.gin
@@ -6,6  6,6 @@ GraphX.pc_enc = @pc_enc
 GraphX.pc_dec = @pc_upreslowrankgraphxdec
 GraphX.adain = True
 GraphX.projection = True
-decimation = .5
 GraphX.decimation = .5
 GraphX.n_points = 250
 GraphX.checkpoint_folder = None
diff --git a/src/train.py b/src/train.py
@@ -16,8  16,6 @@
 from data_loader import ShapeNet, collate
 
 config_file = args.config_file
-backup_files = ['train.py', 'networks.py', 'data_loader.py', 'ops.py']   [config_file]
-
 gin.external_configurable(CNN18Encoder, 'cnn18_enc')
 gin.external_configurable(PointCloudEncoder, 'pc_enc')
 gin.external_configurable(PointCloudDecoder, 'pc_dec')
@@ -54,7  52,8 @@ def train_valid(data_root, name, img_enc, pc_enc, pc_dec, optimizer, scheduler,
     mon.num_iters = len(train_data) // bs
     mon.set_path(checkpoint_folder)
     if checkpoint_folder is None:
-        mon.backup(backup_files)
         backups = os.listdir('.')
         mon.backup(backups, ignore=('results', '*.pyc', '__pycache__', '.idea'))
         mon.dump_rep('network', net)
         mon.dump_rep('optimizer', solver)
         if scheduler is not None: