[MRG] *2Vec SaveLoad improvements

gensim/downloader.py

@@ -50,6 +50,7 @@
 By default, this subdirectory is ~/gensim-data.
 
 """
+
 from __future__ import absolute_import
 import argparse
 import os

gensim/models/_fasttext_bin.py

@@ -549,7 +549,7 @@ def _dict_save(fout, model, encoding):
     # prunedidx_size_=-1, -1 value denotes no prunning index (prunning is only supported in supervised mode)
     fout.write(np.int64(-1))
 
-    for word in model.wv.index2word:
+    for word in model.wv.index_to_key:
         word_count = model.wv.get_vecattr(word, 'count')
         fout.write(word.encode(encoding))
         fout.write(_END_OF_WORD_MARKER)

gensim/models/coherencemodel.py

@@ -25,6 +25,7 @@
     Internal functions for pipelines.
 
 """
+
 import logging
 import multiprocessing as mp
 from collections import namedtuple
@@ -33,9 +34,11 @@
 
 from gensim import interfaces, matutils
 from gensim import utils
-from gensim.topic_coherence import (segmentation, probability_estimation,
-                                    direct_confirmation_measure, indirect_confirmation_measure,
-                                    aggregation)
+from gensim.topic_coherence import (
+    segmentation, probability_estimation,
+    direct_confirmation_measure, indirect_confirmation_measure,
+    aggregation,
+)
 from gensim.topic_coherence.probability_estimation import unique_ids_from_segments
 
 logger = logging.getLogger(__name__)

gensim/models/doc2vec.py

@@ -799,7 +799,7 @@ def load(cls, *args, **kwargs):
         except AttributeError as ae:
             logger.error(
                 "Model load error. Was model saved using code from an older Gensim Version? "
-                "Try loading older model using gensim-3.8.1, then re-saving, to restore "
+                "Try loading older model using gensim-3.8.3, then re-saving, to restore "
                 "compatibility with current code.")
             raise ae
 

gensim/models/fasttext.py

@@ -827,7 +827,6 @@ def save(self, *args, **kwargs):
             Load :class:`~gensim.models.fasttext.FastText` model.
 
         """
-        kwargs['ignore'] = kwargs.get('ignore', []) + ['buckets_word', ]
         super(FastText, self).save(*args, **kwargs)
 
     @classmethod
@@ -850,25 +849,15 @@ def load(cls, *args, **kwargs):
             Save :class:`~gensim.models.fasttext.FastText` model.
 
         """
-        model = super(FastText, cls).load(*args, rethrow=True, **kwargs)
-
-        if not hasattr(model.wv, 'vectors_vocab_lockf') and hasattr(model.wv, 'vectors_vocab'):
-            # TODO: try trainables-location
-            model.wv.vectors_vocab_lockf = ones(1, dtype=REAL)
-        if not hasattr(model, 'vectors_ngrams_lockf') and hasattr(model.wv, 'vectors_ngrams'):
-            # TODO: try trainables-location
-            model.wv.vectors_ngrams_lockf = ones(1, dtype=REAL)
-        # fixup mistakenly overdimensioned gensim-3.x lockf arrays
-        if len(model.wv.vectors_vocab_lockf.shape) > 1:
-            model.wv.vectors_vocab_lockf = ones(1, dtype=REAL)
-        if len(model.wv.vectors_ngrams_lockf.shape) > 1:
-            model.wv.vectors_ngrams_lockf = ones(1, dtype=REAL)
-        if hasattr(model, 'bucket'):
-            del model.bucket  # should only exist in one place: the wv subcomponent
-        if not hasattr(model.wv, 'buckets_word') or not model.wv.buckets_word:
-            model.wv.recalc_char_ngram_buckets()
+        return super(FastText, cls).load(*args, rethrow=True, **kwargs)
 
-        return model
+    def _load_specials(self, *args, **kwargs):
+        """Handle special requirements of `.load()` protocol, usually up-converting older versions."""
+        super(FastText, self)._load_specials(*args, **kwargs)
+        if hasattr(self, 'bucket'):
+            # should only exist in one place: the wv subcomponent
+            self.wv.bucket = self.bucket
+            del self.bucket
 
 
 class FastTextVocab(utils.SaveLoad):
@@ -1202,12 +1191,49 @@ def __init__(self, vector_size, min_n, max_n, bucket):
 
