我正在用CNN做文本分类(遵循kim-yoon的方法) 但我犯了个错误我搞不懂
我看了有类似问题的帖子的ret,但没法理解
inputs = Input(shape=(sequence_length,))
embedding = embedding_layer(inputs)
reshape = Reshape((sequence_length,embedding_dim,1))(embedding)
conv_0 = Conv2D(num_filters, (filter_sizes[0],
embedding_dim),activation='relu',kernel_regularizer=regularizers.l2(0.01))
(reshape)
conv_1 =
Conv2D(num_filters,filter_sizes[1],embedding_dim),activation='relu',
kernel_regularizer=regulari zers.l2(0.01))(reshape)
conv_2 = Conv2D(num_filters,
(filter_sizes[2],embedding_dim),activation='relu',kernel_regularizer=
regularizers.l2(0.01))(reshape)
maxpool_0 = MaxPooling2D((sequence_length - filter_sizes[0] + 1, 1),
strides=(1,1))(conv_0)
flat_0 = Flatten()(maxpool_0)
maxpool_1 = MaxPooling2D((sequence_length - filter_sizes[1] + 1, 1),
strides=(1,1))(conv_1)
flat_1 = Flatten()(maxpool_1)
maxpool_2 = MaxPooling2D((sequence_length - filter_sizes[2] + 1, 1),
strides=(1,1))(conv_2)
flat_2 = Flatten()(maxpool_2)
merged_tensor = concatenate([flat_0,flat_1, flat_2])
output = Dense(units=3,
activation='softmax',kernel_regularizer=regularizers.l2(0.01(merged_tensor)
ValueError回溯(最近一次调用) 在里面 1 ---->;2个型号.fit(x\u列,y\u列,批量大小,epochs=100,verbose=1,callbacks=callback) 3#开始培训
ValueError:检查目标时出错:预期密集的\u 4具有形状(3,),但得到的数组具有形状(2,)
当然,消息中有更多的数据,如果需要的话我会把它放上去
4是最终输出
目前没有回答
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