Merge pull request #87 from borisdayma/feat-text

dalle_mini/text.py

@@ -0,0 +1,268 @@
+"""
+Utilities for processing text.
+"""
+
+import requests
+from pathlib import Path
+from unidecode import unidecode
+import re, math, random, html
+
+
+WIKI_STATS_URL = "https://github.com/borisdayma/wikipedia-word-frequency/raw/feat-update/results/enwiki-20210820-words-frequency.txt"
+WIKI_STATS_LOCAL = Path(WIKI_STATS_URL).parts[-1]
+
+# based on wiki word occurence
+person_token = [("a person", 282265), ("someone", 121194), ("somebody", 12219)]
+temp_token = "xtokx"  # avoid repeating chars
+
+
+def get_wiki_file():
+    if not Path(WIKI_STATS_LOCAL).exists():
+        r = requests.get(WIKI_STATS_URL, stream=True)
+        with open(WIKI_STATS_LOCAL, "wb") as fd:
+            for chunk in r.iter_content(chunk_size=128):
+                fd.write(chunk)
+    return WIKI_STATS_LOCAL
+
+
+class HashtagProcessor:
+    # Adapted from wordninja library
+    # We use our wikipedia word count + a good heuristic to make it work
+    def __init__(self):
+        self._word_cost = (
+            l.split()[0] for l in Path(get_wiki_file()).read_text().splitlines()
+        )
+        self._word_cost = {
+            str(k): math.log(float(i + 1)) for i, k in enumerate(self._word_cost)
+        }
+        self._max_word = max(len(x) for x in self._word_cost.keys())
+        self._SPLIT_RE = re.compile("[^a-zA-Z0-9']+")
+
+    def __call__(self, s):
+        """Uses dynamic programming to infer the location of spaces in a string without spaces."""
+        l = [self._split(x) for x in self._SPLIT_RE.split(s)]
+        return " ".join([item for sublist in l for item in sublist])
+
+    def _split(self, s):
+        # Find the best match for the i first characters, assuming cost has
+        # been built for the i-1 first characters.
+        # Returns a pair (match_cost, match_length).
+        def best_match(i):
+            candidates = enumerate(reversed(cost[max(0, i - self._max_word) : i]))
+            return min(
+                (c + self._word_cost.get(s[i - k - 1 : i].lower(), 9e999), k + 1)
+                for k, c in candidates
+            )
+
+        # Build the cost array
+        cost = [0]
+        for i in range(1, len(s) + 1):
+            c, k = best_match(i)
+            cost.append(c)
+
+        # Backtrack to recover the minimal-cost string.
+        out = []
+        i = len(s)
+        while i > 0:
+            c, k = best_match(i)
+            assert c == cost[i]
+            newToken = True
+            if not s[i - k : i] == "'":  # ignore a lone apostrophe
+                if len(out) > 0:
+                    # re-attach split 's and split digits
+                    if out[-1] == "'s" or (
+                        s[i - 1].isdigit() and out[-1][0].isdigit()
+                    ):  # digit followed by digit
+                        out[-1] = (
+                            s[i - k : i] + out[-1]
+                        )  # combine current token with previous token
+                        newToken = False
+
+            if newToken:
+                out.append(s[i - k : i])
+
+            i -= k
+
+        return reversed(out)
+
+
+def replace_person_token(t):
+    "Used for CC12M"
+    t = re.sub("<person>([,\s]*(and)*[,\s]*<person>)+", " people ", t)
+    while "<person>" in t:
+        t = t.replace(
+            "<person>", f" {random.choices(*tuple(zip(*person_token)))[0]} ", 1
+        )
+    return t
+
+
+def fix_html(t):
+    "Adapted from fastai"
+    t = (
+        t.replace("#39;", "'")
+        .replace("&amp;", "&")
+        .replace("amp;", "&")
+        .replace("#146;", "'")
+        .replace("nbsp;", " ")
+        .replace("#36;", "$")
+        .replace("\\n", "\n")
+        .replace("quot;", "'")
+        .replace("<br />", "\n")
+        .replace('\\"', '"')
+        .replace("<unk>", " ")
+        .replace(" @.@ ", ".")
