fix logger repetitive output

Author: hardyqr

.gitignore

@@ -0,0 +1,2 @@
+runs/
+__pycache__/

README.md

@@ -240,7 +240,7 @@ def i2t(images, captions, npts=None, measure='cosine',
     """
     if npts is None:
         npts = int(images.shape[0] / 5)
-        print(npts)
+        #print(npts)
     index_list = []
 
     scores = images.dot(captions.T)
@@ -297,7 +297,7 @@ def t2i(images, captions, npts=None, measure='cosine',
     """
     if npts is None:
         npts = int(images.shape[0] / 5)
-        print(npts)
+        #print("# points:", npts)
     ims = numpy.array([images[i] for i in range(0, len(images), 5)])
 
     scores = captions.dot(ims.T)

compute_results.py

@@ -0,0 +1,34 @@
+# Automatically generated by https://github.com/damnever/pigar.
+
+# HAL/data.py: 6
+Pillow == 7.0.0
+
+# HAL/data.py: 5
+# HAL/vocab.py: 2
+nltk == 3.4.5
+
+# HAL/data.py: 8
+# HAL/evaluation.py: 5,8
+# HAL/model.py: 10
+numpy == 1.18.1
+
+# HAL/data.py: 7
+# HAL/vocab.py: 5
+pycocotools-fix == 2.0.0.9
+
+# HAL/data.py: 7
+# HAL/vocab.py: 5
+pycocotools-win == 2.0
+
+# HAL/train.py: 9
+tensorboard_logger == 0.1.0
+
+# HAL/data.py: 1,2
+# HAL/evaluation.py: 10
+# HAL/model.py: 7,8,9
+# HAL/train.py: 7
+torch == 1.5.1
+
+# HAL/data.py: 3
+# HAL/model.py: 5
+torchvision == 0.6.0a0+35d732a

data.py

@@ -2,21 +2,17 @@
 import os
 import time
 import shutil
-
+from random import random
+import argparse
 import torch
+import logging
+import tensorboard_logger as tb_logger 
 
 import data
 from vocab import Vocabulary  # NOQA
 from model import VSE
 from evaluation import i2t, t2i, AverageMeter, LogCollector, encode_data
 
-import logging
-import tensorboard_logger as tb_logger
-from random import random
-
-import argparse
-
-
 def main():
     # Hyper Parameters
     parser = argparse.ArgumentParser()
@@ -101,10 +97,6 @@ def main():
 
     logging.basicConfig(format='%(message)s', level=logging.INFO)
     tb_logger.configure(opt.logger_name, flush_secs=5)
-    logger = logging.getLogger()
-    sh = logging.StreamHandler()
-    logger.addHandler(sh)
-    logger.setLevel(logging.INFO)
 
     # Load Vocabulary Wrapper
     vocab = pickle.load(open(os.path.join(
@@ -149,7 +141,7 @@ def main():
 
         # evaluate on validation set
         rsum = validate(opt, val_loader, model)
-        print ("rsum:",rsum)
+        print ("rsum: %.1f" % rsum)
         if opt.record_val:
             with open("rst_val_" + opt.logger_name[5:], "a") as f:
                 f.write("Epoch: %d ; rsum: %.1f\n" %(epoch, rsum))
@@ -283,6 +275,7 @@ def validate(opt, val_loader, model):
 def save_checkpoint(state, is_best, filename='checkpoint.pth.tar', prefix='', save_all=True):
     torch.save(state, prefix + filename)
     if is_best:
+        print ("[Best model sofar, saved.]")
         shutil.copyfile(prefix + filename, prefix + 'model_best.pth.tar')
     if save_all:
         shutil.copyfile(prefix + filename, prefix + "Epoch-" + str(state['epoch']) + "-" + 'model.pth.tar')