#Define model layers.
input_layer = Input(shape=(300,))
dense1 = Dense(units='128', activation='relu')(input_layer)
dense2 = Dense(units='128', activation='relu')(dense1)
# Y1 output will be fed directly from the second dense
y1_output = Dense(units='1', name='y1_output')(dense2)
dense3 = Dense(units='128', activation='relu')(dense2)
# Y2 output will come via the third dense
y2_output = Dense(units='1', name='y2_output')(dense3)
dense4= Dense(units='128', activation='relu')(dense3)
y3_output = Dense(units='1', name='y3_output')(dense4)
dense5= Dense(units='128', activation='relu')(dense4)
y4_output = Dense(units='1', name='y4_output')(dense5)
dense6= Dense(units='128', activation='relu')(dense5)
y5_output = Dense(units='1', name='y5_output')(dense6)
dense7= Dense(units='128', activation='relu')(dense6)
y6_output = Dense(units='1', name='y6_output')(dense7)
dense8= Dense(units='128', activation='relu')(dense7)
y7_output = Dense(units='1', name='y7_output')(dense8)
dense9= Dense(units='128', activation='relu')(dense8)
y8_output = Dense(units='1', name='y8_output')(dense9)
dense10= Dense(units='128', activation='relu')(dense9)
y9_output = Dense(units='1', name='y9_output')(dense10)
dense11= Dense(units='128', activation='relu')(dense10)
y10_output = Dense(units='1', name='y10_output')(dense11)
dense12= Dense(units='128', activation='relu')(dense11)
y11_output = Dense(units='1', name='y11_output')(dense12)
dense13= Dense(units='128', activation='relu')(dense12)
y12_output = Dense(units='1', name='y12_output')(dense13)
dense14= Dense(units='128', activation='relu')(dense13)
y13_output = Dense(units='1', name='y13_output')(dense14)
dense15= Dense(units='128', activation='relu')(dense14)
y14_output = Dense(units='1', name='y14_output')(dense15)
dense16= Dense(units='128', activation='relu')(dense15)
y15_output = Dense(units='1', name='y15_output')(dense16)
dense17= Dense(units='128', activation='relu')(dense16)
y16_output = Dense(units='1', name='y16_output')(dense17)
dense18= Dense(units='128', activation='relu')(dense17)
y17_output = Dense(units='1', name='y17_output')(dense18)
dense19= Dense(units='128', activation='relu')(dense18)
y18_output = Dense(units='1', name='y18_output')(dense19)
dense20= Dense(units='128', activation='relu')(dense19)
y19_output = Dense(units='1', name='y19_output')(dense20)
dense21= Dense(units='128', activation='relu')(dense20)
y20_output = Dense(units='1', name='y20_output')(dense21)
dense22= Dense(units='128', activation='relu')(dense21)
y21_output = Dense(units='1', name='y21_output')(dense22)
dense23= Dense(units='128', activation='relu')(dense22)
y22_output = Dense(units='1', name='y22_output')(dense23)
dense24= Dense(units='128', activation='relu')(dense23)
y23_output = Dense(units='1', name='y23_output')(dense24)
dense25= Dense(units='128', activation='relu')(dense24)
y24_output = Dense(units='1', name='y24_output')(dense25)
dense26= Dense(units='128', activation='relu')(dense25)
y25_output = Dense(units='1', name='y25_output')(dense26)
dense27= Dense(units='128', activation='relu')(dense26)
y26_output = Dense(units='1', name='y26_output')(dense27)
dense28= Dense(units='128', activation='relu')(dense27)
y27_output = Dense(units='1', name='y27_output')(dense28)
dense29= Dense(units='128', activation='relu')(dense28)
y28_output = Dense(units='1', name='y28_output')(dense29)
dense30= Dense(units='128', activation='relu')(dense29)
y29_output = Dense(units='1', name='y29_output')(dense30)
dense31= Dense(units='128', activation='relu')(dense30)
y30_output = Dense(units='1', name='y30_output')(dense31)
dense32= Dense(units='128', activation='relu')(dense31)
y31_output = Dense(units='1', name='y31_output')(dense32)
dense33= Dense(units='128', activation='relu')(dense32)
y32_output = Dense(units='1', name='y32_output')(dense33)
dense34= Dense(units='128', activation='relu')(dense33)
y33_output = Dense(units='1', name='y33_output')(dense34)
dense35= Dense(units='128', activation='relu')(dense34)
y34_output = Dense(units='1', name='y34_output')(dense35)
dense36= Dense(units='128', activation='relu')(dense35)
y35_output = Dense(units='1', name='y35_output')(dense36)
dense37= Dense(units='128', activation='relu')(dense36)
