TypeError: Descriptors cannot not be created directly. - protocol buffer bug

Today I got an expected error, when trying to:
import umap

Error trace is below.

I tried to install the version of PROTOCOL_BUFFERS

!pip install protobuf==3.19
!pip install protobuf==3.20
!pip install protobuf

with no success.

It seems it conflicts with Tensorflow.
Tensorflow version installed is 2.11

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[18], line 16
     13 import librosa
     15 # Clustering
---> 16 import umap
     17 import umap.plot
     19 import hdbscan

File /data0/home/h21/luas6629/venv/lib/python3.10/site-packages/umap/__init__.py:7
      5     with catch_warnings():
      6         simplefilter("ignore")
----> 7         from .parametric_umap import ParametricUMAP
      8 except ImportError:
      9     warn(
     10         "Tensorflow not installed; ParametricUMAP will be unavailable",
     11         category=ImportWarning,
     12     )

File /data0/home/h21/luas6629/venv/lib/python3.10/site-packages/umap/parametric_umap.py:14
     10 import sys
     13 try:
---> 14     import tensorflow as tf
     15 except ImportError:
     16     warn(
     17         """The umap.parametric_umap package requires Tensorflow > 2.0 to be installed.
     18     You can install Tensorflow at https://www.tensorflow.org/install
   (...)
     24     """
     25     )

File /data0/home/h21/luas6629/venv/lib/python3.10/site-packages/tensorflow/__init__.py:37
     34 import sys as _sys
     35 import typing as _typing
---> 37 from tensorflow.python.tools import module_util as _module_util
     38 from tensorflow.python.util.lazy_loader import LazyLoader as _LazyLoader
     40 # Make sure code inside the TensorFlow codebase can use tf2.enabled() at import.

File /data0/home/h21/luas6629/venv/lib/python3.10/site-packages/tensorflow/python/__init__.py:37
     29 # We aim to keep this file minimal and ideally remove completely.
     30 # If you are adding a new file with @tf_export decorators,
     31 # import it in modules_with_exports.py instead.
     32 
     33 # go/tf-wildcard-import
     34 # pylint: disable=wildcard-import,g-bad-import-order,g-import-not-at-top
     36 from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow
---> 37 from tensorflow.python.eager import context
     39 # pylint: enable=wildcard-import
     40 
     41 # Bring in subpackages.
     42 from tensorflow.python import data

File /data0/home/h21/luas6629/venv/lib/python3.10/site-packages/tensorflow/python/eager/context.py:28
     25 from absl import logging
     26 import numpy as np
---> 28 from tensorflow.core.framework import function_pb2
     29 from tensorflow.core.protobuf import config_pb2
     30 from tensorflow.core.protobuf import coordination_config_pb2

File /data0/home/h21/luas6629/venv/lib/python3.10/site-packages/tensorflow/core/framework/function_pb2.py:16
     11 # @@protoc_insertion_point(imports)
     13 _sym_db = _symbol_database.Default()
---> 16 from tensorflow.core.framework import attr_value_pb2 as tensorflow_dot_core_dot_framework_dot_attr__value__pb2
     17 from tensorflow.core.framework import node_def_pb2 as tensorflow_dot_core_dot_framework_dot_node__def__pb2
     18 from tensorflow.core.framework import op_def_pb2 as tensorflow_dot_core_dot_framework_dot_op__def__pb2

File /data0/home/h21/luas6629/venv/lib/python3.10/site-packages/tensorflow/core/framework/attr_value_pb2.py:16
     11 # @@protoc_insertion_point(imports)
     13 _sym_db = _symbol_database.Default()
---> 16 from tensorflow.core.framework import tensor_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__pb2
     17 from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2
     18 from tensorflow.core.framework import types_pb2 as tensorflow_dot_core_dot_framework_dot_types__pb2

File /data0/home/h21/luas6629/venv/lib/python3.10/site-packages/tensorflow/core/framework/tensor_pb2.py:16
     11 # @@protoc_insertion_point(imports)
     13 _sym_db = _symbol_database.Default()
---> 16 from tensorflow.core.framework import resource_handle_pb2 as tensorflow_dot_core_dot_framework_dot_resource__handle__pb2
     17 from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2
     18 from tensorflow.core.framework import types_pb2 as tensorflow_dot_core_dot_framework_dot_types__pb2

File /data0/home/h21/luas6629/venv/lib/python3.10/site-packages/tensorflow/core/framework/resource_handle_pb2.py:16
     11 # @@protoc_insertion_point(imports)
     13 _sym_db = _symbol_database.Default()
---> 16 from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2
     17 from tensorflow.core.framework import types_pb2 as tensorflow_dot_core_dot_framework_dot_types__pb2
     20 DESCRIPTOR = _descriptor.FileDescriptor(
     21   name='tensorflow/core/framework/resource_handle.proto',
     22   package='tensorflow',
   (...)
     26   ,
     27   dependencies=[tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2.DESCRIPTOR,tensorflow_dot_core_dot_framework_dot_types__pb2.DESCRIPTOR,])