+        .replace(" @-@ ", "-")
+    )
+    return html.unescape(t)
+
+
+def replace_punctuation_with_commas(t):
+    return re.sub("""([()[\].,|:;?!=+~\-])""", ",", t)
+
+
+def simplify_quotes(t):
+    return re.sub("""['"`]""", ' " ', t)
+
+
+def merge_quotes(t):
+    return re.sub('(\s*"+\s*)+', ' " ', t)
+
+
+def remove_comma_numbers(t):
+    def _f(t):
+        return re.sub("(\d),(\d{3})", r"\1\2", t)
+
+    return _f(_f(t))
+
+
+def pre_process_dot_numbers(t):
+    return re.sub("(\d)\.(\d)", fr"\1{temp_token}dot{temp_token}\2", t)
+
+
+def post_process_dot_numbers(t):
+    return re.sub(f"{temp_token}dot{temp_token}", ".", t)
+
+
+def pre_process_quotes(t):
+    # allows quotes only for 's, 't, 'd, 'm, 'll, 're, 've
+    return re.sub(
+        r"'(?=([stdm]|(ll)|(re)|(ve)|(ll))\b)", fr"{temp_token}quote{temp_token}", t
+    )
+
+
+def post_process_quotes(t):
+    return re.sub(f"{temp_token}quote{temp_token}", "'", t)
+
+
+def merge_commas(t):
+    return re.sub("(\s*,+\s*)+", ", ", t)
+
+
+def add_space_after_commas(t):
+    return re.sub(",", ", ", t)
+
+
+def handle_special_chars(t):
+    "Handle special characters"
+    # replace "-" with a space when between words without space
+    t = re.sub("([a-zA-Z])-([a-zA-Z])", r"\1 \2", t)
+    # always add space around &
+    return re.sub("&", " & ", t)
+
+
+def expand_hashtags(t, hashtag_processor):
+    "Remove # and try to split words"
+    return re.sub("#(\w+)", lambda m: hashtag_processor(m.group(1)), t)
+
+
+_re_ignore_chars = """[_#\/\\%]"""
+
+
+def ignore_chars(t):
+    "Ignore useless characters"
+    return re.sub(_re_ignore_chars, " ", t)
+
+
+def remove_extra_spaces(t):
+    "Remove extra spaces (including \t and \n)"
+    return re.sub("\s+", " ", t)
+
+
+def remove_repeating_chars(t):
+    "If the same character is present 4+ times (not 3 because of roman 'VIII'), replace with single instance"
+    return re.sub(r"(\D)(\1{3,})", r"\1", t)
+
+
+def remove_urls(t):
+    return re.sub(r"http\S+", "", t)
+
+
+def remove_html_tags(t):
+    return re.sub("<[^<]+?>", "", t)
+
+
+def remove_first_last_commas(t):
+    t = t.strip()
+    t = t[:-1] if t and t[-1] == "," else t
+    t = t[1:] if t and t[0] == "," else t
+    return t.strip()
+
+
+def remove_wiki_ref(t):
+    t = re.sub(r"\A\s*\[\d+\]", "", t)
+    return re.sub(r"\[\d+\]\s*\Z", "", t)
+
+
+class TextNormalizer:
+    "Normalize text"
+
+    def __init__(self):
+        self._hashtag_processor = HashtagProcessor()
+
+    def __call__(self, t, clip=False):
+        # fix html
+        t = fix_html(t)
+        if not clip:
+            # decode and simplify text: see unidecode library
+            t = unidecode(t)
+        # lower case
+        t = t.lower()
+        # replace <PERSON> (for CC12M)
+        t = replace_person_token(t)
+        # remove wiki reference (for WIT)
+        t = remove_wiki_ref(t)
+        # remove html tags
+        t = remove_html_tags(t)
+        # remove urls
+        t = remove_urls(t)
+        # remove commas in numbers
+        t = remove_comma_numbers(t)
+        if not clip:
+            # handle dots in numbers and quotes - Part 1
+            t = pre_process_dot_numbers(t)
+            t = pre_process_quotes(t)
+            # handle special characters
+            t = handle_special_chars(t)
+            # handle hashtags
+            t = expand_hashtags(t, self._hashtag_processor)
+            # ignore useless characters
+            t = ignore_chars(t)
+            # simplify quotes
+            t = simplify_quotes(t)
+            # all punctuation becomes commas
+            t = replace_punctuation_with_commas(t)
+            # handle dots in numbers and quotes - Part 2
+            t = post_process_dot_numbers(t)
+            t = post_process_quotes(t)
+            # handle repeating characters
+            t = remove_repeating_chars(t)
+            # merge commas
+            t = merge_commas(t)
+            # merge quotes
+            t = merge_quotes(t)
+        # remove multiple spaces
+        t = remove_extra_spaces(t)
+        # remove first and last comma
+        t = remove_first_last_commas(t)
+        # always start with a space
+        return f" {t}" if not clip else t