Merge pull request nltk#3217 from purificant/upgrade_pre_commit

upgrade automated code checks

Author: stevenbird

.pre-commit-config.yaml

@@ -1,14 +1,14 @@
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.0.1
+    rev: v4.5.0
     hooks:
       - id: fix-byte-order-marker
       - id: trailing-whitespace
       - id: end-of-file-fixer
       - id: requirements-txt-fixer
       - id: check-yaml
   - repo: https://github.com/asottile/pyupgrade
-    rev: v3.1.0
+    rev: v3.15.0
     hooks:
     - id: pyupgrade
       args: ["--py37-plus"]
@@ -27,4 +27,4 @@ repos:
         types_or: [cython, pyi, python]
         args: ['--filter-files']
         minimum_pre_commit_version: '2.9.2'
-        additional_dependencies: ['isort==5.10.1']
+        additional_dependencies: ['isort==5.13.2']

nltk/classify/naivebayes.py

@@ -168,7 +168,7 @@ def most_informative_features(self, n=100):
             features = set()
             # The max & min probability associated w/ each (fname, fval)
             # pair.  Maps (fname,fval) -> float.
-            maxprob = defaultdict(lambda: 0.0)
+            maxprob = defaultdict(float)
             minprob = defaultdict(lambda: 1.0)
 
             for (label, fname), probdist in self._feature_probdist.items():

nltk/translate/chrf_score.py

@@ -194,7 +194,7 @@ def corpus_chrf(
     num_sents = len(hypotheses)
 
     # Keep f-scores for each n-gram order separate
-    ngram_fscores = defaultdict(lambda: list())
+    ngram_fscores = defaultdict(list)
 
     # Iterate through each hypothesis and their corresponding references.
     for reference, hypothesis in zip(references, hypotheses):

nltk/translate/ibm1.py

@@ -187,7 +187,7 @@ def prob_all_alignments(self, src_sentence, trg_sentence):
         :return: Probability of t for all s in ``src_sentence``
         :rtype: dict(str): float
         """
-        alignment_prob_for_t = defaultdict(lambda: 0.0)
+        alignment_prob_for_t = defaultdict(float)
         for t in trg_sentence:
             for s in src_sentence:
                 alignment_prob_for_t[t] += self.prob_alignment_point(s, t)

nltk/translate/ibm2.py

@@ -209,7 +209,7 @@ def prob_all_alignments(self, src_sentence, trg_sentence):
         :return: Probability of t for all s in ``src_sentence``
         :rtype: dict(str): float
         """
-        alignment_prob_for_t = defaultdict(lambda: 0.0)
+        alignment_prob_for_t = defaultdict(float)
         for j in range(1, len(trg_sentence)):
             t = trg_sentence[j]
             for i in range(0, len(src_sentence)):
@@ -304,10 +304,10 @@ class Model2Counts(Counts):
     def __init__(self):
         super().__init__()
         self.alignment = defaultdict(
-            lambda: defaultdict(lambda: defaultdict(lambda: defaultdict(lambda: 0.0)))
+            lambda: defaultdict(lambda: defaultdict(lambda: defaultdict(float)))
         )
         self.alignment_for_any_i = defaultdict(
-            lambda: defaultdict(lambda: defaultdict(lambda: 0.0))
+            lambda: defaultdict(lambda: defaultdict(float))
         )
 
     def update_lexical_translation(self, count, s, t):

nltk/translate/ibm3.py

@@ -334,10 +334,10 @@ class Model3Counts(Counts):
     def __init__(self):
         super().__init__()
         self.distortion = defaultdict(
-            lambda: defaultdict(lambda: defaultdict(lambda: defaultdict(lambda: 0.0)))
+            lambda: defaultdict(lambda: defaultdict(lambda: defaultdict(float)))
         )
         self.distortion_for_any_j = defaultdict(
-            lambda: defaultdict(lambda: defaultdict(lambda: 0.0))
+            lambda: defaultdict(lambda: defaultdict(float))
         )
 
     def update_distortion(self, count, alignment_info, j, l, m):

nltk/translate/ibm4.py

@@ -457,11 +457,11 @@ class Model4Counts(Counts):
     def __init__(self):
         super().__init__()
         self.head_distortion = defaultdict(
-            lambda: defaultdict(lambda: defaultdict(lambda: 0.0))
+            lambda: defaultdict(lambda: defaultdict(float))
         )
-        self.head_distortion_for_any_dj = defaultdict(lambda: defaultdict(lambda: 0.0))
-        self.non_head_distortion = defaultdict(lambda: defaultdict(lambda: 0.0))
-        self.non_head_distortion_for_any_dj = defaultdict(lambda: 0.0)
+        self.head_distortion_for_any_dj = defaultdict(lambda: defaultdict(float))
+        self.non_head_distortion = defaultdict(lambda: defaultdict(float))
+        self.non_head_distortion_for_any_dj = defaultdict(float)
 
     def update_distortion(self, count, alignment_info, j, src_classes, trg_classes):
         i = alignment_info.alignment[j]

nltk/translate/ibm5.py

@@ -581,14 +581,12 @@ class Model5Counts(Counts):
 
     def __init__(self):
         super().__init__()
-        self.head_vacancy = defaultdict(
-            lambda: defaultdict(lambda: defaultdict(lambda: 0.0))
-        )
-        self.head_vacancy_for_any_dv = defaultdict(lambda: defaultdict(lambda: 0.0))
+        self.head_vacancy = defaultdict(lambda: defaultdict(lambda: defaultdict(float)))
+        self.head_vacancy_for_any_dv = defaultdict(lambda: defaultdict(float))
         self.non_head_vacancy = defaultdict(
-            lambda: defaultdict(lambda: defaultdict(lambda: 0.0))
+            lambda: defaultdict(lambda: defaultdict(float))
         )
-        self.non_head_vacancy_for_any_dv = defaultdict(lambda: defaultdict(lambda: 0.0))
+        self.non_head_vacancy_for_any_dv = defaultdict(lambda: defaultdict(float))
 
     def update_vacancy(self, count, alignment_info, i, trg_classes, slots):
         """

nltk/translate/ibm_model.py

@@ -521,12 +521,12 @@ class Counts:
     """
 
     def __init__(self):
-        self.t_given_s = defaultdict(lambda: defaultdict(lambda: 0.0))
-        self.any_t_given_s = defaultdict(lambda: 0.0)
+        self.t_given_s = defaultdict(lambda: defaultdict(float))
+        self.any_t_given_s = defaultdict(float)
         self.p0 = 0.0
         self.p1 = 0.0
-        self.fertility = defaultdict(lambda: defaultdict(lambda: 0.0))
-        self.fertility_for_any_phi = defaultdict(lambda: 0.0)
+        self.fertility = defaultdict(lambda: defaultdict(float))
+        self.fertility_for_any_phi = defaultdict(float)
 
     def update_lexical_translation(self, count, alignment_info, j):
         i = alignment_info.alignment[j]