File /data0/home/h21/luas6629/venv/lib/python3.10/site-packages/tensorflow/core/framework/tensor_shape_pb2.py:36
     13 _sym_db = _symbol_database.Default()
     18 DESCRIPTOR = _descriptor.FileDescriptor(
     19   name='tensorflow/core/framework/tensor_shape.proto',
     20   package='tensorflow',
   (...)
     23   serialized_pb=_b('\n,tensorflow/core/framework/tensor_shape.proto\x12\ntensorflow\"z\n\x10TensorShapeProto\x12-\n\x03\x64im\x18\x02 \x03(\x0b\x32 .tensorflow.TensorShapeProto.Dim\x12\x14\n\x0cunknown_rank\x18\x03 \x01(\x08\x1a!\n\x03\x44im\x12\x0c\n\x04size\x18\x01 \x01(\x03\x12\x0c\n\x04name\x18\x02 \x01(\tB\x87\x01\n\x18org.tensorflow.frameworkB\x11TensorShapeProtosP\x01ZSgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/tensor_shape_go_proto\xf8\x01\x01\x62\x06proto3')
     24 )
     29 _TENSORSHAPEPROTO_DIM = _descriptor.Descriptor(
     30   name='Dim',
     31   full_name='tensorflow.TensorShapeProto.Dim',
     32   filename=None,
     33   file=DESCRIPTOR,
     34   containing_type=None,
     35   fields=[
---> 36     _descriptor.FieldDescriptor(
     37       name='size', full_name='tensorflow.TensorShapeProto.Dim.size', index=0,
     38       number=1, type=3, cpp_type=2, label=1,
     39       has_default_value=False, default_value=0,
     40       message_type=None, enum_type=None, containing_type=None,
     41       is_extension=False, extension_scope=None,
     42       serialized_options=None, file=DESCRIPTOR),
     43     _descriptor.FieldDescriptor(
     44       name='name', full_name='tensorflow.TensorShapeProto.Dim.name', index=1,
     45       number=2, type=9, cpp_type=9, label=1,
     46       has_default_value=False, default_value=_b("").decode('utf-8'),
     47       message_type=None, enum_type=None, containing_type=None,
     48       is_extension=False, extension_scope=None,
     49       serialized_options=None, file=DESCRIPTOR),
     50   ],
     51   extensions=[
     52   ],
     53   nested_types=[],
     54   enum_types=[
     55   ],
     56   serialized_options=None,
     57   is_extendable=False,
     58   syntax='proto3',
     59   extension_ranges=[],
     60   oneofs=[
     61   ],
     62   serialized_start=149,
     63   serialized_end=182,
     64 )
     66 _TENSORSHAPEPROTO = _descriptor.Descriptor(
     67   name='TensorShapeProto',
     68   full_name='tensorflow.TensorShapeProto',
   (...)
    100   serialized_end=182,
    101 )
    103 _TENSORSHAPEPROTO_DIM.containing_type = _TENSORSHAPEPROTO

File /data0/home/h21/luas6629/venv/lib/python3.10/site-packages/google/protobuf/descriptor.py:560, in FieldDescriptor.__new__(cls, name, full_name, index, number, type, cpp_type, label, default_value, message_type, enum_type, containing_type, is_extension, extension_scope, options, serialized_options, has_default_value, containing_oneof, json_name, file, create_key)
    554 def __new__(cls, name, full_name, index, number, type, cpp_type, label,
    555             default_value, message_type, enum_type, containing_type,
    556             is_extension, extension_scope, options=None,
    557             serialized_options=None,
    558             has_default_value=True, containing_oneof=None, json_name=None,
    559             file=None, create_key=None):  # pylint: disable=redefined-builtin
--> 560   _message.Message._CheckCalledFromGeneratedFile()
    561   if is_extension:
    562     return _message.default_pool.FindExtensionByName(full_name)

TypeError: Descriptors cannot not be created directly.
If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0.
If you cannot immediately regenerate your protos, some other possible workarounds are:
 1. Downgrade the protobuf package to 3.20.x or lower.
 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower).

More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates

Reproduce the failure with import umap and inspect umap/__init__.py and umap/parametric_umap.py, where the TensorFlow import begins. Check the project's dependency metadata and supported TensorFlow/protobuf combinations; done means the reported environment can import UMAP without the descriptor TypeError.