[pre-commit.ci] pre-commit autoupdate

.github/workflows/check-formatting.yml

@@ -13,10 +13,10 @@ jobs:
   build:
     if: contains(fromJson('["wenh06", "DeepPSP"]'), github.repository_owner)
 
-    runs-on: ubuntu-20.04
+    runs-on: ubuntu-22.04
     strategy:
       matrix:
-        python-version: [3.8, 3.9]
+        python-version: ["3.10", "3.12"]
 
     steps:
     - uses: actions/checkout@v4
@@ -28,7 +28,5 @@ jobs:
       run: |
         python -m pip install --upgrade pip setuptools wheel
         python -m pip install -r requirements.txt
-        python -m pip install importlib-metadata==4.8.3 # Testing packages
-        python -m pip install torch==1.10.0+cu113 -f https://download.pytorch.org/whl/torch_stable.html
     - name: Check code format with pre-commit
       uses: pre-commit/action@v3.0.1

.pre-commit-config.yaml

@@ -4,22 +4,22 @@ fail_fast: false
 
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v5.0.0
+    rev: v6.0.0
     hooks:
       - id: end-of-file-fixer
       - id: trailing-whitespace
-  - repo: https://github.com/psf/black
-    rev: 24.8.0
+  - repo: https://github.com/psf/black-pre-commit-mirror
+    rev: 26.3.1
     hooks:
       - id: black
         args: [--line-length=128, --verbose]
   - repo: https://github.com/PyCQA/flake8
-    rev: 7.1.1
+    rev: 7.3.0
     hooks:
       - id: flake8
-        args: [--max-line-length=128, '--exclude=./.*,build,dist,official*,torch_ecg,references,*.ipynb', '--ignore=E501,W503,E203,F841,E402,E231,E731', --count, --statistics, --show-source]
+        args: [--max-line-length=128, '--exclude=./.*,build,dist,official*,torch_ecg,references,*.ipynb', '--ignore=E501,W503,E203,F841,E402,E231,E731,E226,E225', --count, --statistics, --show-source]
   - repo: https://github.com/pycqa/isort
-    rev: 5.13.2
+    rev: 8.0.1
     hooks:
       - id: isort
         args: [--profile=black, --line-length=128]

cfg.py

@@ -1,5 +1,4 @@
-"""
-"""
+""" """
 
 import os
 from copy import deepcopy

data_reader.py

@@ -1,6 +1,5 @@
 # -*- coding: utf-8 -*-
-"""
-"""
+""" """
 
 import json
 import logging

dataset.py

@@ -1252,14 +1252,10 @@ def _train_test_split(self, train_ratio: float = 0.8, force_recompute: bool = Fa
             with open(test_file_1, "w") as f1, open(test_file_2, "w") as f2:
                 json.dump(test_set, f1, ensure_ascii=False)
                 json.dump(test_set, f2, ensure_ascii=False)
-            print(
-                nildent(
-                    f"""
+            print(nildent(f"""
                 train set saved to \n\042{train_file_1}\042and\n\042{train_file_2}\042
                 test set saved to \n\042{test_file_1}\042and\n\042{test_file_2}\042
-                """
-                )
-            )
+                """))
         else:
             with open(train_file, "r") as f:
                 train_set = json.load(f)

gather_results.py

@@ -1,5 +1,4 @@
-"""
-"""
+""" """
 
 import glob
 import json

requirements.txt

@@ -1,18 +1,18 @@
-numpy==1.22.0
-scipy==1.6.1
-joblib==1.2.0
+numpy
+scipy
+joblib
 # Cython==0.29.10
-pandas==1.2.2
-scikit-learn==0.24.1
-wfdb==3.2.0
+pandas<3.0.0
+scikit-learn
+wfdb
 # biosppy==0.6.1
 biosppy
 opencv-python
 # tensorflow==1.15.2
 # keras==2.3.1
 packaging
 easydict
-torch==1.8.0  # see Dockerfile
+torch
 torchsummary
 tensorboardX
 tqdm

sample_data/__init__.py

@@ -1,5 +1,4 @@
-"""
-"""
+""" """
 
 import glob
 import os

test_entry.py

@@ -1,5 +1,4 @@
-"""
-"""
+""" """
 
 import glob
 import os

trainer.py

@@ -1,5 +1,4 @@
-"""
-"""
+""" """
 
 import argparse
 import logging
@@ -149,8 +148,7 @@ def train(
         comment=f"OPT_{config.task}_{_model.__name__}{cnn_name}{rnn_name}{attn_name}_{config.train_optimizer}_LR_{lr}_BS_{batch_size}",
     )
 
-    msg = textwrap.dedent(
-        f"""
+    msg = textwrap.dedent(f"""
         Starting training:
         ------------------
         Task:            {config.task}
@@ -163,8 +161,7 @@ def train(
         Optimizer:       {config.train_optimizer}
         Dataset classes: {train_dataset.all_classes}
         ---------------------------------------------------
-        """
-    )
+        """)
 
     if logger:
         logger.info(msg)
@@ -347,15 +344,13 @@ def train(
             else:
                 eval_train_msg = ""
             for k, v in eval_res.items():
-                msg = textwrap.dedent(
-                    f"""
+                msg = textwrap.dedent(f"""
                     Train epoch_{epoch + 1}:
                     --------------------
                     train/epoch_loss:        {epoch_loss}{eval_train_msg}
                     test/task_metric_{k}:    {v}
                     ---------------------------------
-                    """
-                )
+                    """)
             if logger:
                 logger.info(msg)
             else:
@@ -378,12 +373,10 @@ def train(
                         print(msg)
                     break
 
-            msg = textwrap.dedent(
-                f"""
+            msg = textwrap.dedent(f"""
                 best metric = {best_metric},
                 obtained at epoch {best_epoch}
-            """
-            )
+            """)
             if logger:
                 logger.info(msg)
             else:

utils/__init__.py

@@ -1,5 +1,4 @@
-"""
-"""
+""" """
 
 import os
 import sys

utils/misc.py

@@ -1,5 +1,4 @@
-"""
-"""
+""" """
 
 import datetime
 import json

utils/scoring_metrics_test.py

@@ -1,5 +1,4 @@
-"""
-"""
+""" """
 
 import argparse
 import glob
@@ -165,14 +164,10 @@ def run_single_test(rec: str, classes: Optional[List[str]] = None, verbose: bool
         return
 
     print(f"  {os.path.basename(rec)} starts ".center(30, "-"))
-    print(
-        textwrap.dedent(
-            f"""
+    print(textwrap.dedent(f"""
         record = {os.path.basename(rec)},
         class = {header.comments[0]},
-        """
-        )
-    )
+        """))
 
     custom_onset_scoring_mask, custom_offset_scoring_mask = gen_endpoint_score_mask(
         siglen=header.sig_len,

utils/utils_interval.py

@@ -10,6 +10,7 @@
     2. distinguish openness and closedness
 
 """
+
 import time
 from copy import deepcopy
 from numbers import Real