easy fixes

pyproject.toml

@@ -50,7 +50,7 @@ select = [
     # Pyflakes
     "F",
     # pyupgrade
-#    "UP",
+    "UP",
     # flake8-bugbear
 #    "B",
     # flake8-simplify

tensorboardX/embedding.py

@@ -44,14 +44,9 @@ def make_tsv(metadata, save_path, metadata_header=None):
 
     named_path = os.path.join(save_path, 'metadata.tsv')
 
-    if sys.version_info[0] == 3:
-        with open(named_path, 'w', encoding='utf8') as f:
-            for x in metadata:
-                f.write(x + '\n')
-    else:
-        with open(named_path, 'wb') as f:
-            for x in metadata:
-                f.write((x + '\n').encode('utf-8'))
+    with open(named_path, 'w', encoding='utf8') as f:
+        for x in metadata:
+            f.write(x + '\n')
     maybe_upload_file(named_path)
 
 
@@ -97,17 +92,16 @@ def append_pbtxt(metadata, label_img, save_path, subdir, global_step, tag):
     with open(named_path, 'a') as f:
         # step = os.path.split(save_path)[-1]
         f.write('embeddings {\n')
-        f.write('tensor_name: "{}:{}"\n'.format(
-            tag, str(global_step).zfill(5)))
+        f.write(f'tensor_name: "{tag}:{str(global_step).zfill(5)}"\n')
         f.write('tensor_path: "{}"\n'.format(join(subdir, 'tensors.tsv')))
         if metadata is not None:
             f.write('metadata_path: "{}"\n'.format(
                 join(subdir, 'metadata.tsv')))
         if label_img is not None:
             f.write('sprite {\n')
             f.write('image_path: "{}"\n'.format(join(subdir, 'sprite.png')))
-            f.write('single_image_dim: {}\n'.format(label_img.shape[3]))
-            f.write('single_image_dim: {}\n'.format(label_img.shape[2]))
+            f.write(f'single_image_dim: {label_img.shape[3]}\n')
+            f.write(f'single_image_dim: {label_img.shape[2]}\n')
             f.write('}\n')
         f.write('}\n')
     maybe_upload_file(named_path)

tensorboardX/event_file_writer.py

@@ -14,7 +14,6 @@
 # ==============================================================================
 """Writes events to disk in a logdir."""
 
-from __future__ import absolute_import, division, print_function
 
 import multiprocessing
 import os
@@ -27,7 +26,7 @@
 from .record_writer import RecordWriter, directory_check
 
 
-class EventsWriter(object):
+class EventsWriter:
     '''Writes `Event` protocol buffers to an event file.'''
 
     def __init__(self, file_prefix, filename_suffix=''):
@@ -75,7 +74,7 @@ def close(self):
         return return_value
 
 
-class EventFileWriter(object):
+class EventFileWriter:
     """Writes `Event` protocol buffers to an event file.
 
     The `EventFileWriter` class creates an event file in the specified directory,

tensorboardX/global_writer.py

@@ -7,7 +7,7 @@
 _writer = None
 
 
-class GlobalSummaryWriter(object):
+class GlobalSummaryWriter:
     """A class that implements an event writer that supports concurrent logging and global logging across
     different modules.
 

tensorboardX/record_writer.py

@@ -61,7 +61,7 @@ def open_file(path):
         return open(path, 'wb')
 
 
-class S3RecordWriter(object):
+class S3RecordWriter:
     """Writes tensorboard protocol buffer files to S3."""
 
     def __init__(self, path):
@@ -99,7 +99,7 @@ def close(self):
         self.closed = True
 
 
-class S3RecordWriterFactory(object):
+class S3RecordWriterFactory:
     """Factory for event protocol buffer files to S3."""
 
     def open(self, path):
@@ -114,7 +114,7 @@ def directory_check(self, path):
 register_writer_factory("s3", S3RecordWriterFactory())
 
 
-class GCSRecordWriter(object):
+class GCSRecordWriter:
     """Writes tensorboard protocol buffer files to Google Cloud Storage."""
 
     def __init__(self, path):
@@ -158,7 +158,7 @@ def close(self):
         self.flush()
 
 
-class GCSRecordWriterFactory(object):
+class GCSRecordWriterFactory:
     """Factory for event protocol buffer files to Google Cloud Storage."""
 
     def open(self, path):
@@ -173,7 +173,7 @@ def directory_check(self, path):
 register_writer_factory("gs", GCSRecordWriterFactory())
 
 
-class RecordWriter(object):
+class RecordWriter:
     def __init__(self, path):
         self._name_to_tf_name = {}
         self._tf_names = set()

tensorboardX/summary.py

@@ -1,4 +1,3 @@
-from __future__ import absolute_import, division, print_function
 
 import logging
 import os
@@ -570,7 +569,7 @@ def _get_tensor_summary(tag, tensor, content_type, json_config):
                              TensorShapeProto.Dim(size=tensor.shape[2]),
                          ]))
     tensor_summary = Summary.Value(
-        tag='{}_{}'.format(tag, content_type),
+        tag=f'{tag}_{content_type}',
         tensor=tensor,
         metadata=smd,
     )

tensorboardX/torchvis.py

@@ -1,4 +1,3 @@
-from __future__ import absolute_import, division, print_function, unicode_literals
 
 import gc
 import time

tensorboardX/utils.py

@@ -93,10 +93,10 @@ def make_grid(I, ncols=8):
 
 def convert_to_NTCHW(tensor, input_format):
     assert len(input_format) == 5, "Only 5D tensor is supported."
-    assert len(set(input_format)) == len(input_format), "You can not use the same dimension shorthand twice. \
-        input_format: {}".format(input_format)
-    assert len(tensor.shape) == len(input_format), "size of input tensor and input format are different. \
-        tensor shape: {}, input_format: {}".format(tensor.shape, input_format)
+    assert len(set(input_format)) == len(input_format), f"You can not use the same dimension shorthand twice. \
+        input_format: {input_format}"
+    assert len(tensor.shape) == len(input_format), f"size of input tensor and input format are different. \
+        tensor shape: {tensor.shape}, input_format: {input_format}"
     input_format = input_format.upper()
     index = [input_format.find(c) for c in 'NTCHW']
     tensor_NTCHW = tensor.transpose(index)
@@ -105,10 +105,10 @@ def convert_to_NTCHW(tensor, input_format):
 
 def convert_to_HWC(tensor, input_format):  # tensor: numpy array
     import numpy as np
-    assert len(set(input_format)) == len(input_format), "You can not use the same dimension shorthand twice. \
-        input_format: {}".format(input_format)
-    assert len(tensor.shape) == len(input_format), "size of input tensor and input format are different. \
-        tensor shape: {}, input_format: {}".format(tensor.shape, input_format)
+    assert len(set(input_format)) == len(input_format), f"You can not use the same dimension shorthand twice. \
+        input_format: {input_format}"
+    assert len(tensor.shape) == len(input_format), f"size of input tensor and input format are different. \
+        tensor shape: {tensor.shape}, input_format: {input_format}"
     input_format = input_format.upper()
 
     if len(input_format) == 4:

tensorboardX/visdom_writer.py

@@ -61,7 +61,7 @@ def add_scalar(self, tag, scalar_value, global_step=None, main_tag='default'):
         exists = self.scalar_dict[main_tag].get(tag) is not None
         self.scalar_dict[main_tag][tag] = self.scalar_dict[main_tag][tag] + \
             [scalar_value] if exists else [scalar_value]
-        plot_name = '{}-{}'.format(main_tag, tag)
+        plot_name = f'{main_tag}-{tag}'
         # If there is no global_step provided, follow sequential order
         x_val = len(self.scalar_dict[main_tag][tag]
                     ) if not global_step else global_step
@@ -283,7 +283,7 @@ def add_pr_curve(self, tag, labels, predictions, global_step=None, num_threshold
             Y=precision,
             name=tag,
             opts={
-                'title': 'PR Curve for {}'.format(tag),
+                'title': f'PR Curve for {tag}',
                 'xlabel': 'recall',
                 'ylabel': 'precision',
             },
@@ -316,7 +316,7 @@ def add_pr_curve_raw(self, tag, true_positive_counts,
             Y=precision,
             name=tag,
             opts={
-                'title': 'PR Curve for {}'.format(tag),
+                'title': f'PR Curve for {tag}',
                 'xlabel': 'recall',
                 'ylabel': 'precision',
             },

tensorboardX/writer.py

@@ -1,14 +1,13 @@
 """Provides an API for writing protocol buffers to event files to be
 consumed by TensorBoard for visualization."""
 
