Unify the style of comments

Unify the style of comments suggested by @sandeep-krishnamurthy

example/cnn_text_classification/text_cnn.py

@@ -19,9 +19,7 @@
 
 # -*- coding: utf-8 -*-
 
-"""
-Implementing CNN + Highway Network for Text Classification in MXNet
-"""
+"""Implementing CNN + Highway Network for Text Classification in MXNet"""
 
 import os
 import logging
@@ -59,8 +57,7 @@
 
 
 def save_model():
-    """
-    Save cnn model
+    """Save cnn model
 
     Returns
     ----------
@@ -72,8 +69,7 @@ def save_model():
 
 
 def data_iter(batch_size, num_embed, pre_trained_word2vec=False):
-    """
-    Construct data iter
+    """Construct data iter
 
     Parameters
     ----------
@@ -136,8 +132,7 @@ def data_iter(batch_size, num_embed, pre_trained_word2vec=False):
 def sym_gen(batch_size, sentences_size, num_embed, vocabulary_size,
             num_label=2, filter_list=None, num_filter=100,
             dropout=0.0, pre_trained_word2vec=False):
-    """
-    Generate network symbol
+    """Generate network symbol
 
     Parameters
     ----------
@@ -204,8 +199,7 @@ def sym_gen(batch_size, sentences_size, num_embed, vocabulary_size,
 
 
 def train(symbol_data, train_iterator, valid_iterator, data_column_names, target_names):
-    """
-    Train cnn model
+    """Train cnn model
 
     Parameters
     ----------

example/ctc/captcha_generator.py

@@ -15,7 +15,6 @@
 # specific language governing permissions and limitations
 # under the License.
 """ Helper classes for multiprocess captcha image generation
-
 This module also provides script for saving captcha images to file using CLI.
 """
 
@@ -29,8 +28,7 @@
 
 
 class CaptchaGen(object):
-    """
-    Generates a captcha image
+    """Generates a captcha image
     """
     def __init__(self, h, w, font_paths):
         """
@@ -48,8 +46,7 @@ def __init__(self, h, w, font_paths):
         self.w = w
 
     def image(self, captcha_str):
-        """
-        Generate a greyscale captcha image representing number string
+        """Generate a greyscale captcha image representing number string
 
         Parameters
         ----------
@@ -71,8 +68,7 @@ def image(self, captcha_str):
 
 
 class DigitCaptcha(object):
-    """
-    Provides shape() and get() interface for digit-captcha image generation
+    """Provides shape() and get() interface for digit-captcha image generation
     """
     def __init__(self, font_paths, h, w, num_digit_min, num_digit_max):
         """
@@ -95,8 +91,7 @@ def __init__(self, font_paths, h, w, num_digit_min, num_digit_max):
 
     @property
     def shape(self):
-        """
-        Returns shape of the image data generated
+        """Returns shape of the image data generated
 
         Returns
         -------
@@ -105,8 +100,7 @@ def shape(self):
         return self.captcha.h, self.captcha.w
 
     def get(self):
-        """
-        Get an image from the queue
+        """Get an image from the queue
 
         Returns
         -------
@@ -117,9 +111,8 @@ def get(self):
 
     @staticmethod
     def get_rand(num_digit_min, num_digit_max):
-        """
-        Generates a character string of digits. Number of digits are
-         between self.num_digit_min and self.num_digit_max
+        """Generates a character string of digits. Number of digits are
+        between self.num_digit_min and self.num_digit_max
         Returns
         -------
         str
@@ -131,8 +124,7 @@ def get_rand(num_digit_min, num_digit_max):
         return buf
 
     def _gen_sample(self):
-        """
-        Generate a random captcha image sample
+        """Generate a random captcha image sample
         Returns
         -------
         (numpy.ndarray, str)
@@ -143,13 +135,10 @@ def _gen_sample(self):
 
 
 class MPDigitCaptcha(DigitCaptcha):
-    """
-    Handles multi-process captcha image generation
+    """Handles multi-process captcha image generation
     """
     def __init__(self, font_paths, h, w, num_digit_min, num_digit_max, num_processes, max_queue_size):
-        """
-
-        Parameters
+        """Parameters
         ----------
         font_paths: list of str
             List of path to ttf font files
@@ -170,14 +159,11 @@ def __init__(self, font_paths, h, w, num_digit_min, num_digit_max, num_processes
         self.mp_data = MPData(num_processes, max_queue_size, self._gen_sample)
 
     def start(self):
-        """
-        Starts the processes
-        """
+        """Starts the processes"""
         self.mp_data.start()
 
     def get(self):
-        """
-        Get an image from the queue
+        """Get an image from the queue
 
         Returns
         -------
@@ -187,19 +173,15 @@ def get(self):
         return self.mp_data.get()
 
     def reset(self):
-        """
-        Resets the generator by stopping all processes
-        """
+        """Resets the generator by stopping all processes"""
         self.mp_data.reset()
 
 
 if __name__ == '__main__':
     import argparse
 
     def main():
-        """
-        Program entry point
-        """
+        """Program entry point"""
         parser = argparse.ArgumentParser()
         parser.add_argument("font_path", help="Path to ttf font file")
         parser.add_argument("output", help="Output filename including extension (e.g. 'sample.jpg')")

example/ctc/ctc_metrics.py

@@ -22,8 +22,7 @@
 
 
 class CtcMetrics(object):
-    """
-    Module for calculating the prediction accuracy during training. Two accuracy measures are implemented:
+    """Module for calculating the prediction accuracy during training. Two accuracy measures are implemented:
     A simple accuracy measure that calculates number of correct predictions divided by total number of predictions
     and a second accuracy measure based on sum of Longest Common Sequence(LCS) ratio of all predictions divided by total
     number of predictions
@@ -33,9 +32,7 @@ def __init__(self, seq_len):
 
     @staticmethod
     def ctc_label(p):
-        """
-        Iterates through p, identifying non-zero and non-repeating values, and returns them in a list
-        Parameters
+        """Iterates through p, identifying non-zero and non-repeating values, and returns them in a list Parameters
         ----------
         p: list of int
 

example/ctc/hyperparams.py

@@ -20,9 +20,7 @@
 
 
 class Hyperparams(object):
-    """
-    Hyperparameters for LSTM network
-    """
+    """Hyperparameters for LSTM network"""
     def __init__(self):
         # Training hyper parameters
         self._train_epoch_size = 30000

example/ctc/lstm_ocr_infer.py

@@ -46,8 +46,7 @@ def lstm_init_states(batch_size):
 
 
 def load_module(prefix, epoch, data_names, data_shapes):
-    """
-    Loads the model from checkpoint specified by prefix and epoch, binds it
+    """Loads the model from checkpoint specified by prefix and epoch, binds it
     to an executor, and sets its parameters and returns a mx.mod.Module
     """
     sym, arg_params, aux_params = mx.model.load_checkpoint(prefix, epoch)
@@ -64,9 +63,7 @@ def load_module(prefix, epoch, data_names, data_shapes):
 
 
 def main():
-    """
-    Program entry point
-    """
+    """Program entry point"""
     parser = argparse.ArgumentParser()
     parser.add_argument("path", help="Path to the CAPTCHA image file")
     parser.add_argument("--prefix", help="Checkpoint prefix [Default 'ocr']", default='ocr')

example/ctc/lstm_ocr_train.py

@@ -42,9 +42,7 @@ def get_fonts(path):
 
 
 def parse_args():
-    """
-    Parse command line arguments
-    """
+    """Parse command line arguments"""
     parser = argparse.ArgumentParser()
     parser.add_argument("font_path", help="Path to ttf font file or directory containing ttf files")
     parser.add_argument("--loss", help="'ctc' or 'warpctc' loss [Default 'ctc']", default='ctc')
@@ -58,9 +56,7 @@ def parse_args():
 
 
 def main():
-    """
-    Program entry point
-    """
+    """Program entry point"""
     args = parse_args()
     if not any(args.loss == s for s in ['ctc', 'warpctc']):
         raise ValueError("Invalid loss '{}' (must be 'ctc' or 'warpctc')".format(args.loss))

example/ctc/multiproc_data.py

@@ -27,19 +27,17 @@
     from Queue import Full as QFullExcept
     from Queue import Empty as QEmptyExcept
 
+
 class MPData(object):
-    """
-    Handles multi-process data generation.
+    """Handles multi-process data generation.
 
