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Commit 976665f7 authored by Sebastian N.'s avatar Sebastian N.
Browse files

Renamed load_data(batch_size, img_size) to load_data_img because it clashes...

Renamed load_data(batch_size, img_size) to load_data_img because it clashes with load_data(train_batch_size, test_batch_size)
parent 06b482a2
Pipeline #205588 failed with stages
in 18 seconds
......@@ -68,7 +68,7 @@ class ${tc.fileNameWithoutEnding}:
return train_iter, train_test_iter, test_iter, data_mean, data_std, train_images, test_images
def load_data(self, batch_size, img_size):
def load_data_img(self, batch_size, img_size):
train_h5, test_h5 = self.load_h5_files()
width = img_size[0]
height = img_size[1]
......
......@@ -81,7 +81,7 @@ class ${tc.fileNameWithoutEnding}:
logging.error("Context argument is '" + context + "'. Only 'cpu' and 'gpu are valid arguments'.")
#train_iter = getDataIter(mx_context, batch_size, 100)
train_iter, test_iter, data_mean, data_std = self._data_loader.load_data(batch_size, img_resize)
train_iter, test_iter, data_mean, data_std = self._data_loader.load_data_img(batch_size, img_resize)
if 'weight_decay' in optimizer_params:
optimizer_params['wd'] = optimizer_params['weight_decay']
......
......@@ -67,7 +67,7 @@ class CNNDataLoader_Alexnet:
return train_iter, train_test_iter, test_iter, data_mean, data_std, train_images, test_images
def load_data(self, batch_size, img_size):
def load_data_img(self, batch_size, img_size):
train_h5, test_h5 = self.load_h5_files()
width = img_size[0]
height = img_size[1]
......
......@@ -67,7 +67,7 @@ class CNNDataLoader_CifarClassifierNetwork:
return train_iter, train_test_iter, test_iter, data_mean, data_std, train_images, test_images
def load_data(self, batch_size, img_size):
def load_data_img(self, batch_size, img_size):
train_h5, test_h5 = self.load_h5_files()
width = img_size[0]
height = img_size[1]
......
......@@ -67,7 +67,7 @@ class CNNDataLoader_VGG16:
return train_iter, train_test_iter, test_iter, data_mean, data_std, train_images, test_images
def load_data(self, batch_size, img_size):
def load_data_img(self, batch_size, img_size):
train_h5, test_h5 = self.load_h5_files()
width = img_size[0]
height = img_size[1]
......
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