Traceback (most recent call last):


 "my_script.py", line 11, in <module>

import wandb


 "{venv}/lib/python3.6/site-packages/wandb/__init__.py", line 118, in <module>

api = InternalApi()


 "{venv}/lib/python3.6/site-packages/wandb/apis/internal.py", line 17, in __init__

self.api = InternalApi(*args, **kwargs)


 "{venv}/lib/python3.6/site-packages/wandb/sdk/internal/internal_api.py", line 74, in __init__

load_settings=load_settings, root_dir=self.default_settings.get("root_dir")


 "{venv}/lib/python3.6/site-packages/wandb/old/settings.py", line 25, in __init__

self._global_settings.read([Settings._global_path()])


 "{venv}/lib/python3.6/site-packages/wandb/old/settings.py", line 105, in _global_path

util.mkdir_exists_ok(config_dir)


 "{venv}/lib/python3.6/site-packages/wandb/util.py", line 642, in mkdir_exists_ok

os.makedirs(path)


 "/usr/lib/python3.6/os.py", line 220, in makedirs

mkdir(name, mode)
OSError: [Errno 30] Read-only file system: '/home/user/.config/wandb'

768/10000 [=>............................] - ETA: 46:01:31 - loss: 2.7264 - regression_loss: 2.2707 - classification_loss: 0.4557Traceback (most recent call last):


 "object_detector_retinanet/keras_retinanet/bin/train.py", line 440, in <module>

main()


 "object_detector_retinanet/keras_retinanet/bin/train.py", line 435, in main

validation_steps=validation_generator.size()


 "/opt/conda/lib/python3.7/site-packages/keras/legacy/interfaces.py", line 91, in wrapper

return func(*args, **kwargs)


 "/opt/conda/lib/python3.7/site-packages/keras/engine/training.py", line 1418, in fit_generator

initial_epoch=initial_epoch)


 "/opt/conda/lib/python3.7/site-packages/keras/engine/training_generator.py", line 181, in fit_generator

generator_output = next(output_generator)


 "/opt/conda/lib/python3.7/site-packages/keras/utils/data_utils.py", line 709, in get

six.reraise(*sys.exc_info())


 "/opt/conda/lib/python3.7/site-packages/six.py", line 693, in reraise

raise value


 "/opt/conda/lib/python3.7/site-packages/keras/utils/data_utils.py", line 685, in get

inputs = self.queue.get(block=True).get()


 "/opt/conda/lib/python3.7/multiprocessing/pool.py", line 657, in get

raise self._value


 "/opt/conda/lib/python3.7/multiprocessing/pool.py", line 121, in worker

result = (True, func(*args, **kwds))


 "/opt/conda/lib/python3.7/site-packages/keras/utils/data_utils.py", line 626, in next_sample

return six.next(_SHARED_SEQUENCES[uid])


 "/notebooks/SKU/object_detector_retinanet/keras_retinanet/preprocessing/generator.py", line 287, in __next__

return self.next()


 "/notebooks/SKU/object_detector_retinanet/keras_retinanet/preprocessing/generator.py", line 298, in next

return self.compute_input_output(group)


 "/notebooks/SKU/object_detector_retinanet/keras_retinanet/preprocessing/generator.py", line 269, in compute_input_output

image_group
= self.load_image_group(group)


 "/notebooks/SKU/object_detector_retinanet/keras_retinanet/preprocessing/generator.py", line 147, in load_image_group

return [self.load_image(image_index) for image_index in group]


 "/notebooks/SKU/object_detector_retinanet/keras_retinanet/preprocessing/generator.py", line 147, in <listcomp>

return [self.load_image(image_index) for image_index in group]


 "/notebooks/SKU/object_detector_retinanet/keras_retinanet/preprocessing/csv_generator.py", line 270, in load_image

return read_image_bgr(self.image_path(image_index))


 "/notebooks/SKU/object_detector_retinanet/keras_retinanet/utils/image.py", line 32, in read_image_bgr

image = np.asarray(Image.open(path).convert('RGB'))


 "/opt/conda/lib/python3.7/site-packages/PIL/Image.py", line 912, in convert

self.load()


 "/opt/conda/lib/python3.7/site-packages/PIL/Image
.py", line 239, in load

len(b))
OSError: image file is truncated (23 bytes not processed)
