Support loading fasttext model from custom file

torchnlp/metrics/__init__.py

@@ -1,7 +1,6 @@
 from torchnlp.metrics.accuracy import get_accuracy
 from torchnlp.metrics.accuracy import get_token_accuracy
 from torchnlp.metrics.bleu import get_moses_multi_bleu
-
 # TODO: Use `sklearn.metrics` for a `confusion_matrix` implemented with ignore_index
 # TODO: Use `sklearn.metrics` for a `recall` implemented with ignore_index
 # TODO: Use `sklearn.metrics` for a `precision` implemented with ignore_index

torchnlp/word_to_vector/fast_text.py

@@ -46,12 +46,16 @@ class FastText(_PretrainedWordVectors):
         * https://arxiv.org/abs/1710.04087
 
     Args:
-        language (str): language of the vectors
+        name (str or None, optional): The name of the file that contains the vectors
+        url (str or None, optional): url for download if vectors not found in cache
+        language (str): language of the vectors (only needed when both url and name
+            are ignored)
         aligned (bool): if True: use multilingual embeddings where words with
             the same meaning share (approximately) the same position in the
             vector space across languages. if False: use regular FastText
             embeddings. All available languages can be found under
-            https://github.com/facebookresearch/MUSE#multilingual-word-embeddings
+            https://github.com/facebookresearch/MUSE#multilingual-word-embeddings.
+            (only needed when both url and name are ignored)
         cache (str, optional): directory for cached vectors
         unk_init (callback, optional): by default, initialize out-of-vocabulary word vectors
             to zero vectors; can be any function that takes in a Tensor and
@@ -74,10 +78,12 @@ class FastText(_PretrainedWordVectors):
     url_base = 'https://dl.fbaipublicfiles.com/fasttext/vectors-wiki/wiki.{}.vec'
     aligned_url_base = 'https://dl.fbaipublicfiles.com/fasttext/vectors-aligned/wiki.{}.align.vec'
 
-    def __init__(self, language="en", aligned=False, **kwargs):
-        if aligned:
-            url = self.aligned_url_base.format(language)
-        else:
-            url = self.url_base.format(language)
-        name = os.path.basename(url)
+    def __init__(self, language="en", url=None, name=None, aligned=False, **kwargs):
+        if not name:
+            if not url:
+                if aligned:
+                    url = self.aligned_url_base.format(language)
+                else:
+                    url = self.url_base.format(language)
+            name = os.path.basename(url)
         super(FastText, self).__init__(name, url=url, **kwargs)