     Operation:
         - call start() to start the data generation
         - call get() (blocking) to read one sample
         - call reset() to stop data generation
     """
     def __init__(self, num_processes, max_queue_size, fn):
-        """
-
-        Parameters
+        """Parameters
         ----------
         num_processes: int
             Number of processes to spawn
@@ -55,15 +53,12 @@ def __init__(self, num_processes, max_queue_size, fn):
         self.fn = fn
 
     def start(self):
-        """
-        Starts the processes
-        """
+        """Starts the processes"""
         self._init_proc()
 
     @staticmethod
     def _proc_loop(proc_id, alive, queue, fn):
-        """
-        Thread loop for generating data
+        """Thread loop for generating data
 
         Parameters
         ----------
@@ -94,9 +89,7 @@ def _proc_loop(proc_id, alive, queue, fn):
         queue.close()
 
     def _init_proc(self):
-        """
-        Start processes if not already started
-        """
+        """Start processes if not already started"""
         if not self.proc:
             self.proc = [
                 mp.Process(target=self._proc_loop, args=(i, self.alive, self.queue, self.fn))
@@ -107,8 +100,7 @@ def _init_proc(self):
                 p.start()
 
     def get(self):
-        """
-        Get a datum from the queue
+        """Get a datum from the queue
 
         Returns
         -------
@@ -119,9 +111,7 @@ def get(self):
         return self.queue.get()
 
     def reset(self):
-        """
-        Resets the generator by stopping all processes
-        """
+        """Resets the generator by stopping all processes"""
         self.alive.value = False
         qsize = 0
         try:

example/ctc/ocr_iter.py

@@ -23,8 +23,7 @@
 
 
 class SimpleBatch(object):
-    """
-    Batch class for getting label data
+    """Batch class for getting label data
     Operation:
         - call get_label() to start label data generation
     """
@@ -72,12 +71,9 @@ def get_label(buf):
 
 
 class OCRIter(mx.io.DataIter):
-    """
-    Iterator class for generating captcha image data
-    """
+    """Iterator class for generating captcha image data"""
     def __init__(self, count, batch_size, lstm_init_states, captcha, name):
-        """
-        Parameters
+        """Parameters
         ----------
         count: int
             Number of batches to produce for one epoch

example/ctc/ocr_predict.py

@@ -26,9 +26,7 @@
 
 
 class lstm_ocr_model(object):
-    """
-    LSTM network for predicting the Optical Character Recognition
-    """
+    """LSTM network for predicting the Optical Character Recognition"""
     # Keep Zero index for blank. (CTC request it)
     CONST_CHAR = '0123456789'
 
@@ -63,8 +61,7 @@ def __init_ocr(self):
                                    all_shapes_dict)
 
     def forward_ocr(self, img_):
-        """
-        Forward the image through the LSTM network model
+        """Forward the image through the LSTM network model
 
         Parameters
         ----------

example/deep-embedded-clustering/dec.py

@@ -30,7 +30,6 @@
 from solver import Solver, Monitor
 
 
-
 def cluster_acc(Y_pred, Y):
     from sklearn.utils.linear_assignment_ import linear_assignment
     assert Y_pred.size == Y.size

example/distributed_training/cifar10_dist.py

@@ -161,8 +161,7 @@ def forward_backward(network, data, label):
 
 # Train a batch using multiple GPUs
 def train_batch(batch_list, context, network, gluon_trainer):
-    """ 
-    Training with multiple GPUs
+    """ Training with multiple GPUs
 
     Parameters
     ----------