tensorflow as tfmodel.save_weights("hello.h5") 我得到了一个属性错误model.save_wieghts("hello")
AttributeError: 'Sequential' object has no attribute 'save_wieghts'
NotImplementedError: Saving the model to HDF5 format requires the model to be a Functional model or a SequentialConsider saving to the Tensorflow SavedModel format (by setting save_format="tf") or using `save_weights我遵循的是official tutorial,它没有将这个场景计算在内。令人惊讶的是,除了cl
numpy import reshapedef model_CNN(X_train,Y_train,X_test,Y_test):
37 # Print the summary of the model
AttributeError: 'Sequential' object has no attribute 'score' 由于我是pyth
# Define model architecturemodel.add(Dense(512,input_shape=(3,),activation="relucalibration.py", line 312, in _preprocAttributeError: 'Sequentialmodel.classes_ Traceback (most recent call last):
Fil
NotImplementedError: Saving the model to HDF5 format requires the model to be
a Functional model or a SequentialConsider saving to the Tensorflow SavedModel format (by setting save_format="tf") or using `save_weights
我试图用DenseVariational层构建一个模型,以便它能够报告认知不确定性。有点像Layer DenseVariational has arguments in `__init__` and therefore must override `get_config`.class CustomVariational(tfp.layers.DenseVariational):
def get_config(self):