我想绘制自定义 keras 模型的底层拓扑。根据此链接( https://machinelearningmastery.com/visualize-deep-learning-neural-network-model-keras/ ),我以为我可以使用 keras.utils.vis_utils.plot_model ,但这产生了错误。
这是重现错误的最小自定义模型和代码:
import tensorflow as tf
from keras.models import Model
from keras import backend as K
from keras.utils.vis_utils import plot_model
import unittest
'''
Construct a double-layer perceptron without an activation
'''
rows = 10
cols = 2
class Model(tf.keras.Model):
def __init__(self, hidden_topology):
super(Model, self).__init__(name='')
self.hidden_topology = hidden_topology
def call(self, inputs):
hidden_output = inputs
for hidden_layer in self.hidden_topology:
hidden_output = hidden_layer(hidden_output)
return hidden_output
def compute_output_shape(self, input_shape):
return (input_shape[0][0], 1)
model = Model(
[
tf.keras.layers.Dense(
1,
input_shape=((rows, cols), ),
use_bias=True,
kernel_initializer=tf.constant_initializer(1.0),
bias_initializer=tf.constant_initializer(0.0)),
tf.keras.layers.Dense(
1,
input_shape=((rows, cols), ),
use_bias=True,
kernel_initializer=tf.constant_initializer(1.0),
bias_initializer=tf.constant_initializer(0.0))
])
test_data = np.reshape(range(rows*cols), (rows,cols)).astype(np.float32)
top = model.call(test_data)
#plot_model(top, to_file='model_plot.png')#, show_shapes=True, show_layer_names=True)
plot_model(model, to_file='model_plot.png')#, show_shapes=True, show_layer_names=True)
这会产生以下错误:
AttributeErrorTraceback (most recent call last)
<ipython-input-3-b73c347c7b0a> in <module>()
49 # top = model.call(test_data)
50
---> 51 plot_model(model, to_file='model_plot.png')#, show_shapes=True, show_layer_names=True)
52
53 # def call(self, inputs):
/package/python-2.7.15/lib/python2.7/site-packages/keras/utils/vis_utils.pyc in plot_model(model, to_file, show_shapes, show_layer_names, rankdir, expand_nested, dpi)
238 """
239 dot = model_to_dot(model, show_shapes, show_layer_names, rankdir,
--> 240 expand_nested, dpi)
241 _, extension = os.path.splitext(to_file)
242 if not extension:
/package/python-2.7.15/lib/python2.7/site-packages/keras/utils/vis_utils.pyc in model_to_dot(model, show_shapes, show_layer_names, rankdir, expand_nested, dpi, subgraph)
104
105 # Append a wrapped layer's label to node's label, if it exists.
--> 106 layer_name = layer.name
107 class_name = layer.__class__.__name__
108
AttributeError: 'ListWrapper' object has no attribute 'name'
我也尝试了注释掉的行,但没有成功。
如何可视化此拓扑?我正在使用 tensorflow 2.0.0
最佳答案
您提到的链接在使用tf.keras
时使用keras
(Tensorflow的高级API)。
而不是:
from keras.utils.vis_utils import plot_model
将此行更改为:
from tensorflow.keras.utils import plot_model
编辑:
虽然您将摆脱此错误,但由于您使用的是子类模型,因此您将看到的只是图中的模型 block 。要绘制完整的模型图,您必须使用顺序或功能模型。我还建议将类名称更改为 Model
以外的名称。
关于python - 绘制 keras 自定义模型时,“ListWrapper”对象没有属性 'name',我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/59443567/