以下代码给我一个错误:ValueError: Shapes (None, 3, 2) 和 (None, 2) 不兼容。我想构建一个多任务网络,该如何解决?我正在使用Tensorflow 2.3.0。
import numpy as np
import tensorflow as tf
from tensorflow.keras.layers import GlobalAveragePooling2D, Dense, Dropout
from tensorflow.keras import Model
base_model = tf.keras.applications.EfficientNetB7(input_shape=(32,32, 3), weights='imagenet',
include_top=False) # or weights='noisy-student'
for layer in base_model.layers[:]:
layer.trainable = False
x = GlobalAveragePooling2D()(base_model.output)
dropout_rate = 0.3
x = Dense(256, activation='relu')(x)
x = Dropout(dropout_rate)(x)
x = Dense(256, activation='relu')(x)
x = Dropout(dropout_rate)(x)
all_target = []
loss_list = []
test_metrics = {}
for name, node in [("task1", 2), ("task2", 2), ("task3", 2)]:
y1 = Dense(128, activation='relu')(x)
y1 = Dropout(dropout_rate)(y1)
y1 = Dense(64, activation='relu')(y1)
y1 = Dropout(dropout_rate)(y1)
# y1 = Dense(64, activation='relu')(y1)
# y1 = Dropout(dropout_rate)(y1)
y1 = Dense(node, activation='softmax', name=name)(y1)
all_target.append(y1)
loss_list.append('categorical_crossentropy')
test_metrics[name] = "accuracy"
# model = Model(inputs=model_input, outputs=[y1, y2, y3])
model = Model(inputs=base_model.input, outputs=all_target)
model.compile(loss=loss_list, optimizer='adam', metrics=test_metrics)
res=np.random.randint(2, size=3072).reshape(32, 32, 3)
res=np.expand_dims(res, 0)
lab=np.array([[[0,1], [0,1], [0,1]]])
history = model.fit(res, y=lab, epochs=1, verbose=1)