我正在尝试使用 Keras 功能 API 构建 CNN 模型,但每当我尝试执行这行代码时: model = CNN(settings, np.expand_dims(x_train, axis = 3)).build_network()
我一直遇到以下问题:
ValueError: Graph disconnected: cannot obtain value for tensor Tensor("input_11:0", shape=(?, 28, 28, 1), dtype=float32) at layer "input_11". The following previous layers were accessed without issue: []
这是我的代码:
class CNN:
def __init__(self, settings, data):
self.flag = False
self.settings = settings
if self.check_network_settings() == False:
self.flag = True
return
self.data = data
if K.image_data_format() == "channels_first":
self.data = self.data.reshape(data.shape[0], data.shape[3], data.shape[2], data.shape[1])
self.build_network()
def show_model_chart(self):
if not os.path.isfile('model.png'):
plot_model(self.model, to_file = 'model.png')
model_pic = cv2.imread('model.png')
plt.imshow(model_pic)
plt.show()
def build_network(self):
print('Bulding Convolutional Neural Network ...')
inputs = Input(shape = (self.data.shape[1], self.data.shape[2], self.data.shape[3]))
final_output = None
for layer_idx in range(self.settings['conv']['layers']):
inputs = Conv2D(
filters = self.settings['conv']['filters'][layer_idx],
kernel_size = self.settings['conv']['kernel_size'][layer_idx],
strides = self.settings['conv']['strides'][layer_idx],
padding = self.settings['conv']['padding']
)(inputs)
if self.settings['pooling']['apply'] == True:
inputs = MaxPooling2D(
pool_size = self.settings['pooling']['pool_size'][layer_idx],
strides = self.settings['pooling']['strides'][layer_idx],
padding = self.settings['pooling']['padding']
)(inputs)
inputs = Activation(
activation = self.settings['detector_stage'][layer_idx]
)(inputs)
inputs = Flatten()(inputs)
for dense_layer_idx in range(self.settings['dense']['layers']):
if self.settings['dense']['activations'][dense_layer_idx] != 'softmax':
inputs = Dense(
units = self.settings['dense']['output_units'][dense_layer_idx],
activation = self.settings['dense']['activations'][dense_layer_idx]
)(inputs)
else:
final_output = Dense(
units = self.settings['dense']['output_units'][dense_layer_idx],
activation = self.settings['dense']['activations'][dense_layer_idx]
)(inputs)
self.model = Model(inputs = inputs, outputs = final_output)
def check_network_settings(self):
for key in self.settings:
if key == 'conv':
if set(self.settings['conv'].keys()) != {'layers', 'filters', 'kernel_size', 'strides', 'padding'}:
print('[INCORRECT SETTINGS]: Convolutional layers ...')
return False
elif key == 'pooling':
if set(self.settings['pooling'].keys()) != {'apply', 'pool_size', 'strides', 'padding'}:
print('[INCORRECT SETTINGS]: Pooling layers ...')
return False
if len(self.settings['pooling']['apply']) != self.settings['conv']['layers']:
print('Please specify wether or not to apply pooling for each convolutional layer')
return False
elif key == 'detector_stage':
if self.settings['conv']['layers'] != len(self.settings['detector_stage']):
print('Number of activation functions you have specified does not match the number of convolutional layers inside the network ...')
return False
elif key == 'dense':
if set(self.settings['dense'].keys()) != {'layers', 'output_units', 'activations'}:
print('[INCORRECT SETTINGS]: Dense layers ...')
return False
if 'softmax' != self.settings['dense']['activations'][len(self.settings['dense']['activations'])-1]:
print('Your network must contain Softmax activation function at the last Dense layer in order to produce class probabilities ...')
return False
print('Network settings have been correctly specified ...')
return True
以下是我作为类构造函数的参数提供的设置:
settings = {
'conv':
{
'layers': 3,
'filters': [32, 64, 128],
'kernel_size':[(3,3), (5,5), (5,5)],
'strides': [1, 1, 1],
'padding': 'same',
},
'pooling':
{
'apply': [True, True, True],
'pool_size': [(2,2), (3,3), (3,3)],
'strides': [1, 1, 1],
'padding': 'same'
},
'detector_stage': ['relu', 'relu', 'relu'],
'dense':
{
'layers': 2,
'output_units': [500, 10],
'activations': ['relu', 'softmax'],
},
'batch_norm': [False, False, False, False]
}
最佳答案
问题是 inputs
变量具有第一个 Dense 层的输出张量,而不是实际输入。
关于tensorflow - 尝试使用 Keras 功能 API 构建 CNN 模型时图断开连接,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/54797198/