Traceback (most recent call last):


 "convert_pb_tfcoreml.py", line 80, in <module>

convert()


 "convert_pb_tfcoreml.py", line 76, in convert

output_feature_names=output_tensor_names


 "/home/ubuntu/tf-coreml/tfcoreml/_tf_coreml_converter.py", line 552, in convert

custom_conversion_functions=custom_conversion_functions)


 "/home/ubuntu/tf-coreml/tfcoreml/_tf_coreml_converter.py", line 262, in _convert_pb_to_mlmodel

unused_ops, effectively_constant_ops = _find_unused_ops(OPS, sess, output_feature_names, input_feed_dict, input_feed_dict2) # return type: List[str], List[str]


 "/home/ubuntu/tf-coreml/tfcoreml/_tf_graph_transform.py", line 99, in _find_unused_ops

out1 = tensors_evaluated1[idx].flatten().astype(np.float32)
AttributeError: 'str' object has no attribute 'flatten'

Traceback (most recent call last):


 "/opt/program/keras_retinanet/bin/train.py", line 530, in <module>

main()


 "/opt/program/keras_retinanet/bin/train.py", line 490, in main

config=args.config


 "/opt/program/keras_retinanet/bin/train.py", line 112, in create_models

training_model = multi_gpu_model(model, gpus=multi_gpu)


 "/root/.local/lib/python3.6/site-packages/keras/utils/multi_gpu_utils.py", line 150, in multi_gpu_model

available_devices = _get_available_devices()


 "/root/.local/lib/python3.6/site-packages/keras/utils/multi_gpu_utils.py", line 16, in _get_available_devices

return K.tensorflow_backend._get_available_gpus() + ['/cpu:0']


 "/root/.local/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py", line 506, in _get_available_gpus

_LOCAL_DEVICES = tf.config.experimental_list_devices()
AttributeError: module 'tensorflow_core._api.v2.config' has no attribute 'experimental_list_devices'
