import keras
from keras.layers import Input, LSTM, Dense, Conv2D
from keras.models import Model
a = Input(shape=(32, 32, 3))
b = Input(shape=(64, 64, 3))
 
conv = Conv2D(16, (3, 3), padding='same')
conved_a = conv(a)
 
# 到目前为止只有一个输入，以下可行：
assert conv.input_shape == (None, 32, 32, 3)

import keras
from keras.layers import Input, LSTM, Dense, Conv2D
from keras.models import Model
a = Input(shape=(32, 32, 3))
b = Input(shape=(64, 64, 3))
 
conv = Conv2D(16, (3, 3), padding='same')
conved_a = conv(a)
 
# 到目前为止只有一个输入，以下可行：
assert conv.input_shape == (None, 32, 32, 3)
 
conved_b = conv(b)
# 现在 `.input_shape` 属性不可行，但是这样可以：
assert conv.get_input_shape_at(0) == (None, 32, 32, 3)
assert conv.get_input_shape_at(1) == (None, 64, 64, 3)

import keras
from keras.layers import Input, LSTM, Dense, Conv2D
from keras.models import Model
a = Input(shape=(32, 32, 3))
b = Input(shape=(64, 64, 3))
 
conv = Conv2D(16, (3, 3), padding='same')
conved_a = conv(a)
 
# 到目前为止只有一个输入，以下可行：
assert conv.input_shape == (None, 32, 32, 3)
 
conved_b = conv(b)
# 就改了output，当然尺寸我也改了
assert conv.get_output_shape_at(0) == (None, 32, 32, 16)
assert conv.get_output_shape_at(1) == (None, 64, 64, 16)