[英]How can I get the number of trainable parameters of a model in Keras?
I am setting trainable=False
in all my layers, implemented through the Model
API, but I want to verify whether that is working.我在所有层中设置
trainable=False
,通过Model
API 实现,但我想验证这是否有效。 model.count_params()
returns the total number of parameters, but is there any way in which I can get the total number of trainable parameters, other than looking at the last few lines of model.summary()
? model.count_params()
返回参数的总数,但是除了查看model.summary()
的最后几行之外,有什么方法可以获得可训练参数的总数?
from keras import backend as K
trainable_count = int(
np.sum([K.count_params(p) for p in set(model.trainable_weights)]))
non_trainable_count = int(
np.sum([K.count_params(p) for p in set(model.non_trainable_weights)]))
print('Total params: {:,}'.format(trainable_count + non_trainable_count))
print('Trainable params: {:,}'.format(trainable_count))
print('Non-trainable params: {:,}'.format(non_trainable_count))
The above snippet can be discovered in the end of layer_utils.print_summary()
definition, which summary()
is calling.上面的片段可以在
layer_utils.print_summary()
定义的末尾发现,这是summary()
调用。
Edit: more recent version of Keras has a helper function count_params()
for this purpose:编辑:最新版本的
count_params()
有一个辅助函数count_params()
用于此目的:
from keras.utils.layer_utils import count_params
trainable_count = count_params(model.trainable_weights)
non_trainable_count = count_params(model.non_trainable_weights)
For TensorFlow 2.0 :对于TensorFlow 2.0 :
import tensorflow.keras.backend as K
trainable_count = np.sum([K.count_params(w) for w in model.trainable_weights])
non_trainable_count = np.sum([K.count_params(w) for w in model.non_trainable_weights])
print('Total params: {:,}'.format(trainable_count + non_trainable_count))
print('Trainable params: {:,}'.format(trainable_count))
print('Non-trainable params: {:,}'.format(non_trainable_count))
For tensorflow.keras this works for me.对于 tensorflow.keras 这对我有用。 Its from the tensorflow github code for the function print_layer_summary_with_connections() in layer_utils.py
它来自 tensorflow github 代码,用于 layer_utils.py 中的函数 print_layer_summary_with_connections()
import numpy as np
from tensorflow.python.util import object_identity
def count_params(weights):
return int(sum(np.prod(p.shape.as_list())
for p in object_identity.ObjectIdentitySet(weights)))
if hasattr(model, '_collected_trainable_weights'):
trainable_count = count_params(model._collected_trainable_weights)
else:
trainable_count = count_params(model.trainable_weights)
print (trainable_count)
另一种计算可训练参数的方法是:
model.count_params()
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