通过设置 TF_KERAS==1 , 切换至 tf.keras. 启动训练脚本后可正常编译模型, 但训练时报错.
报错信息如下:
Traceback (most recent call last): File "train.py", line 94, in <module> train_generator.forfit(), steps_per_epoch=len(train_generator), epochs=1 File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training.py", line 728, in fit use_multiprocessing=use_multiprocessing) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training_v2.py", line 224, in fit distribution_strategy=strategy) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training_v2.py", line 547, in _process_training_inputs use_multiprocessing=use_multiprocessing) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training_v2.py", line 606, in _process_inputs use_multiprocessing=use_multiprocessing) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/data_adapter.py", line 566, in __init__ reassemble, nested_dtypes, output_shapes=nested_shape) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/data/ops/dataset_ops.py", line 540, in from_generator output_types, tensor_shape.as_shape, output_shapes) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/data/util/nest.py", line 471, in map_structure_up_to results = [func(*tensors) for tensors in zip(*all_flattened_up_to)] File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/data/util/nest.py", line 471, in <listcomp> results = [func(*tensors) for tensors in zip(*all_flattened_up_to)] File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/framework/tensor_shape.py", line 1216, in as_shape return TensorShape(shape) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/framework/tensor_shape.py", line 776, in __init__ self._dims = [as_dimension(d) for d in dims_iter] File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/framework/tensor_shape.py", line 776, in <listcomp> self._dims = [as_dimension(d) for d in dims_iter] File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/framework/tensor_shape.py", line 718, in as_dimension return Dimension(value) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/framework/tensor_shape.py", line 193, in __init__ self._value = int(value) TypeError: int() argument must be a string, a bytes-like object or a number, not 'tuple'
wduo
commented
2 years ago
通过设置 TF_KERAS==1 , 切换至 tf.keras. 启动训练脚本后可正常编译模型, 但训练时报错. 报错信息如下:
Traceback (most recent call last): File "train.py", line 94, in <module> train_generator.forfit(), steps_per_epoch=len(train_generator), epochs=1 File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training.py", line 728, in fit use_multiprocessing=use_multiprocessing) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training_v2.py", line 224, in fit distribution_strategy=strategy) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training_v2.py", line 547, in _process_training_inputs use_multiprocessing=use_multiprocessing) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training_v2.py", line 606, in _process_inputs use_multiprocessing=use_multiprocessing) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/data_adapter.py", line 566, in __init__ reassemble, nested_dtypes, output_shapes=nested_shape) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/data/ops/dataset_ops.py", line 540, in from_generator output_types, tensor_shape.as_shape, output_shapes) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/data/util/nest.py", line 471, in map_structure_up_to results = [func(*tensors) for tensors in zip(*all_flattened_up_to)] File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/data/util/nest.py", line 471, in <listcomp> results = [func(*tensors) for tensors in zip(*all_flattened_up_to)] File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/framework/tensor_shape.py", line 1216, in as_shape return TensorShape(shape) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/framework/tensor_shape.py", line 776, in __init__ self._dims = [as_dimension(d) for d in dims_iter] File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/framework/tensor_shape.py", line 776, in <listcomp> self._dims = [as_dimension(d) for d in dims_iter] File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/framework/tensor_shape.py", line 718, in as_dimension return Dimension(value) File "/Users/yuxi/opt/anaconda3/envs/TrainingRobot/lib/python3.7/site-packages/tensorflow_core/python/framework/tensor_shape.py", line 193, in __init__ self._value = int(value) TypeError: int() argument must be a string, a bytes-like object or a number, not 'tuple'使用 keras 可正常训练. 至于想要用 tf.keras训练的原因是, 想将 hdf5 格式保存的模型切换至 SavedModel. keras.model 无法直接转换.