Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower)

[sayedidrees]

This is first code block and its givign me this error

%cd  
!git clone --quiet https://github.com/tensorflow/models.git
!apt-get install -qq protobuf-compiler python-tk
!pip install -q Cython contextlib2 pillow lxml matplotlib PyDrive
!pip install -q pycocotools
%cd ~/models/research
!protoc object_detection/protos/*.proto --python_out=.
import os
%set_env PYTHONPATH=/root/models/research:/root/models/research/slim
!python object_detection/builders/model_builder_test.py

Logs

env: PYTHONPATH=/root/models/research:/root/models/research/slim
2025-02-07 06:49:56.377985: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1738910996.400236    1466 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1738910996.407201    1466 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2025-02-07 06:49:56.429154: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
Traceback (most recent call last):
  File "/root/models/research/object_detection/builders/model_builder_test.py", line 20, in <module>
    from object_detection.builders import model_builder
  File "/root/models/research/object_detection/builders/model_builder.py", line 23, in <module>
    from object_detection.builders import anchor_generator_builder
  File "/root/models/research/object_detection/builders/anchor_generator_builder.py", line 26, in <module>
    from object_detection.protos import anchor_generator_pb2
  File "/root/models/research/object_detection/protos/anchor_generator_pb2.py", line 14, in <module>
    from object_detection.protos import flexible_grid_anchor_generator_pb2 as object__detection_dot_protos_dot_flexible__grid__anchor__generator__pb2
  File "/root/models/research/object_detection/protos/flexible_grid_anchor_generator_pb2.py", line 36, in <module>
    _descriptor.FieldDescriptor(
  File "/usr/local/lib/python3.11/dist-packages/google/protobuf/descriptor.py", line 553, in __new__
    _message.Message._CheckCalledFromGeneratedFile()
TypeError: Descriptors cannot 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