问题描述
class D1(Layer):
def __init__ (self,input_shape=(256,256,3),name='d1',**kwargs):
super(D1,self).__init__(name=name,**kwargs)
self.h1 = Conv2D(64,(3,strides=(1,1),padding='same')
self.h2 = MaxPooling2D(pool_size=(2,2),strides=None,padding='same')
self.h3 = LeakyReLU(alpha=0.2)
self.h4 = Conv2D(128,padding='same')
self.h5 = Conv2D(128,padding='same')
self.h6 = MaxPooling2D(pool_size=(2,padding='same')
self.h7 = LeakyReLU(alpha=0.2)
self.h8 = Conv2D(256,padding='same')
self.h9 = Conv2D(256,padding='same')
self.h10 = MaxPooling2D(pool_size=(2,padding='same')
self.h11 = LeakyReLU(alpha=0.2)
self.h12 = Conv2D(512,padding='same')
self.h13 = Conv2D(512,padding='same')
self.h14 = MaxPooling2D(pool_size=(2,padding='same')
self.h15 = Flatten()
self.h16 = Dropout(0.4)
self.D1R = Dense(1,activation='sigmoid')
self.h17 = Dense(4096,activation='relu')
self.h18 = Dense(4096,activation='relu')
self.D1C = Dense(16,activation='sigmoid')
def call(self,inputs):
x = self.h1(inputs)
x = self.h2(x)
x = self.h3(x)
x = self.h4(x)
x = self.h5(x)
x = self.h6(x)
x = self.h7(x)
x = self.h8(x)
x = self.h9(x)
x = self.h10(x)
x = self.h11(x)
x = self.h12(x)
x = self.h13(x)
x = self.h14(x)
x = self.h15(x)
x = self.h16(x)
d1r = self.D1R(x)
x = self.h17(x)
x = self.h18(x)
d1c = self.D1C(x)
return d1r,d1c'''
class discriminator1(Model):
def __init__(
self,input_shape=(None,name='disc1',**kwargs
):
super(discriminator1,**kwargs)
self.d1 = D1(input_shape=input_shape)
def call(self,inputs):
image = inputs
d1r,d1c = self.d1(image)
d1_loss = d1_loss(d1r,d1c)
self.add_loss(d1_loss)
return out
在训练中调用它时，它将引发TypeError：预期的字符串或类似字节的对象。我不知道是什么。 有什么帮助吗？我的所有功能都不应该使用字符串
'''def generate_latent_noise(latent_dim,n_samples):
x_input = randn(latent_dim * n_samples)
x_input = x_input.reshape(n_samples,latent_dim)
return x_input'''
'''def generate_fake_samples(g,latent_dim,n_samples,y_i,y_l):
x_input = generate_latent_noise(latent_dim,n_samples)
X = g.predict(x_input)
y = zeros((n_samples,1))
for i in range(n_samples-1):
intent = y_i[i]
bio = y_l[i]
return X,y,intent,bio'''
'''epochs = 200
opt = SGD(learning_rate=1e-3,momentum=0.99)
metric = Accuracy()
yi,yl = retrieve_target_labels('/content/drive/My Drive/Project/input.xlsx')
g = Generator(100)
d1 = D1((256,3))
d2 = D2((256,3))
gen = G_Model((256,100,yi,yl)
disc1 = discriminator1((256,100)
disc2 = discriminator2((256,100)
art,yc_real,yi_real,yl_real =load_real_samples('/content/drive/MyDrive/Project/TrainSA.xlsx')
half_batch = yi.shape[0]
n_batch = half_batch * 2
batch_per_epoch = int(art.shape[0]/n_batch)
for epoch in range(epochs):
for batch in range(batch_per_epoch):
fake,yl = generate_fake_samples(g,half_batch,yl)
real,y_real,c_real,i_real,l_real = generate_real_samples(art,yl_real)
fake_image = tf.convert_to_tensor(fake)
d1r,d1c = d1(fake_image) #error!
d1_loss_fake = d1.losses
d1r,d1c = d1(real)
d1_loss = d1.losses
d2i_fake,d2l_fake = d2(fake_image)
d2_loss_fake = d2.losses
d2i,d2l = d2(real)
d2_loss = d2.losses
g_loss = gen.losses '''
要提供一个最小的工作示例有点困难，因为在调用了许多函数之后，错误出现在代码的末尾，但是我试图包括可能与错误有关的那些函数。
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-95-d4bb0da7c68f> in <module>()
23 #d1_loss_fake = d1.losses
24 real_image = tf.convert_to_tensor(real,dtype = tf.float32)
---> 25 d1r,d1c = disc1(real_image)
26 d1_loss = d1.losses
27 d2i_fake,d2l_fake = d2(fake_image)
3 frames
/tensorflow-1.15.2/python3.6/tensorflow_core/python/framework/ops.py in
name_scope(self,name)
4126 # Scopes created in the root must match the more restrictive
4127 # op name regex,which constrains the initial character.
-> 4128 if not _VALID_OP_NAME_REGEX.match(name):
4129 raise ValueError("'%s' is not a valid scope name" % name)
4130 old_stack = self._name_stack
TypeError: expected string or bytes-like object
解决方法
暂无找到可以解决该程序问题的有效方法，小编努力寻找整理中！
如果你已经找到好的解决方法，欢迎将解决方案带上本链接一起发送给小编。
小编邮箱:dio#foxmail.com (将#修改为@）