Natural Language Processing Week3

.gitignore

@@ -31,3 +31,5 @@ Deep Learning in Computer Vision/Week5/gan-task/new_samples
 Deep Learning in Computer Vision/Week5/gan-task/face_interpolation
 *.tsv
 Natural Language Processing/Week2/data
+Natural Language Processing/Week3/starspace
+Natural Language Processing/Week3/StarSpace_embeddings

Natural Language Processing/Week3/grader.py

@@ -0,0 +1,67 @@
+import requests
+import json
+import numpy as np
+from collections import OrderedDict
+
+class Grader(object):
+    def __init__(self):
+        self.submission_page = 'https://www.coursera.org/api/onDemandProgrammingScriptSubmissions.v1'
+        self.assignment_key = '7DdYfMQFEeevjw7-W7Fr0A'
+        self.parts = OrderedDict([('98mDT', 'Question2Vec'), 
+                                  ('nc7RP', 'HitsCount'), 
+                                  ('bNp90', 'DCGScore'), 
+                                  ('3gRlQ', 'W2VTokenizedRanks'), 
+                                  ('mX6wS', 'StarSpaceRanks')])
+        self.answers = {key: None for key in self.parts}
+
+    @staticmethod
+    def ravel_output(output):
+        '''
+           If student accidentally submitted np.array with one
+           element instead of number, this function will submit
+           this number instead
+        '''
+        if isinstance(output, np.ndarray) and output.size == 1:
+            output = output.item(0)
+        return output
+
+    def submit(self, email, token):
+        submission = {
+                    "assignmentKey": self.assignment_key, 
+                    "submitterEmail": email, 
+                    "secret": token, 
+                    "parts": {}
+                  }
+        for part, output in self.answers.items():
+            if output is not None:
+                submission["parts"][part] = {"output": output}
+            else:
+                submission["parts"][part] = dict()
+        request = requests.post(self.submission_page, data=json.dumps(submission))
+        response = request.json()
+        if request.status_code == 201:
+            print('Submitted to Coursera platform. See results on assignment page!')
+        elif u'details' in response and u'learnerMessage' in response[u'details']:
+            print(response[u'details'][u'learnerMessage'])
+        else:
+            print("Unknown response from Coursera: {}".format(request.status_code))
+            print(response)
+
+    def status(self):
+        print("You want to submit these parts:")
+        for part_id, part_name in self.parts.items():
+            answer = self.answers[part_id]
+            if answer is None:
+                answer = '-'*10
+            print("Task {}: {}".format(part_name, answer[:100] + '...'))
+
+    def submit_part(self, part, output):
+        self.answers[part] = output
+        print("Current answer for task {} is: {}".format(self.parts[part], output[:100] + '...'))
+
+    def submit_tag(self, tag, output):
+        part_id = [k for k, v in self.parts.items() if v == tag]
+        if len(part_id) != 1:
+            raise RuntimeError('cannot match tag with part_id: found {} matches'.format(len(part_id)))
+        part_id = part_id[0]
+        self.submit_part(part_id, str(self.ravel_output(output)))

Natural Language Processing/Week3/util.py

@@ -0,0 +1,18 @@
+import re
+from nltk.corpus import stopwords
+
+REPLACE_BY_SPACE_RE = re.compile('[/(){}\[\]\|@,;]')
+GOOD_SYMBOLS_RE = re.compile('[^0-9a-z #+_]')
+STOPWORDS = set(stopwords.words('english'))
+def text_prepare(text):
+    text = text.lower()
+    text = REPLACE_BY_SPACE_RE.sub(' ', text)
+    text = GOOD_SYMBOLS_RE.sub('', text)
+    text = ' '.join([x for x in text.split() if x and x not in STOPWORDS])
+    return text.strip()
+
+def array_to_string(arr):
+    return '\n'.join(str(num) for num in arr)
+
+def matrix_to_string(matrix):
+    return '\n'.join('\t'.join(str(num) for num in line) for line in matrix)