error when running colabfold_batch

fold_error.txt

2023-08-22 18:58:05,566 Running colabfold 1.3.0 (26de12d3afb5f85d49d0c7db1b9371f034388395)
2023-08-22 18:58:28,127 Unable to initialize backend 'tpu_driver': NOT_FOUND: Unable to find driver in registry given worker: 
2023-08-22 18:58:28,382 Unable to initialize backend 'tpu': INVALID_ARGUMENT: TpuPlatform is not available.
2023-08-22 18:58:35,545 generated new fontManager
Traceback (most recent call last):
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/bin/colabfold_batch", line 8, in <module>
    sys.exit(main())
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/colabfold/batch.py", line 1728, in main
    run(
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/colabfold/batch.py", line 1210, in run
    from colabfold.alphafold.models import load_models_and_params
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/colabfold/alphafold/models.py", line 7, in <module>
    from alphafold.model import model, config, data
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/alphafold/model/model.py", line 20, in <module>
    from alphafold.model import features
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/alphafold/model/features.py", line 19, in <module>
    from alphafold.model.tf import input_pipeline
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/alphafold/model/tf/input_pipeline.py", line 17, in <module>
    from alphafold.model.tf import data_transforms
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/alphafold/model/tf/data_transforms.py", line 18, in <module>
    from alphafold.model.tf import shape_helpers
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/alphafold/model/tf/shape_helpers.py", line 16, in <module>
    import tensorflow.compat.v1 as tf
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/tensorflow/__init__.py", line 41, in <module>
    from tensorflow.python.tools import module_util as _module_util
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/tensorflow/python/__init__.py", line 41, in <module>
    from tensorflow.python.eager import context
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/tensorflow/python/eager/context.py", line 33, in <module>
    from tensorflow.core.framework import function_pb2
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/tensorflow/core/framework/function_pb2.py", line 16, in <module>
    from tensorflow.core.framework import attr_value_pb2 as tensorflow_dot_core_dot_framework_dot_attr__value__pb2
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/tensorflow/core/framework/attr_value_pb2.py", line 16, in <module>
    from tensorflow.core.framework import tensor_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__pb2
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/tensorflow/core/framework/tensor_pb2.py", line 16, in <module>
    from tensorflow.core.framework import resource_handle_pb2 as tensorflow_dot_core_dot_framework_dot_resource__handle__pb2
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/tensorflow/core/framework/resource_handle_pb2.py", line 16, in <module>
    from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2
  File "/g/data/if89/apps/colabfold_batch/1.4.0/python3/3.9.2/lib/python3.9/site-packages/tensorflow/core/framework/tensor_shape_pb2.py", line 36, in <module>
    _descriptor.FieldDescriptor(
  File "/home/005/ml0997/.local/lib/python3.9/site-packages/google/protobuf/descriptor.py", line 561, in __new__
    _message.Message._CheckCalledFromGeneratedFile()
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

======================================================================================
                  Resource Usage on 2023-08-22 18:58:57:
   Job Id:             93195220.gadi-pbs
   Project:            kx58
   Exit Status:        0
   Service Units:      0.62
   NCPUs Requested:    12                     NCPUs Used: 12              
                                           CPU Time Used: 00:00:07        
   Memory Requested:   48.0GB                Memory Used: 1.22GB          
   NGPUs Requested:    1                 GPU Utilisation: 0%              
                                         GPU Memory Used: 308.0MB         
   Walltime requested: 12:00:00            Walltime Used: 00:01:02        
   JobFS requested:    1.0GB                  JobFS used: 0B              
======================================================================================

#!/bin/bash

#PBS -P kx58
#PBS -q gpuvolta
#PBS -l ncpus=12
#PBS -l ngpus=1
#PBS -l mem=48GB
#PBS -l walltime=12:00:00
#PBS -l jobfs=1GB
#PBS -l wd
#PBS -l storage=gdata/if89+scratch/kx58
#PBS -M "[email protected]"
#PBS -m abe

module use /g/data/if89/apps/modulefiles
module load colabfold_batch/1.4.0

# see https://opus.nci.org.au/display/Help/Colabfold
DATE=$(date +%d_%m_%Y_%H_%M_%S)
log_dir="/scratch/kx58/ml0997/colabfold_logs"
mkdir -p "${log_dir}"

run_name="1uao_chignolin"
# naming is numerical, if 1 input FASTA to search = 1 file in out folder
a3m_input_path="/home/005/ml0997/colabfold/search_outputs/1uao_chignolin/0.a3m"
out_folder="/home/005/ml0997/colabfold/fold_outputs/1uao_chignolin/"
mkdir -p ${out_folder}

colabfold_batch --amber --templates --num-recycle 3 --use-gpu-relax \
    ${a3m_input_path} \
    ${out_folder} \
    2>&1 | tee "${log_dir}/${run_name}_fold_${DATE}.log"

#!/bin/bash

#PBS -P kx58
#PBS -q normal
#PBS -l ncpus=24
#PBS -l mem=100GB
#PBS -l walltime=3:00:00
#PBS -l jobfs=1GB
#PBS -l wd
#PBS -l storage=gdata/if89+scratch/kx58
#PBS -M "[email protected]"
#PBS -m abe

module use /g/data/if89/apps/modulefiles
module load colabfold_batch/1.4.0

# see https://opus.nci.org.au/display/Help/Colabfold
DATE=$(date +%d_%m_%Y_%H_%M_%S)
log_dir="/scratch/kx58/ml0997/colabfold_logs"
mkdir -p "${log_dir}"

# FYI: took 49 mins for chignolin, 12 CPUs = 41 SUs
# 24 CPUs = 41 mins, not much faster. better to use 12 CPUs.
run_name="1uao_chignolin_24cpus"
num_threads=24
in_path="/home/005/ml0997/colabfold/data/1uao_chignolin.fasta"
out_folder="/home/005/ml0997/colabfold/search_outputs/${run_name}/"
mkdir -p ${out_folder}

colabfold_search --db-load-mode 1 --threads ${num_threads} \
    ${in_path} \
    $COLABFOLDDIR/database \
    ${out_folder} \
    2>&1 | tee "${log_dir}/${run_name}_search_${DATE}.log"