Ported model cli from v1

spacy/__main__.py

@@ -3,15 +3,21 @@ from __future__ import print_function
 # NB! This breaks in plac on Python 2!!
 #from __future__ import unicode_literals
 
-
 if __name__ == '__main__':
     import plac
     import sys
-    from spacy.cli import download, link, info, package, train, convert
+    from spacy.cli import download, link, info, package, train, convert, model
     from spacy.util import prints
 
-    commands = {'download': download, 'link': link, 'info': info, 'train': train,
+    commands = {
-                'convert': convert, 'package': package}
+        'download': download,
+        'link': link,
+        'info': info,
+        'train': train,
+        'convert': convert,
+        'package': package,
+        'model': model
+    }
     if len(sys.argv) == 1:
         prints(', '.join(commands), title="Available commands", exits=1)
     command = sys.argv.pop(1)
@@ -19,5 +25,7 @@ if __name__ == '__main__':
     if command in commands:
         plac.call(commands[command])
     else:
-        prints("Available: %s" % ', '.join(commands),
+        prints(
-               title="Unknown command: %s" % command, exits=1)
+            "Available: %s" % ', '.join(commands),
+            title="Unknown command: %s" % command,
+            exits=1)

spacy/cli/__init__.py

@@ -4,3 +4,4 @@ from .link import link
 from .package import package
 from .train import train
 from .convert import convert
+from .model import model

spacy/cli/model.py

@@ -0,0 +1,119 @@
+# coding: utf8
+from __future__ import unicode_literals
+
+import gzip
+import math
+from ast import literal_eval
+from pathlib import Path
+from preshed.counter import PreshCounter
+
+import spacy
+from ..compat import fix_text
+from .. import util
+
+
+def model(cmd, lang, model_dir, freqs_data, clusters_data, vectors_data):
+    model_path = Path(model_dir)
+    freqs_path = Path(freqs_data)
+    clusters_path = Path(clusters_data) if clusters_data else None
+    vectors_path = Path(vectors_data) if vectors_data else None
+
+    check_dirs(freqs_path, clusters_path, vectors_path)
+    # vocab = util.get_lang_class(lang).Defaults.create_vocab()
+    nlp = spacy.blank(lang)
+    vocab = nlp.vocab
+    probs, oov_prob = read_probs(freqs_path)
+    clusters = read_clusters(clusters_path) if clusters_path else {}
+    populate_vocab(vocab, clusters, probs, oov_prob)
+    create_model(model_path, nlp)
+
+
+def create_model(model_path, model):
+    if not model_path.exists():
+        model_path.mkdir()
+    model.to_disk(model_path.as_posix())
+
+
+def read_probs(freqs_path, max_length=100, min_doc_freq=5, min_freq=200):
+    counts = PreshCounter()
+    total = 0
+    freqs_file = check_unzip(freqs_path)
+    for i, line in enumerate(freqs_file):
+        freq, doc_freq, key = line.rstrip().split('\t', 2)
+        freq = int(freq)
+        counts.inc(i + 1, freq)
+        total += freq
+    counts.smooth()
+    log_total = math.log(total)
+    freqs_file = check_unzip(freqs_path)
+    probs = {}
+    for line in freqs_file:
+        freq, doc_freq, key = line.rstrip().split('\t', 2)
+        doc_freq = int(doc_freq)
+        freq = int(freq)
+        if doc_freq >= min_doc_freq and freq >= min_freq and len(
+                key) < max_length:
+            word = literal_eval(key)
+            smooth_count = counts.smoother(int(freq))
+            probs[word] = math.log(smooth_count) - log_total
+    oov_prob = math.log(counts.smoother(0)) - log_total
+    return probs, oov_prob
+
+
+def read_clusters(clusters_path):
+    clusters = {}
+    with clusters_path.open() as f:
+        for line in f:
+            try:
+                cluster, word, freq = line.split()
+                word = fix_text(word)
+            except ValueError:
+                continue
+            # If the clusterer has only seen the word a few times, its
+            # cluster is unreliable.
+            if int(freq) >= 3:
+                clusters[word] = cluster
+            else:
+                clusters[word] = '0'
+    # Expand clusters with re-casing
+    for word, cluster in list(clusters.items()):
+        if word.lower() not in clusters:
+            clusters[word.lower()] = cluster
+        if word.title() not in clusters:
+            clusters[word.title()] = cluster
+        if word.upper() not in clusters:
+            clusters[word.upper()] = cluster
+    return clusters
+
+
+def populate_vocab(vocab, clusters, probs, oov_prob):
+    for word, prob in reversed(
+            sorted(list(probs.items()), key=lambda item: item[1])):
+        lexeme = vocab[word]
+        lexeme.prob = prob
+        lexeme.is_oov = False
+        # Decode as a little-endian string, so that we can do & 15 to get
+        # the first 4 bits. See _parse_features.pyx
+        if word in clusters:
+            lexeme.cluster = int(clusters[word][::-1], 2)
+        else:
+            lexeme.cluster = 0
+
+
+def check_unzip(file_path):
+    file_path_str = file_path.as_posix()
+    if file_path_str.endswith('gz'):
+        return gzip.open(file_path_str)
+    else:
+        return file_path.open()
+
+
+def check_dirs(freqs_data, clusters_data, vectors_data):
+    if not freqs_data.is_file():
+        util.sys_exit(freqs_data.as_posix(), title="No frequencies file found")
+    if clusters_data and not clusters_data.is_file():
+        util.sys_exit(
+            clusters_data.as_posix(), title="No Brown clusters file found")
+    if vectors_data and not vectors_data.is_file():
+        util.sys_exit(
+            vectors_data.as_posix(), title="No word vectors file found")