同一组程序，在服务器上跑正常，在自己电脑上跑loss=nan?

#程序如下 服务器显卡P6000 我的3070ti

from keras.layers import Conv1D
from keras.layers import Input
from keras.layers import Dense
from keras.layers import GlobalMaxPooling1D
from keras import Model
from keras.optimizers import Adam
import numpy as np

x = np.ones((3,5,1))+ np.random.rand(3,5,1)
y = np.ones((3,4))
#参数设定与预留空间
point = 5
classes = 4
#模型建立
A3_oil = Input((point,1), name="i1")
A3_oil_b = Conv1D(2,3, name='i3')(A3_oil)
A3_oil_c = GlobalMaxPooling1D()(A3_oil_b)
output = Dense(classes, name='i5')(A3_oil_c)
model = Model(inputs=A3_oil, outputs=output)
model.compile(optimizer=Adam(0.001),
              loss='categorical_crossentropy',
              metrics = ['accuracy'])

# 模型训练
h1 = model.fit(x=x,y=y,batch_size=1,epochs=10)

#打印结果
t = model.get_layer('i3')
t1 = model.get_layer('i5')
print(t.get_weights())
print(t1.get_weights())

#服务器上结果

t------------------------------
[array([[[ 0.43431887,  0.41476223]],
       [[ 1.4486791 ,  0.59360373]],
       [[-0.12812461,  0.4679315 ]]], dtype=float32), 
array([0.6965934, 1.024095 ], dtype=float32)]
t1------------------------------
[array([[-1.0713661e+00, -5.9727323e-01,  7.2374243e-01,  8.7767702e-01],
       [ 9.6996349e-01, -1.1376817e+00,  2.9774686e-02,  5.3538941e-04]],
      dtype=float32), array([-0.82753366, -0.64814734,  0.5947477 ,  0.6944112 ], dtype=float32)]

#自己电脑上结果

[array([[[nan, nan]],
       [[nan, nan]],
       [[nan, nan]]], dtype=float32), array([nan, nan], dtype=float32)]

[array([[nan, nan, nan, nan],
       [nan, nan, nan, nan]], dtype=float32), array([nan, nan, nan, nan], dtype=float32)]

而且自己电脑上从第一步开始就是nan
后来我把卷积层去了就正常了，发现不能用卷积，一加卷积就loss=nan，哪怕batch=1,学习率都试过。
只要没有卷积层，其他都能正常训练，这是怎么了？

#去掉卷积
from keras.layers import Conv1D
from keras.layers import Input
from keras.layers import Dense
from keras.layers import GlobalMaxPooling1D
from keras import Model
from keras.optimizers import Adam
import numpy as np

x = np.ones((3,5,1))+ np.random.rand(3,5,1)
y = np.ones((3,4))
#参数设定与预留空间
point = 5
classes = 4
#模型建立
A3_oil = Input((point,1),name="i1")
A3_oil_c = GlobalMaxPooling1D()(A3_oil)
output = Dense(classes,name='i5')(A3_oil_c)
model = Model(inputs=A3_oil,outputs=output)
model.compile(optimizer=Adam(0.001),
              loss='categorical_crossentropy',
              metrics = ['accuracy'])
# 模型训练
h1 = model.fit(x=x,y=y,batch_size=1,epochs=10)
t1 = model.get_layer('i5')
print(t1.get_weights())

#结果

t1-----------------------------------
[array([[ 0.07497485, -0.2384741 ,  0.6795341 ,  0.20184563]],
      dtype=float32), array([ 0.026965  , -0.02952293, -0.02944644,  0.02643826], dtype=float32)]

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