     @classmethod
     def load(cls, fname_or_handle, **kwargs):
-        model = super(FastTextKeyedVectors, cls).load(fname_or_handle, **kwargs)
-        if isinstance(model, FastTextKeyedVectors):
-            if not hasattr(model, 'compatible_hash') or model.compatible_hash is False:
-                raise TypeError("Pre-gensim-3.8.x Fasttext models with nonstandard hashing are no longer compatible."
-                                "Loading into gensim-3.8.3 & re-saving may create a compatible model.")
-        return model
+        """Load a previously saved `FastTextKeyedVectors` model.
+
+        Parameters
+        ----------
+        fname : str
+            Path to the saved file.
+
+        Returns
+        -------
+        :class:`~gensim.models.fasttext.FastTextKeyedVectors`
+            Loaded model.
+
+        See Also
+        --------
+        :meth:`~gensim.models.fasttext.FastTextKeyedVectors.save`
+            Save :class:`~gensim.models.fasttext.FastTextKeyedVectors` model.
+
+        """
+        return super(FastTextKeyedVectors, cls).load(fname_or_handle, **kwargs)
+
+    def _load_specials(self, *args, **kwargs):
+        """Handle special requirements of `.load()` protocol, usually up-converting older versions."""
+        super(FastTextKeyedVectors, self)._load_specials(*args, **kwargs)
+        if not isinstance(self, FastTextKeyedVectors):
+            raise TypeError("Loaded object of type %s, not expected FastTextKeyedVectors" % type(self))
+        if not hasattr(self, 'compatible_hash') or self.compatible_hash is False:
+            raise TypeError(
+                "Pre-gensim-3.8.x fastText models with nonstandard hashing are no longer compatible. "
+                "Loading your old model into gensim-3.8.3 & re-saving may create a model compatible with gensim 4.x."
+            )
+        if not hasattr(self, 'vectors_vocab_lockf') and hasattr(self, 'vectors_vocab'):
+            self.vectors_vocab_lockf = ones(1, dtype=REAL)
+        if not hasattr(self, 'vectors_ngrams_lockf') and hasattr(self, 'vectors_ngrams'):
+            self.vectors_ngrams_lockf = ones(1, dtype=REAL)
+        # fixup mistakenly overdimensioned gensim-3.x lockf arrays
+        if len(self.vectors_vocab_lockf.shape) > 1:
+            self.vectors_vocab_lockf = ones(1, dtype=REAL)
+        if len(self.vectors_ngrams_lockf.shape) > 1:
+            self.vectors_ngrams_lockf = ones(1, dtype=REAL)
+        if not hasattr(self, 'buckets_word') or not self.buckets_word:
+            self.recalc_char_ngram_buckets()
+        if not hasattr(self, 'vectors') or self.vectors is None:
+            self.adjust_vectors()  # recompose full-word vectors
 
     def __contains__(self, word):
         """Check if `word` or any character ngrams in `word` are present in the vocabulary.
@@ -1255,14 +1281,15 @@ def save(self, *args, **kwargs):
             Load object.
 
         """
-        # don't bother storing the cached normalized vectors
-        ignore_attrs = [
-            'buckets_word',
-            'hash2index',
-        ]
-        kwargs['ignore'] = kwargs.get('ignore', ignore_attrs)
         super(FastTextKeyedVectors, self).save(*args, **kwargs)
 
+    def _save_specials(self, fname, separately, sep_limit, ignore, pickle_protocol, compress, subname):
+        """Arrange any special handling for the gensim.utils.SaveLoad protocol"""
+        # don't save properties that are merely calculated from others
+        ignore = set(ignore).union(['buckets_word', 'vectors', ])
+        return super(FastTextKeyedVectors, self)._save_specials(
+            fname, separately, sep_limit, ignore, pickle_protocol, compress, subname)
+
     def get_vector(self, word, norm=False):
         """Get `word` representations in vector space, as a 1D numpy array.