From 21176d65abef5e78685356fc7d599efdfb997550 Mon Sep 17 00:00:00 2001
From: dcrmg <35922726+dcrmg@users.noreply.github.com>
Date: Mon, 6 Jan 2020 20:29:56 +0800
Subject: [PATCH 1/3] Update train.py

---
 train.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/train.py b/train.py
index cc3c049..a68488e 100644
--- a/train.py
+++ b/train.py
@@ -6,7 +6,9 @@
 import timeit
 import math
 import numpy as np
-import matplotlib.pyplot as plt
+import matplotlib
+matplotlib.use('Agg')
+from matplotlib import pyplot as plt
 import torch.backends.cudnn as cudnn
 from argparse import ArgumentParser
 # user

From bf8cfe9a37231a128fb168c42df5c210ef03c08b Mon Sep 17 00:00:00 2001
From: dcrmg <35922726+dcrmg@users.noreply.github.com>
Date: Mon, 6 Jan 2020 20:32:57 +0800
Subject: [PATCH 2/3] Update train.py

---
 train.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/train.py b/train.py
index a68488e..ecfb383 100644
--- a/train.py
+++ b/train.py
@@ -364,8 +364,8 @@ def val(args, val_loader, model):
         with torch.no_grad():
             # input_var = Variable(input).cuda()
             input_var = input.cuda()
-        start_time = time.time()
-        output = model(input_var)
+            start_time = time.time()
+            output = model(input_var)
         time_taken = time.time() - start_time
         print("[%d/%d]  time: %.2f" % (i + 1, total_batches, time_taken))
         output = output.cpu().data[0].numpy()

From 622f4beaf32d3c362ddba1c84b0bd294683e6f9c Mon Sep 17 00:00:00 2001
From: dcrmg <35922726+dcrmg@users.noreply.github.com>
Date: Mon, 6 Jan 2020 20:35:46 +0800
Subject: [PATCH 3/3] Update dataset_builder.py

---
 builders/dataset_builder.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/builders/dataset_builder.py b/builders/dataset_builder.py
index 8342357..f78a7b7 100644
--- a/builders/dataset_builder.py
+++ b/builders/dataset_builder.py
@@ -7,7 +7,7 @@
 
 def build_dataset_train(dataset, input_size, batch_size, train_type, random_scale, random_mirror, num_workers):
     data_dir = os.path.join('./dataset/', dataset)
-    dataset_list = os.path.join(dataset, '_trainval_list.txt')
+    dataset_list = dataset + '_trainval_list.txt'
     train_data_list = os.path.join(data_dir, dataset + '_' + train_type + '_list.txt')
     val_data_list = os.path.join(data_dir, dataset + '_val' + '_list.txt')
     inform_data_file = os.path.join('./dataset/inform/', dataset + '_inform.pkl')
@@ -43,7 +43,7 @@ def build_dataset_train(dataset, input_size, batch_size, train_type, random_scal
 
         valLoader = data.DataLoader(
             CityscapesValDataSet(data_dir, val_data_list, f_scale=1, mean=datas['mean']),
-            batch_size=1, shuffle=True, num_workers=num_workers, pin_memory=True,
+            batch_size=batch_size, shuffle=True, num_workers=num_workers, pin_memory=True,
             drop_last=True)
 
         return datas, trainLoader, valLoader
@@ -58,7 +58,7 @@ def build_dataset_train(dataset, input_size, batch_size, train_type, random_scal
 
         valLoader = data.DataLoader(
             CamVidValDataSet(data_dir, val_data_list, f_scale=1, mean=datas['mean']),
-            batch_size=1, shuffle=True, num_workers=num_workers, pin_memory=True)
+            batch_size=batch_size, shuffle=True, num_workers=num_workers, pin_memory=True)
 
         return datas, trainLoader, valLoader