From 89343ce75c887cad0334df495c9029d5716ef663 Mon Sep 17 00:00:00 2001
From: "Arun S. Maiya" <arun@maiya.net>
Date: Sat, 27 Jan 2024 14:32:10 -0500
Subject: [PATCH] black

---
 .pre-commit-config.yaml            |  2 +-
 ktrain/imports.py                  |  6 +++---
 ktrain/lroptimize/optimization.py  | 16 +++++++++-------
 ktrain/text/ner/anago/callbacks.py |  1 +
 ktrain/text/ner/anago/models.py    |  1 +
 ktrain/text/ner/anago/tagger.py    |  1 +
 ktrain/text/ner/anago/utils.py     |  1 -
 ktrain/text/qa/qa_finetuner.py     |  8 +++++---
 8 files changed, 21 insertions(+), 15 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index ddbe97311..6d1551fae 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/ambv/black
-    rev: 23.1.0
+    rev: 24.1.0
     hooks:
       - id: black
         #language_version: python3.6 
diff --git a/ktrain/imports.py b/ktrain/imports.py
index 3ab644c44..321307f3b 100644
--- a/ktrain/imports.py
+++ b/ktrain/imports.py
@@ -10,9 +10,9 @@
 
 from packaging import version
 
-os.environ[
-    "NUMEXPR_MAX_THREADS"
-] = "8"  # suppress warning from NumExpr on machines with many CPUs
+os.environ["NUMEXPR_MAX_THREADS"] = (
+    "8"  # suppress warning from NumExpr on machines with many CPUs
+)
 
 # TensorFlow
 SUPPRESS_DEP_WARNINGS = strtobool(os.environ.get("SUPPRESS_DEP_WARNINGS", "1"))
diff --git a/ktrain/lroptimize/optimization.py b/ktrain/lroptimize/optimization.py
index 1c97d3115..fcd4db2c6 100644
--- a/ktrain/lroptimize/optimization.py
+++ b/ktrain/lroptimize/optimization.py
@@ -346,14 +346,16 @@ def __call__(self, gradients):
             _ = self.step  # Create the step variable.
             self._gradients.extend(
                 [
-                    tf.Variable(
-                        tf.zeros_like(gradient),
-                        trainable=False,
-                        synchronization=tf.VariableSynchronization.ON_READ,
-                        aggregation=tf.VariableAggregation.ONLY_FIRST_REPLICA,
+                    (
+                        tf.Variable(
+                            tf.zeros_like(gradient),
+                            trainable=False,
+                            synchronization=tf.VariableSynchronization.ON_READ,
+                            aggregation=tf.VariableAggregation.ONLY_FIRST_REPLICA,
+                        )
+                        if gradient is not None
+                        else gradient
                     )
-                    if gradient is not None
-                    else gradient
                     for gradient in gradients
                 ]
             )
diff --git a/ktrain/text/ner/anago/callbacks.py b/ktrain/text/ner/anago/callbacks.py
index 0b6a8cfb7..4fbf3d9c0 100644
--- a/ktrain/text/ner/anago/callbacks.py
+++ b/ktrain/text/ner/anago/callbacks.py
@@ -1,6 +1,7 @@
 """
 Custom callbacks.
 """
+
 from ....imports import *
 from .. import metrics
 
diff --git a/ktrain/text/ner/anago/models.py b/ktrain/text/ner/anago/models.py
index 7a66f9e47..62f511adb 100644
--- a/ktrain/text/ner/anago/models.py
+++ b/ktrain/text/ner/anago/models.py
@@ -1,6 +1,7 @@
 """
 Model definition.
 """
+
 from .... import utils as U
 from ....imports import *
 
diff --git a/ktrain/text/ner/anago/tagger.py b/ktrain/text/ner/anago/tagger.py
index e738f4aee..726e0ce37 100644
--- a/ktrain/text/ner/anago/tagger.py
+++ b/ktrain/text/ner/anago/tagger.py
@@ -1,6 +1,7 @@
 """
 Model API.
 """
+
 from ....imports import *
 from .. import metrics
 
diff --git a/ktrain/text/ner/anago/utils.py b/ktrain/text/ner/anago/utils.py
index 4acf3bdcb..20343dec0 100644
--- a/ktrain/text/ner/anago/utils.py
+++ b/ktrain/text/ner/anago/utils.py
@@ -2,7 +2,6 @@
 Utility functions.
 """
 
-
 from ....imports import *
 
 
diff --git a/ktrain/text/qa/qa_finetuner.py b/ktrain/text/qa/qa_finetuner.py
index 35b157dae..2835d2ad4 100644
--- a/ktrain/text/qa/qa_finetuner.py
+++ b/ktrain/text/qa/qa_finetuner.py
@@ -69,9 +69,11 @@ def convert_dataset_for_tensorflow(
 
     def densify_ragged_batch(features, label=None):
         features = {
-            feature: ragged_tensor.to_tensor(shape=batch_shape[feature])
-            if feature in tensor_keys
-            else ragged_tensor
+            feature: (
+                ragged_tensor.to_tensor(shape=batch_shape[feature])
+                if feature in tensor_keys
+                else ragged_tensor
+            )
             for feature, ragged_tensor in features.items()
         }
         if label is None: