Upgrade pinned version of black. (#5853)

This upgrades the pinned version of black to 22.6.0.

I encountered the following error when running `black .` on my tensorboard repo:

```
Traceback (most recent call last):
  File "/usr/local/google/home/bdubois/virtualenv/tensorboard-git/bin/black", line 8, in <module>
    sys.exit(patched_main())
  File "/usr/local/google/home/bdubois/virtualenv/tensorboard-git/lib/python3.10/site-packages/black/__init__.py", line 1322, in patched_main
    patch_click()
  File "/usr/local/google/home/bdubois/virtualenv/tensorboard-git/lib/python3.10/site-packages/black/__init__.py", line 1308, in patch_click
    from click import _unicodefun
ImportError: cannot import name '_unicodefun' from 'click' (/usr/local/google/home/bdubois/virtualenv/tensorboard-git/lib/python3.10/site-packages/click/__init__.py)
```

According to https://stackoverflow.com/questions/71673404/importerror-cannot-import-name-unicodefun-from-click thi was fixed in 22.3.0.

I choose to upgrade to the slightly more recent 22.6.0.

To test:
```
$ pip install -r tensorboard/pip_package/requirements.txt -r tensorboard/pip_package/requirements_dev.txt
$ black .
```
Examine diff using `git diff` to check if formatting changes seem reasonable. Ensure python tests pass and tensorboard builds and runs.

Author: bmd3k

tensorboard/backend/event_processing/data_provider_test.py

@@ -51,9 +51,9 @@ def setUp(self):
         with tf.summary.create_file_writer(logdir).as_default():
             for i in range(10):
                 scalar_summary.scalar(
-                    "square", i ** 2, step=2 * i, description="boxen"
+                    "square", i**2, step=2 * i, description="boxen"
                 )
-                scalar_summary.scalar("cube", i ** 3, step=3 * i)
+                scalar_summary.scalar("cube", i**3, step=3 * i)
 
         logdir = os.path.join(self.logdir, "waves")
         with tf.summary.create_file_writer(logdir).as_default():

tensorboard/compat/tensorflow_stub/dtypes.py

@@ -328,10 +328,10 @@ def size(self):
     np.uint16: (0, 65535),
     np.int8: (-128, 127),
     np.int16: (-32768, 32767),
-    np.int64: (-(2 ** 63), 2 ** 63 - 1),
-    np.uint64: (0, 2 ** 64 - 1),
-    np.int32: (-(2 ** 31), 2 ** 31 - 1),
-    np.uint32: (0, 2 ** 32 - 1),
+    np.int64: (-(2**63), 2**63 - 1),
+    np.uint64: (0, 2**64 - 1),
+    np.int32: (-(2**31), 2**31 - 1),
+    np.uint32: (0, 2**32 - 1),
     np.float32: (-1, 1),
     np.float64: (-1, 1),
 }

tensorboard/pip_package/requirements_dev.txt

@@ -25,7 +25,7 @@ moto==1.3.7
 fsspec==0.7.4
 
 # For linting
-black==21.10b0
+black==22.6.0
 flake8==3.7.8
 yamllint==1.17.0
 

tensorboard/plugins/audio/summary_test.py

@@ -87,7 +87,7 @@ def test_wav_format_roundtrip(self):
         # WAV roundtrip goes from float32 to int16 and back, so expect some
         # precision loss, but not more than 2 applications of rounding error from
         # mapping the range [-1.0, 1.0] to 2^16.
-        epsilon = 2 * 2.0 / (2 ** 16)
+        epsilon = 2 * 2.0 / (2**16)
         self.assertAllClose(audio[0], decoded, atol=epsilon)
         self.assertEqual(44100, sample_rate.numpy())
 

tensorboard/plugins/debugger_v2/debug_data_provider.py

@@ -557,22 +557,19 @@ def read_blob_sequences(
                 continue
             output[run] = dict()
             for tag in run_tag_filter.tags:
-                if (
-                    tag.startswith(
-                        (
-                            ALERTS_BLOB_TAG_PREFIX,
-                            EXECUTION_DIGESTS_BLOB_TAG_PREFIX,
-                            EXECUTION_DATA_BLOB_TAG_PREFIX,
-                            GRAPH_EXECUTION_DIGESTS_BLOB_TAG_PREFIX,
-                            GRAPH_EXECUTION_DATA_BLOB_TAG_PREFIX,
-                            GRAPH_INFO_BLOB_TAG_PREFIX,
-                            GRAPH_OP_INFO_BLOB_TAG_PREFIX,
-                            SOURCE_FILE_BLOB_TAG_PREFIX,
-                            STACK_FRAMES_BLOB_TAG_PREFIX,
-                        )
+                if tag.startswith(
+                    (
+                        ALERTS_BLOB_TAG_PREFIX,
+                        EXECUTION_DIGESTS_BLOB_TAG_PREFIX,
+                        EXECUTION_DATA_BLOB_TAG_PREFIX,
+                        GRAPH_EXECUTION_DIGESTS_BLOB_TAG_PREFIX,
+                        GRAPH_EXECUTION_DATA_BLOB_TAG_PREFIX,
+                        GRAPH_INFO_BLOB_TAG_PREFIX,
+                        GRAPH_OP_INFO_BLOB_TAG_PREFIX,
+                        SOURCE_FILE_BLOB_TAG_PREFIX,
+                        STACK_FRAMES_BLOB_TAG_PREFIX,
                     )
-                    or tag in (SOURCE_FILE_LIST_BLOB_TAG,)
-                ):
+                ) or tag in (SOURCE_FILE_LIST_BLOB_TAG,):
                     output[run][tag] = [
                         provider.BlobReference(blob_key="%s.%s" % (tag, run))
                     ]

tensorboard/plugins/graph/graphs_demo.py

@@ -53,7 +53,7 @@ def write_graph():
     def f():
         x = tf.constant(2)
         y = tf.constant(3)
-        return x ** y
+        return x**y
 
     with tf.summary.create_file_writer(logdir).as_default():
         if hasattr(tf.summary, "graph"):

tensorboard/plugins/graph/graphs_plugin_test.py

@@ -112,7 +112,7 @@ def generate_run(
         tf.compat.v1.reset_default_graph()
         k1 = tf.constant(math.pi, name="k1")
         k2 = tf.constant(math.e, name="k2")
-        result = (k1 ** k2) - k1
+        result = (k1**k2) - k1
         expected = tf.constant(20.0, name="expected")
         error = tf.abs(result - expected, name="error")
         message_prefix_value = "error " * 1000

tensorboard/plugins/histogram/summary_test.py

@@ -92,7 +92,7 @@ def test_normal_distribution_input(self):
         self.assertEqual(buckets[:, 0].min(), self.gaussian.min())
         # Assert near, not equal, since TF's linspace op introduces floating point
         # error in the upper bound of the result.
-        self.assertNear(buckets[:, 1].max(), self.gaussian.max(), 1.0 ** -10)
+        self.assertNear(buckets[:, 1].max(), self.gaussian.max(), 1.0**-10)
         self.assertEqual(buckets[:, 2].sum(), self.gaussian.size)
         np.testing.assert_allclose(buckets[1:, 0], buckets[:-1, 1])
 

tensorboard/plugins/text/text_plugin_test.py

@@ -336,7 +336,7 @@ def make_range_array(dim):
 
             Example: rangeArray(2) results in [[0,1],[2,3]].
             """
-            return np.array(range(2 ** dim)).reshape([2] * dim)
+            return np.array(range(2**dim)).reshape([2] * dim)
 
         for i in range(2, 5):
             actual = text_plugin.reduce_to_2d(make_range_array(i))

tensorboard/plugins/text_v2/text_v2_plugin_test.py

@@ -132,7 +132,7 @@ def make_range_array(dim):
 
             Example: rangeArray(2) results in [[0,1],[2,3]].
             """
-            return np.array(range(2 ** dim)).reshape([2] * dim)
+            return np.array(range(2**dim)).reshape([2] * dim)
 
         for i in range(2, 5):
             actual = text_v2_plugin.reduce_to_2d(make_range_array(i))

tensorboard/uploader/exporter.py

@@ -43,7 +43,7 @@
 _FILENAME_SAFE_CHARS = frozenset(string.ascii_letters + string.digits + "-_")
 
 # Maximum value of a signed 64-bit integer.
-_MAX_INT64 = 2 ** 63 - 1
+_MAX_INT64 = 2**63 - 1
 
 # Output filename for experiment metadata (creation time, description,
 # etc.) within an experiment directory.

tensorboard/uploader/exporter_test.py

@@ -144,7 +144,7 @@ def stream_experiment_data(request, **kwargs):
 
         expected_eids_request = export_service_pb2.StreamExperimentsRequest()
         expected_eids_request.read_timestamp.CopyFrom(start_time_pb)
-        expected_eids_request.limit = 2 ** 63 - 1
+        expected_eids_request.limit = 2**63 - 1
         expected_eids_request.experiments_mask.create_time = True
         expected_eids_request.experiments_mask.update_time = True
         expected_eids_request.experiments_mask.name = True
@@ -357,7 +357,7 @@ def stream_experiment_data(request, **kwargs):
 
         expected_eids_request = export_service_pb2.StreamExperimentsRequest()
         expected_eids_request.read_timestamp.CopyFrom(start_time_pb)
-        expected_eids_request.limit = 2 ** 63 - 1
+        expected_eids_request.limit = 2**63 - 1
         expected_eids_request.experiments_mask.create_time = True
         expected_eids_request.experiments_mask.update_time = True
         expected_eids_request.experiments_mask.name = True

tensorboard/uploader/server_info.py

@@ -48,27 +48,27 @@
 # slow and we would otherwise risk Deadline Exceeded errors.
 #
 # [1]: https://github.com/grpc/grpc/blob/e70d8582b4b0eedc45e3d25a57b58a08b94a9f4a/include/grpc/impl/codegen/grpc_types.h#L447  # pylint: disable=line-too-long
-_DEFAULT_MAX_SCALAR_REQUEST_SIZE = 128 * (2 ** 10)  # 128KiB
+_DEFAULT_MAX_SCALAR_REQUEST_SIZE = 128 * (2**10)  # 128KiB
 
 # Maximum WriteTensor request size, if not specified by server_info, in bytes.
 # The server-side limit is 4 MiB [1]; we should pad a bit to mitigate any errors
 # in our bookkeeping. Currently, we pad a lot.
 #
 # [1]: https://github.com/grpc/grpc/blob/e70d8582b4b0eedc45e3d25a57b58a08b94a9f4a/include/grpc/impl/codegen/grpc_types.h#L447  # pylint: disable=line-too-long
-_DEFAULT_MAX_TENSOR_REQUEST_SIZE = 512 * (2 ** 10)  # 512KiB
+_DEFAULT_MAX_TENSOR_REQUEST_SIZE = 512 * (2**10)  # 512KiB
 
 # Maximum WriteBlob request size, if not specified by server_info, in bytes.
 # The server-side limit is 4 MiB [1]; we pad with a 256 KiB chunk to mitigate
 # any errors in our bookkeeping.
 #
 # [1]: https://github.com/grpc/grpc/blob/e70d8582b4b0eedc45e3d25a57b58a08b94a9f4a/include/grpc/impl/codegen/grpc_types.h#L447  # pylint: disable=line-too-long
-_DEFAULT_MAX_BLOB_REQUEST_SIZE = 4 * (2 ** 20) - 256 * (2 ** 10)  # 4MiB-256KiB
+_DEFAULT_MAX_BLOB_REQUEST_SIZE = 4 * (2**20) - 256 * (2**10)  # 4MiB-256KiB
 
 # Maximum blob size, if not specified by server_info, in bytes.
-_DEFAULT_MAX_BLOB_SIZE = 10 * (2 ** 20)  # 10MiB
+_DEFAULT_MAX_BLOB_SIZE = 10 * (2**20)  # 10MiB
 
 # Maximum tensor point size, if not specified by server_info, in bytes.
-_DEFAULT_MAX_TENSOR_POINT_SIZE = 16 * (2 ** 10)  # 16KiB
+_DEFAULT_MAX_TENSOR_POINT_SIZE = 16 * (2**10)  # 16KiB
 
 
 def _server_info_request(upload_plugins):

tensorboard/uploader/upload_tracker.py

@@ -28,10 +28,10 @@ def readable_time_string():
 
 def readable_bytes_string(bytes):
     """Get a human-readable string for number of bytes."""
-    if bytes >= 2 ** 20:
-        return "%.1f MB" % (float(bytes) / 2 ** 20)
-    elif bytes >= 2 ** 10:
-        return "%.1f kB" % (float(bytes) / 2 ** 10)
+    if bytes >= 2**20:
+        return "%.1f MB" % (float(bytes) / 2**20)
+    elif bytes >= 2**10:
+        return "%.1f kB" % (float(bytes) / 2**10)
     else:
         return "%d B" % bytes
 

tensorboard/uploader/util.py

@@ -113,7 +113,7 @@ def set_timestamp(pb, seconds_since_epoch):
       seconds_since_epoch: A `float`, as returned by `time.time`.
     """
     pb.seconds = int(seconds_since_epoch)
-    pb.nanos = int(round((seconds_since_epoch % 1) * 10 ** 9))
+    pb.nanos = int(round((seconds_since_epoch % 1) * 10**9))
 
 
 def format_time(timestamp_pb, now=None):

tensorboard/util/grpc_util.py

@@ -190,7 +190,7 @@ def _compute_backoff_seconds(num_attempts):
         _GRPC_RETRY_JITTER_FACTOR_MIN, _GRPC_RETRY_JITTER_FACTOR_MAX
     )
     backoff_secs = (
-        _GRPC_RETRY_EXPONENTIAL_BASE ** num_attempts
+        _GRPC_RETRY_EXPONENTIAL_BASE**num_attempts
     ) * jitter_factor
     return backoff_secs