y36_output = Dense(units='1', name='y36_output')(dense37)
dense38= Dense(units='128', activation='relu')(dense37)
y37_output = Dense(units='1', name='y37_output')(dense38)
dense39= Dense(units='128', activation='relu')(dense38)
y38_output = Dense(units='1', name='y38_output')(dense39)
dense40= Dense(units='128', activation='relu')(dense39)
y39_output = Dense(units='1', name='y39_output')(dense40)
dense41= Dense(units='128', activation='relu')(dense40)
y40_output = Dense(units='1', name='y40_output')(dense41)
dense42= Dense(units='128', activation='relu')(dense41)
y41_output = Dense(units='1', name='y41_output')(dense42)
dense43= Dense(units='128', activation='relu')(dense42)
y42_output = Dense(units='1', name='y42_output')(dense43)
dense44= Dense(units='128', activation='relu')(dense43)
y43_output = Dense(units='1', name='y43_output')(dense44)
dense45= Dense(units='128', activation='relu')(dense44)
y44_output = Dense(units='1', name='y44_output')(dense45)
dense46= Dense(units='128', activation='relu')(dense45)
y45_output = Dense(units='1', name='y45_output')(dense46)
dense47= Dense(units='128', activation='relu')(dense46)
y46_output = Dense(units='1', name='y46_output')(dense47)
dense48= Dense(units='128', activation='relu')(dense47)
y47_output = Dense(units='1', name='y47_output')(dense48)
dense49= Dense(units='128', activation='relu')(dense48)
y48_output = Dense(units='1', name='y48_output')(dense49)
dense50= Dense(units='128', activation='relu')(dense49)
y49_output = Dense(units='1', name='y49_output')(dense50)
dense51= Dense(units='128', activation='relu')(dense50)
y50_output = Dense(units='1', name='y50_output')(dense51)
dense52= Dense(units='128', activation='relu')(dense51)
y51_output = Dense(units='1', name='y51_output')(dense52)
dense53= Dense(units='128', activation='relu')(dense52)
y52_output = Dense(units='1', name='y52_output')(dense53)
dense54= Dense(units='128', activation='relu')(dense53)
y53_output = Dense(units='1', name='y53_output')(dense54)
dense55= Dense(units='128', activation='relu')(dense54)
y54_output = Dense(units='1', name='y54_output')(dense55)
dense56= Dense(units='128', activation='relu')(dense55)
y55_output = Dense(units='1', name='y55_output')(dense56)
dense57= Dense(units='128', activation='relu')(dense56)
y56_output = Dense(units='1', name='y56_output')(dense57)
dense58= Dense(units='128', activation='relu')(dense57)
y57_output = Dense(units='1', name='y57_output')(dense58)
dense59= Dense(units='128', activation='relu')(dense58)
y58_output = Dense(units='1', name='y58_output')(dense59)
dense60= Dense(units='128', activation='relu')(dense59)
y59_output = Dense(units='1', name='y59_output')(dense60)
dense61= Dense(units='128', activation='relu')(dense60)
y60_output = Dense(units='1', name='y60_output')(dense61)
# Define the model with the input layer and a list of output layers
model = Model(inputs=input_layer, outputs=[y1_output, y2_output,y3_output,y4_output,y5_output,y6_output,y7_output,y8_output,y9_output,y10_output, y11_output, y12_output,y13_output,y14_output,y15_output,y16_output,y17_output,y18_output,y19_output,y20_output, y21_output, y22_output,y23_output,y24_output,y25_output,y26_output,y27_output,y28_output,y29_output,y30_output, y31_output, y32_output,y33_output,y34_output,y35_output,y36_output,y37_output,y38_output,y39_output,y40_output,y41_output, y42_output,y43_output,y44_output,y45_output,y46_output,y47_output,y48_output,y49_output,y50_output, y51_output, y52_output,y53_output,y54_output,y55_output,y56_output,y57_output,y58_output,y59_output,y60_output])
print(model.summary())
也许您正在寻找这样的结构？这样，您就有了一个具有60个节点的单个输出层。
#Define model layers.
input_layer = Input(shape=(300,))
dense1 = Dense(units='128', activation='relu')(input_layer)
dense2 = Dense(units='128', activation='relu')(dense1)
output = Dense(units='60', name='output')(dense2)
model = keras.Model(inputs=input_layer, outputs= output)
print(model.summary())
输出：
Layer (type) Output Shape Param #
=================================================================
input_1 (InputLayer) [(None, 300)] 0
dense (Dense) (None, 128) 38528
dense_1 (Dense) (None, 128) 16512
output (Dense) (None, 60) 7740