Keras 在尝试预测多个值时'Error when checking input'

Question

我有一个长度为 4 的输入向量，长度为 2 的输出向量。我正在尝试同时预测多个输入。如果我只想预测一个，我会执行以下操作，它有效：

in = numpy.array( [ [1,2,3,4] ] )
self.model.predict(in)
# prediction = [ [1,2] ] 

但是，当我尝试传入多个输入时，我得到ValueError: Error when checking input: expected dense_1_input to have shape (4,) but got array with shape (1,)

in = numpy.array( [
[1,2,3,4],
[1,2,3,4]
]
)
#OR
in = numpy.array( [
[ [1,2,3,4] ],
[ [1,2,3,4] ]
]
)
self.model.predict(in)
#ERR

我做错了什么？

编辑：

代码 =

model = Sequential()
model.add(Dense(24, input_dim=4, activation='relu'))
model.add(Dense(24, activation='relu'))
model.add(Dense(4, activation='linear'))
model.compile(loss='mse',
optimizer=Adam(lr=self.learning_rate))
print(batch_arr[:,3][0])
predictions = self.model.predict(batch_arr[:,3][0])
print(predictions)
print(batch_arr[:,3])
predictions = model.predict(batch_arr[:,3])

输出 =

[[-0.00441936 -0.20398824 -0.08134908  0.09739554]]
[[ 0.01860509 -0.01136071]]
[array([[-0.00441936, -0.20398824, -0.08134908,  0.09739554]])
array([[-0.00517939,  0.38975933, -0.11951023, -0.9718224 ]])
array([[0.00272119, 0.0025476 , 0.002645  , 0.03973542]])
array([[-0.00421809, -0.01006362, -0.07795483, -0.16971247]])
array([[-0.00904593,  0.19332681, -0.10655871, -0.64757587]])
array([[ 0.00654432,  0.00347247, -0.15332555, -0.47302148]])
array([[-0.01921821, -0.17354519, -0.20207744, -0.58569029]])
array([[ 0.00661377,  0.20038962, -0.16278598, -0.80983334]])
array([[-0.00348096,  0.18171964, -0.07072813, -0.38913168]])
array([[-0.01268919, -0.00548544, -0.08286095, -0.27108632]])
array([[ 0.01077598, -0.19254374, -0.004982  ,  0.33175341]])
array([[-4.37101750e-04, -5.68196965e-01, -1.99532537e-01,
1.10581883e-01]])
array([[ 0.00657382, -0.19263146, -0.00402872,  0.33368607]])
array([[ 0.00677398,  0.19760551, -0.00076944, -0.25153403]])
array([[ 0.00261579,  0.19642629, -0.13894668, -0.71894379]])
array([[-0.0221003 ,  0.37477368, -0.03765055, -0.63564477]])
array([[-0.0110009 ,  0.37599703, -0.0574645 , -0.66318148]])
array([[ 0.00277214,  0.19763152,  0.00343971, -0.25211181]])
array([[-9.31810654e-05, -2.06245307e-01, -8.09019674e-02,
1.47356796e-01]])
array([[ 0.00709025, -0.37636771, -0.19725323, -0.11396513]])
array([[ 0.00015344, -0.01233088, -0.07851076, -0.11956039]])
array([[ 0.01077811, -0.18439307, -0.19043179, -0.34107231]])
array([[-0.01460483,  0.18019651, -0.05036345, -0.35505252]])
array([[-0.0127989 ,  0.19071515, -0.08828268, -0.58871071]])
array([[ 0.01072609,  0.00249456, -0.00580012,  0.0409061 ]])
array([[ 0.01062156,  0.00782762, -0.17898265, -0.57245695]])
array([[-0.01180104, -0.37085843, -0.1973209 , -0.23782701]])
array([[-0.00849912, -0.00780031, -0.07940117, -0.21980343]])
array([[ 0.00672477,  0.00246062, -0.00160252,  0.04165408]])
array([[-0.02268911, -0.36534914, -0.21379125, -0.36284594]])
array([[-0.00865513, -0.20170279, -0.08379724,  0.0468145 ]])
array([[-0.0256848 ,  0.17922475, -0.03098346, -0.33335449]])]
#ERR

编辑：当我打印出batch_arr[:,3]的形状时，我得到了(32,)，而不是像我预期的那样(32,4)。因此，我猜 numpy 数组不知道其内部数组的形状。有没有简单的方法可以解决这个问题？这可能是问题的根源

Answer 1

问题是我创建 numpy 数组的方式。我用可变大小的索引创建了它，因此它不知道它的形状(32,4(，只知道它是(32，(。重新制定逻辑以确保数组从一开始就始终是设定的宽度，允许数组为 (32,4(，这允许预测工作。