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Metaclass conflict with Keras 2.3.0 #199
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Subclassing # keras_helper.py
# AttributeError: 'LossFunctionWrapper' object has no attribute '__name__'
try:
compile_params["loss_function_names"] = [_.__name__ for _ in compile_params["loss_functions"]]
except:
compile_params["loss_function_names"] = [_.name for _ in compile_params["loss_functions"]]
# AttributeError: 'Sequential' object has no attribute 'weighted_metrics'
try:
compile_params["weighted_metrics"] = get_keras_attr(model, "weighted_metrics")
except:
print('WARNING: could not fetch "weighted_metrics" attribute; skipping...') Full error trace: total:0 # print(self.name) outputs
count:0
UnreadVariable
Traceback (most recent call last):
File "<ipython-input-1-1226ec5313a7>", line 56, in <module>
execute()
File "<ipython-input-1-1226ec5313a7>", line 49, in execute
shuffle=True,
File "C:\hyperparameter_hunter\hyperparameter_hunter\experiment_core.py", line 165, in __call__
return super().__call__(*args, **kwargs)
File "C:\hyperparameter_hunter\hyperparameter_hunter\experiments.py", line 749, in __init__
target_metric=target_metric,
File "C:\hyperparameter_hunter\hyperparameter_hunter\experiments.py", line 595, in __init__
target_metric=target_metric,
File "C:\hyperparameter_hunter\hyperparameter_hunter\experiments.py", line 302, in __init__
self.preparation_workflow()
File "C:\hyperparameter_hunter\hyperparameter_hunter\experiments.py", line 354, in preparation_workflow
self._generate_hyperparameter_key()
File "C:\hyperparameter_hunter\hyperparameter_hunter\experiments.py", line 450, in _generate_hyperparameter_key
self.hyperparameter_key = HyperparameterKeyMaker(parameters, self.cross_experiment_key)
File "C:\hyperparameter_hunter\hyperparameter_hunter\keys\makers.py", line 367, in __init__
KeyMaker.__init__(self, parameters, **kwargs)
File "C:\hyperparameter_hunter\hyperparameter_hunter\keys\makers.py", line 90, in __init__
self.parameters = deepcopy(parameters)
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 150, in deepcopy
y = copier(x, memo)
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 240, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 150, in deepcopy
y = copier(x, memo)
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 240, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 150, in deepcopy
y = copier(x, memo)
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 240, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 150, in deepcopy
y = copier(x, memo)
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 215, in _deepcopy_list
append(deepcopy(a, memo))
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 180, in deepcopy
y = _reconstruct(x, memo, *rv)
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 280, in _reconstruct
state = deepcopy(state, memo)
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 150, in deepcopy
y = copier(x, memo)
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 240, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 150, in deepcopy
y = copier(x, memo)
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 215, in _deepcopy_list
append(deepcopy(a, memo))
File "D:\Anaconda\envs\test_hh\lib\copy.py", line 161, in deepcopy
y = copier(memo)
File "D:\Anaconda\envs\test_hh\lib\site-packages\tensorflow_core\python\ops\resource_variable_ops.py", line 464, in __deepcopy__
name=self._shared_name + "_copy",
File "D:\Anaconda\envs\test_hh\lib\site-packages\tensorflow_core\python\ops\variables.py", line 1155, in _shared_name
return self.name[:self.name.index(":")]
ValueError: substring not found |
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Error Traceback
examples/keras_examples/experiment_example.py
Bug Hunt Notes
tracers.ArgumentTracer
to descend fromABCMeta
does resolve the metaclass conflict, but leads to different errors regarding the usage of__deepcopy__
in TensorFlow:NotImplementedError: __deepcopy__() is only available when eager execution is enabled.
lr
tolearning_rate
for all optimizersdecay
argument for all optimizersThe text was updated successfully, but these errors were encountered: