Use pandas for examples, removed csv import

Author: terrytangyuan

AUTHORS

@@ -9,4 +9,4 @@
 # If you have contributed a few PRs, feel free to send a PR adding yourself here.
 
 Google Inc.
-Yuan (Terry) Tang [email protected] 
+Yuan Tang [email protected] 

CONTRIBUTORS

@@ -12,4 +12,4 @@
 # If you have contributed a few PRs, feel free to send a PR adding yourself here.
 
 Illia Polosukhin [email protected]
-Yuan (Terry) Tang [email protected]
+Yuan Tang [email protected]

examples/text_classification.py

@@ -12,7 +12,6 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 
-import csv
 import numpy as np
 from sklearn import metrics
 import pandas

examples/text_classification_character_cnn.py

@@ -24,7 +24,6 @@
    https://github.com/zhangxiangxiao/Crepe
 """
 
-import csv
 import numpy as np
 from sklearn import metrics
 import pandas

examples/text_classification_character_rnn.py

@@ -24,7 +24,6 @@
    https://github.com/zhangxiangxiao/Crepe
 """
 
-import csv
 import numpy as np
 from sklearn import metrics
 import pandas

examples/text_classification_cnn.py

@@ -12,7 +12,6 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 
-import csv
 import numpy as np
 from sklearn import metrics
 import pandas

examples/text_classification_save_restore.py

@@ -13,9 +13,9 @@
 #  limitations under the License.
 
 import os
-import csv
 import numpy as np
 from sklearn import metrics
+import pandas
 
 import tensorflow as tf
 from tensorflow.models.rnn import rnn, rnn_cell
@@ -27,17 +27,10 @@
 # https://drive.google.com/folderview?id=0Bz8a_Dbh9Qhbfll6bVpmNUtUcFdjYmF2SEpmZUZUcVNiMUw1TWN6RDV3a0JHT3kxLVhVR2M
 # Unpack: tar -xvf dbpedia_csv.tar.gz
 
-def load_dataset(filename):
-    target = []
-    data = []
-    reader = csv.reader(open(filename), delimiter=',')
-    for line in reader:
-        target.append(int(line[0]))
-        data.append(line[2])
-    return data, np.array(target, np.float32)
-
-X_train, y_train = load_dataset('dbpedia_csv/train.csv')
-X_test, y_test = load_dataset('dbpedia_csv/test.csv')
+train = pandas.read_csv('dbpedia_csv/train.csv', header=None)
+X_train, y_train = train[2], train[0]
+test = pandas.read_csv('dbpedia_csv/test.csv', header=None)
+X_test, y_test = test[2], test[0]
 
 ### Process vocabulary
 

skflow/ops/array_ops.py

@@ -71,4 +71,3 @@ def one_hot_matrix(tensor_in, num_classes, on_value=1.0, off_value=0.0):
     ret = tf.reshape(one_hot_vector, tf.concat(0, [dims, [num_classes]]))
     ret.set_shape(tensor_in.get_shape().concatenate(num_classes))
     return ret
-

skflow/ops/conv_ops.py

@@ -38,7 +38,7 @@ def conv2d(tensor_in, n_filters, filter_shape, strides=None, padding='SAME',
                  use.
         bias: Boolean, if to add bias.
     Returns:
-        A Tensor with resuling convolution.
+        A Tensor with resulting convolution.
     """
     with tf.variable_scope('convolution'):
         if strides is None: