We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Hi, I found the implementation of accuracy just take the logits and then pass it into a softmax.
pred = tf.nn.softmax(logit) acc = tf.reduce_mean(tf.cast(tf.equal(tf.argmax(pred, axis=1), labels), dtype=tf.float32))
However, the computation of the logits make use the ground truth labels. So how can this be true?
Thank you.
你好,我发现计算准确率的实现是用arcface 算法生成的logits 直接进行softmax函数计算的, 但是再arcface 算法中,logits 的生成需要用到数据的真实label。所以测试集的准确率是不是不可以这样计算? 谢谢
The text was updated successfully, but these errors were encountered:
+1
Sorry, something went wrong.
No branches or pull requests
Hi, I found the implementation of accuracy just take the logits and then pass it into a softmax.
However, the computation of the logits make use the ground truth labels. So how can this be true?
Thank you.
你好,我发现计算准确率的实现是用arcface 算法生成的logits 直接进行softmax函数计算的, 但是再arcface 算法中,logits 的生成需要用到数据的真实label。所以测试集的准确率是不是不可以这样计算?
谢谢
The text was updated successfully, but these errors were encountered: