I used the Keras functional API (keras version 2.2) to define a model but when I try to fit the data to the model I get some for of error. I am currently using python 2.7 and the code is running on Ubuntu 18.04.
The following is the code for the model:
class Model:
def __init__(self, config):
self.hidden_layers = config["hidden_layers"]
self.loss = config["loss"]
self.optimizer = config["optimizer"]
self.batch_normalization = config["batch_normalization"]
self.model = self._build_model()
def _build_model(self):
input = Input(shape=(32,))
hidden_layers = []
if self.batch_normalization:
hidden_layers.append(Dense(self.hidden_layers[0], bias_initializer= Orthogonal)(input))
hidden_layers.append(BatchNormalization()(hidden_layers[-1]))
hidden_layers.append(Activation("relu")(hidden_layers[-1]))
else:
hidden_layers.append(Dense(self.hidden_layers[0], bias_initializer= Orthogonal, activation='relu')(input))
for i in self.hidden_layers[1:]:
if self.batch_normalization:
hidden_layers.append(Dense(i, bias_initializer= Orthogonal)(hidden_layers[-1]))
hidden_layers.append(BatchNormalization()(hidden_layers[-1]))
hidden_layers.append(Activation("relu")(hidden_layers[-1]))
else:
hidden_layers.append(Dense(i, bias_initializer= Orthogonal, activation='relu')(hidden_layers[-1]))
output_layer = Dense(2, activation="softmax")(hidden_layers[-1])
model = Model(input= input, output= output_layer)
model.compile(optimizer=self.optimizer, loss=self.loss, metrics=["accuracy"])
return model
The following is the command that I use and the error message I get once I run the fit method:
model.fit(x=X_train,y=Y_train, epochs=20)
File "/home/project/main.py", line 69, in <module>
main(config)
File "/home/project/main.py", line 62, in main
model = Model(config, logging).model
File "/home/project/model.py", line 18, in __init__
self.model = self._build_model()
File "/home/project/model.py", line 34, in _build_model
hidden_layers.append(Dense(self.hidden_layers[0], bias_initializer= Orthogonal, activation='relu')(input))
File "/home/project/venv/local/lib/python2.7/site-packages/keras/engine/base_layer.py", line 431, in __call__
self.build(unpack_singleton(input_shapes))
File "/home/project/venv/local/lib/python2.7/site-packages/keras/layers/core.py", line 872, in build
constraint=self.bias_constraint)
File "/home/project/venv/local/lib/python2.7/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/home/project/venv/local/lib/python2.7/site-packages/keras/engine/base_layer.py", line 252, in add_weight
constraint=constraint)
File "/home/project/venv/local/lib/python2.7/site-packages/keras/backend/tensorflow_backend.py", line 402, in variable
v = tf.Variable(value, dtype=tf.as_dtype(dtype), name=name)
File "/home/project/venv/local/lib/python2.7/site-packages/tensorflow/python/ops/variables.py", line 183, in __call__
return cls._variable_v1_call(*args, **kwargs)
...
...
File "/home/project/venv/local/lib/python2.7/site-packages/tensorflow/python/ops/variables.py", line 1329, in __init__
constraint=constraint)
File "/home/project/venv/local/lib/python2.7/site-packages/tensorflow/python/ops/variables.py", line 1437, in _init_from_args
initial_value(), name="initial_value", dtype=dtype)
TypeError: __call__() takes at least 2 arguments (1 given)
I really don't understand what this TypeError is. I am not sure how to change my model definition to avoid this error.
config["hidden_layers"]?