-from __future__ import absolute_import, division, print_function
 
 import atexit
 import json
 import logging
 import os
 import time
-from typing import Dict, List, Optional, Union
+from typing import Optional, Union
 
 import numpy
 
@@ -46,7 +45,7 @@
     pass
 
 
-class DummyFileWriter(object):
+class DummyFileWriter:
     """A fake file writer that writes nothing to the disk.
     """
 
@@ -79,7 +78,7 @@ def reopen(self):
         return
 
 
-class FileWriter(object):
+class FileWriter:
     """Writes protocol buffers to event files to be consumed by TensorBoard.
 
     The `FileWriter` class provides a mechanism to create an event file in a
@@ -216,7 +215,7 @@ def reopen(self):
         self.event_writer.reopen()
 
 
-class SummaryWriter(object):
+class SummaryWriter:
     """Writes entries directly to event files in the logdir to be
     consumed by TensorBoard.
 
@@ -361,8 +360,8 @@ def _get_comet_logger(self):
 
     def add_hparams(
             self,
-            hparam_dict: Dict[str, Union[bool, str, float, int]],
-            metric_dict: Dict[str, float],
+            hparam_dict: dict[str, Union[bool, str, float, int]],
+            metric_dict: dict[str, float],
             name: Optional[str] = None,
             global_step: Optional[int] = None):
         """Add a set of hyperparameters to be compared in tensorboard.
@@ -448,7 +447,7 @@ def add_scalar(
     def add_scalars(
             self,
             main_tag: str,
-            tag_scalar_dict: Dict[str, float],
+            tag_scalar_dict: dict[str, float],
             global_step: Optional[int] = None,
             walltime: Optional[float] = None):
         """Adds many scalar data to summary.
@@ -742,7 +741,7 @@ def add_image_with_boxes(
             global_step: Optional[int] = None,
             walltime: Optional[float] = None,
             dataformats: Optional[str] = 'CHW',
-            labels: Optional[List[str]] = None,
+            labels: Optional[list[str]] = None,
             **kwargs):
         """Add image and draw bounding boxes on the image.
 
@@ -1104,7 +1103,7 @@ def add_pr_curve_raw(
 
     def add_custom_scalars_multilinechart(
             self,
-            tags: List[str],
+            tags: list[str],
             category: str = 'default',
             title: str = 'untitled'):
         """Shorthand for creating multilinechart. Similar to ``add_custom_scalars()``, but the only necessary argument
@@ -1122,7 +1121,7 @@ def add_custom_scalars_multilinechart(
 
     def add_custom_scalars_marginchart(
             self,
-            tags: List[str],
+            tags: list[str],
             category: str = 'default',
             title: str = 'untitled'):
         """Shorthand for creating marginchart. Similar to ``add_custom_scalars()``, but the only necessary argument
@@ -1141,7 +1140,7 @@ def add_custom_scalars_marginchart(
 
     def add_custom_scalars(
             self,
-            layout: Dict[str, Dict[str, List]]):
+            layout: dict[str, dict[str, list]]):
         """Create special chart by collecting charts tags in 'scalars'. Note that this function can only be called once
         for each SummaryWriter() object. Because it only provides metadata to tensorboard, the function can be called
         before or after the training loop. See ``examples/demo_custom_scalars.py`` for more.

tensorboardX/x2num.py

@@ -1,5 +1,4 @@
 # DO NOT alter/distruct/free input object !
-from __future__ import absolute_import, division, print_function
 
 import logging
 
@@ -31,7 +30,7 @@ def make_np(x):
     if 'jax' in str(type(x)):
         return check_nan(np.array(x))
     raise NotImplementedError(
-        'Got {}, but expected numpy array or torch tensor.'.format(type(x)))
+        f'Got {type(x)}, but expected numpy array or torch tensor.')
 
 
 def prepare_pytorch(x):