我正在尝试使用autokeras制作模型，并将模型部署到移动设备上。 我创建了一个简单的模型，并尝试转换移动模型。
reg = ak.StructuredDataRegressor(max_trials=1, overwrite=True)
reg.fit(X_train, y_train, epochs=2)
model = reg.export_model()
tf.keras.models.save_model(model, "model_test/ak_pb", save_format="tf")
(I also tried with converted Sequential model using Sequential(model.layers))
然后，我尝试将模型转换为移动模型（据我所知），但是在任何方法上都失败了。
错误消息大约有3种类型。
我不是该领域的专家，所以我无法完全理解错误消息。 我想知道错误是否是因为：
1. coding error?
2. convert routine(converter.convert()) is not perfect?
3. autokeras generated model is different from native keras model?
import tensorflow as tf
import autokeras as ak
from tensorflow.keras.models import load_model
model_tf = load_model("model_test/ak_pb")
# model = load_model("model_test/ak_pb", custom_objects=ak.CUSTOM_OBJECTS)
model_tf.summary()
converter = tf.lite.TFLiteConverter.from_keras_model(model_tf)
输出为：（省略了一些警告消息...）
Model: "functional_1"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 132)] 0
_________________________________________________________________
multi_category_encoding (Mul (None, 132) 0
_________________________________________________________________
dense (Dense) (None, 32) 4256
_________________________________________________________________
re_lu (ReLU) (None, 32) 0
_________________________________________________________________
dense_1 (Dense) (None, 16) 528
_________________________________________________________________
re_lu_1 (ReLU) (None, 16) 0
_________________________________________________________________
regression_head_1 (Dense) (None, 1) 17
=================================================================
Total params: 4,801
Trainable params: 4,801
Non-trainable params: 0
_________________________________________________________________
WARNING:tensorflow:From /home/gb/miniconda3/envs/tfconv/lib/python3.6/site-packages/tensorflow/python/training/tracking/tracking.py:111: Model.state_updates (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.
Instructions for updating:
This property should not be used in TensorFlow 2.0, as updates are applied automatically.
WARNING:tensorflow:From /home/gb/miniconda3/envs/tfconv/lib/python3.6/site-packages/tensorflow/python/training/tracking/tracking.py:111: Layer.updates (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.
Instructions for updating:
This property should not be used in TensorFlow 2.0, as updates are applied automatically.
INFO:tensorflow:Assets written to: /tmp/tmphq0lh3_e/assets
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
<ipython-input-3-f4dca08044b1> in <module>
12 converter.allow_custom_ops=False
13
---> 14 tflite_model = converter.convert()
~/miniconda3/envs/tfconv/lib/python3.6/site-packages/tensorflow/lite/python/lite.py in convert(self)
807 frozen_func, graph_def = (
808 _convert_to_constants.convert_variables_to_constants_v2_as_graph(
--> 809 self._funcs[0], lower_control_flow=False))
810
811 input_tensors = [
~/miniconda3/envs/tfconv/lib/python3.6/site-packages/tensorflow/python/framework/convert_to_constants.py in convert_variables_to_constants_v2_as_graph(func, lower_control_flow, aggressive_inlining)
1101 func=func,
1102 lower_control_flow=lower_control_flow,
-> 1103 aggressive_inlining=aggressive_inlining)
1104
1105 output_graph_def, converted_input_indices = _replace_variables_by_constants(
~/miniconda3/envs/tfconv/lib/python3.6/site-packages/tensorflow/python/framework/convert_to_constants.py in __init__(self, func, lower_control_flow, aggressive_inlining, variable_names_whitelist, variable_names_blacklist)
802 variable_names_whitelist=variable_names_whitelist,
803 variable_names_blacklist=variable_names_blacklist)
--> 804 self._build_tensor_data()
805
806 def _build_tensor_data(self):
~/miniconda3/envs/tfconv/lib/python3.6/site-packages/tensorflow/python/framework/convert_to_constants.py in _build_tensor_data(self)
821 data = map_index_to_variable[idx].numpy()
822 else:
--> 823 data = val_tensor.numpy()
824 self._tensor_data[tensor_name] = _TensorData(
825 numpy=data,
~/miniconda3/envs/tfconv/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in numpy(self)
1061 """
1062 # TODO(slebedev): Consider avoiding a copy for non-CPU or remote tensors.
-> 1063 maybe_arr = self._numpy() # pylint: disable=protected-access
1064 return maybe_arr.copy() if isinstance(maybe_arr, np.ndarray) else maybe_arr
1065
~/miniconda3/envs/tfconv/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in _numpy(self)
1029 return self._numpy_internal()
1030 except core._NotOkStatusException as e: # pylint: disable=protected-access
-> 1031 six.raise_from(core._status_to_exception(e.code, e.message), None) # pylint: disable=protected-access
1032
1033 @property
~/.local/lib/python3.6/site-packages/six.py in raise_from(value, from_value)
InvalidArgumentError: Cannot convert a Tensor of dtype resource to a NumPy array.
from tensorflow.compat.v1 import graph_util
import tensorflow.keras.backend as K
from tensorflow.python.framework.convert_to_constants import convert_variables_to_constants_v2
import numpy as np
print (f'eager execution mode should be True == {tf.executing_eagerly()}\n')
from tensorflow.keras.models import load_model
# model_tf = load_model("model_test/ak_pb")
model_tf = load_model("model_test/ak_pb", custom_objects=ak.CUSTOM_OBJECTS)
full_model = tf.function(lambda x: model_tf(x))
full_model = full_model.get_concrete_function(
tf.TensorSpec(model_tf.inputs[0].shape, model_tf.inputs[0].dtype))
# Get frozen ConcreteFunction
frozen_func = convert_variables_to_constants_v2(full_model)
# frozen_func.graph.as_graph_def()
layers = [op.name for op in frozen_func.graph.get_operations()]
# Save frozen graph from frozen ConcreteFunction to hard drive
tf.io.write_graph(graph_or_graph_def=frozen_func.graph,
logdir="frozen_models", name="frozen_graph.pb", as_text=False)
它产生，
InvalidArgumentError Traceback (most recent call last)
<ipython-input-4-8a2e5ff939d8> in <module>
16
17 # Get frozen ConcreteFunction
---> 18 frozen_func = convert_variables_to_constants_v2(full_model)
19 # frozen_func.graph.as_graph_def()
20
~/miniconda3/envs/tfconv/lib/python3.6/site-packages/tensorflow/python/framework/convert_to_constants.py in convert_variables_to_constants_v2(func, lower_control_flow, aggressive_inlining)
1067 func=func,
1068 lower_control_flow=lower_control_flow,
-> 1069 aggressive_inlining=aggressive_inlining)
1070
1071 output_graph_def, converted_input_indices = _replace_variables_by_constants(
~/miniconda3/envs/tfconv/lib/python3.6/site-packages/tensorflow/python/framework/convert_to_constants.py in __init__(self, func, lower_control_flow, aggressive_inlining, variable_names_whitelist, variable_names_blacklist)
802 variable_names_whitelist=variable_names_whitelist,
803 variable_names_blacklist=variable_names_blacklist)
--> 804 self._build_tensor_data()
805
806 def _build_tensor_data(self):
~/miniconda3/envs/tfconv/lib/python3.6/site-packages/tensorflow/python/framework/convert_to_constants.py in _build_tensor_data(self)
821 data = map_index_to_variable[idx].numpy()
822 else:
--> 823 data = val_tensor.numpy()
824 self._tensor_data[tensor_name] = _TensorData(
825 numpy=data,
~/miniconda3/envs/tfconv/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in numpy(self)
1061 """
1062 # TODO(slebedev): Consider avoiding a copy for non-CPU or remote tensors.
-> 1063 maybe_arr = self._numpy() # pylint: disable=protected-access
1064 return maybe_arr.copy() if isinstance(maybe_arr, np.ndarray) else maybe_arr
1065
~/miniconda3/envs/tfconv/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in _numpy(self)
1029 return self._numpy_internal()
1030 except core._NotOkStatusException as e: # pylint: disable=protected-access
-> 1031 six.raise_from(core._status_to_exception(e.code, e.message), None) # pylint: disable=protected-access
1032
1033 @property
~/.local/lib/python3.6/site-packages/six.py in raise_from(value, from_value)
InvalidArgumentError: Cannot convert a Tensor of dtype resource to a NumPy array.
<< input_format = tf_saved_model >>
(tfjsv) D:\0.Projects\autokeras_test\tfjs>tensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model D:\0.Projects\autokeras_test\model_test\ak_pb D:\0.Projects\autokeras_test\model_test\res\
2020-09-18 21:44:20.651344: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x2d1bea1ea00 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-09-18 21:44:20.651688: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2020-09-18 21:44:23.029133: I tensorflow/core/grappler/devices.cc:78] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 0 (Note: TensorFlow was not compiled with CUDA or ROCm support)
2020-09-18 21:44:23.029870: I tensorflow/core/grappler/clusters/single_machine.cc:356] Starting new session
2020-09-18 21:44:23.338069: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:816] Optimization results for grappler item: graph_to_optimize
2020-09-18 21:44:23.340454: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:818] function_optimizer: Graph size after: 537 nodes (528), 910 edges (901), time = 147.066ms.
2020-09-18 21:44:23.340631: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:818] function_optimizer: function_optimizer did nothing. time = 0.629ms.
Traceback (most recent call last):
File "D:\0.Projects\autokeras_test\tfjs\pyenv-win\versions\3.6.8\lib\runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "D:\0.Projects\autokeras_test\tfjs\pyenv-win\versions\3.6.8\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "D:\0.Projects\autokeras_test\tfjs\tfjsv\Scripts\tensorflowjs_converter.exe\__main__.py", line 9, in <module>
File "d:\0.projects\autokeras_test\tfjs\tfjsv\lib\site-packages\tensorflowjs\converters\converter.py", line 757, in pip_main
main([' '.join(sys.argv[1:])])
File "d:\0.projects\autokeras_test\tfjs\tfjsv\lib\site-packages\tensorflowjs\converters\converter.py", line 761, in main
convert(argv[0].split(' '))
File "d:\0.projects\autokeras_test\tfjs\tfjsv\lib\site-packages\tensorflowjs\converters\converter.py", line 699, in convert
experiments=args.experiments)
File "d:\0.projects\autokeras_test\tfjs\tfjsv\lib\site-packages\tensorflowjs\converters\tf_saved_model_conversion_v2.py", line 552, in convert_tf_saved_model
experiments=experiments)
File "d:\0.projects\autokeras_test\tfjs\tfjsv\lib\site-packages\tensorflowjs\converters\tf_saved_model_conversion_v2.py", line 143, in optimize_graph
', '.join(unsupported))
ValueError: Unsupported Ops in the model before optimization
StringToNumber, IsNan
<< --input_format = tf_frozen_model >>
(tfjsv) D:\0.Projects\autokeras_test\tfjs>tensorflowjs_converter --input_format tf_frozen_model --output_format tfjs_graph_model --output_node_names=functional_1/regression_head_1/BiasAdd D:\0.Projects\autokeras_test\model_test\frozen_graph.pb D:\0.Projects\autokeras_test\model_test\res\
Traceback (most recent call last):
File "D:\0.Projects\autokeras_test\tfjs\pyenv-win\versions\3.6.8\lib\runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "D:\0.Projects\autokeras_test\tfjs\pyenv-win\versions\3.6.8\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "D:\0.Projects\autokeras_test\tfjs\tfjsv\Scripts\tensorflowjs_converter.exe\__main__.py", line 9, in <module>
File "d:\0.projects\autokeras_test\tfjs\tfjsv\lib\site-packages\tensorflowjs\converters\converter.py", line 757, in pip_main
main([' '.join(sys.argv[1:])])
File "d:\0.projects\autokeras_test\tfjs\tfjsv\lib\site-packages\tensorflowjs\converters\converter.py", line 761, in main
convert(argv[0].split(' '))
File "d:\0.projects\autokeras_test\tfjs\tfjsv\lib\site-packages\tensorflowjs\converters\converter.py", line 744, in convert
experiments=args.experiments)
File "d:\0.projects\autokeras_test\tfjs\tfjsv\lib\site-packages\tensorflowjs\converters\tf_saved_model_conversion_v2.py", line 433, in convert_tf_frozen_model
experiments=experiments)
File "d:\0.projects\autokeras_test\tfjs\tfjsv\lib\site-packages\tensorflowjs\converters\tf_saved_model_conversion_v2.py", line 143, in optimize_graph
', '.join(unsupported))
ValueError: Unsupported Ops in the model before optimization
IsNan, StringToNumber