我使用 Keras 函数式 API(keras 2.2 版)来定义模型,但是当我尝试将数据拟合到模型时,我得到了一些错误。我目前使用的是 python 2.7,代码在 Ubuntu 18.04 上运行。以下是模型的代码: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我真的不明白这个 TypeError 是什么。我不确定如何更改我的模型定义以避免此错误。
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