The accuracy calculation in tensorflow is calculated in units of batch_size.

it seems to say on the Internet that accuracy in TF is calculated according to batch_size (denominator batch_size). Why is it that when batch_size = 4 is set, the output accuracy of each batch_size after updating the model parameters is not one of 0meme 0.25meme0.5mag0.75? But a result that is difficult to divide, such as 0.8763? I don"t know if there is any deviation in my understanding.

Deep-learning machine-learning tensorflow python
Mar.25,2021

this depends on which accuracy you use. There are two kinds of accuracy of TF you know so far:

  1. stream-acc: this is to count the accuracy of all past training results
  2. batch-acc: this is the accuracy you understand

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