Adding type check for corpus_file argument

gensim/models/fasttext.py

@@ -280,10 +280,12 @@
 """
 
 import logging
+import os
 
 import numpy as np
 from numpy import ones, vstack, float32 as REAL, sum as np_sum
 import six
+from collections import Iterable
 
 import gensim.models._fasttext_bin
 
@@ -901,6 +903,23 @@ def train(self, sentences=None, corpus_file=None, total_examples=None, total_wor
             >>> model.train(sentences, total_examples=model.corpus_count, epochs=model.epochs)
 
         """
+
+        # Check if both sentences and corpus_file are None
+        if corpus_file is None and sentences is None:
+            raise TypeError("Either one of corpus_file or sentences value must be provided")
+
+        # Check if both sentences and corpus_file are not None
+        if corpus_file is not None and sentences is not None:
+            raise TypeError("Both corpus_file and sentences must not be provided at the same time")
+
+        # Check if corpus_file is string type
+        if sentences is None and not os.path.isfile(corpus_file):
+            raise TypeError("Parameter corpus_file must be a valid path to a file, got %r instead" % corpus_file)
+
+        # Check if sentences is iterable
+        if sentences is not None and not isinstance(sentences, Iterable):
+            raise TypeError("sentences must be an iterable of list, got %r instead" % sentences)
+
         super(FastText, self).train(
             sentences=sentences, corpus_file=corpus_file, total_examples=total_examples, total_words=total_words,
             epochs=epochs, start_alpha=start_alpha, end_alpha=end_alpha, word_count=word_count,

gensim/test/test_fasttext.py

@@ -95,6 +95,22 @@ def test_training(self):
         oov_vec = model.wv['minor']  # oov word
         self.assertEqual(len(oov_vec), 10)
 
+    def testFastTextTrainParameters(self):
+
+        model =  FT_gensim(size=10, min_count=1, hs=1, negative=0, seed=42, workers=1)
+        model.build_vocab(sentences=sentences)
+
+        # check if corpus_file is not a string
+        self.assertRaises(TypeError, model.train, corpus_file=11111)
+        # check if sentences is an iterable
+        self.assertRaises(TypeError, model.train, sentences=11111)
+        # check is both the parameters are provided
+        self.assertRaises(TypeError, model.train, sentences=sentences, corpus_file='test')
+        # check if both the parameters are left empty
+        self.assertRaises(TypeError, model.train, sentences=None, corpus_file=None)
+        # check if corpus_file is an iterable
+        self.assertRaises(TypeError, model.train, corpus_file=sentences)
+
     @unittest.skipIf(os.name == 'nt' and six.PY2, "corpus_file training is not supported on Windows + Py27")
     def test_training_fromfile(self):
         with temporary_file(get_tmpfile('gensim_fasttext.tst')) as corpus_file: