text: - .
  Reposted with permission.
  If you are implementing Softmax in Pytorch and you already know Pytorch well, scroll down to the Deep Dive section and grab the code. pe-requisites: the demonstrative codes are written with Python list comprehension (scroll down to see an entire section explaining list comprehension). The math operations demonstrated are intuitive and code agnostic: it comes down to taking exponentials, sums and division aka the normalization step. This article is for your personal use only, not for production or commercial usage. Please read our disclaimer.ipediaLog). If you are not familiar with Python list comprehension, read the explanation in the next section first. Nonesample. Read it here.). In fact cross entropy loss isneedswant.Read our full Cross Entropy Loss tutorial here.
  Deep Dive Softmax
  For Softmax deep dive read our article Softmax Beyond the Basics. There you can also find explanation that Softmax and Sigmoid are equivalent for binary classification. Different flavors and implementations of Softmax in Tensorflow and Pytorch. Coming soon in Softmax Beyond the Basics: How to graph Softmax function? Is there a more efficient way to calculate Softmax for big datasets? Stay tuned. Get alerts subscribe@uniqtech.co
  Softmax Formula in Pytorch
  def softmax(x): return torch.exp(x)/torch.sum(torch.exp(x), dim=1).view(-1,1)
  dim=1is for
  torch.sum()to sum each row across all the columns,
  .view(-1,1)is for preventing broadcasting. For details of this formula, visit our Softmax Beyond the Basics article. The above is the formula. If you are just looking for an API then use
  softmaxor
  LogSoftmaxsee Pytorch documentation.%.
  Update History
  - August 2019 Code snippet for Pytorch Softmax
  - July 2019 A discussion on cross entropy evaluation of Softmax
  - June 2019 Correction: there was an incorrect statement about Sigmoid and it has been removed. Remember Sigmoid predicts one class for example Prob(class=A) to calculate Prob(class=B) just do 1-Prob(class=A) because there are only two classes in binary classification. It’s an either or relation. Also changed the Deep Dive section.
  - May 11 2019 In Progress: a deep dive on Softmax source code Softmax Beyond the Basics (post under construction): implementation of Softmax in Pytorch Tensorflow, Softmax in practice, in production.
  - Coming soon: citation for all the sections to make the article beginner friendly and robust at the same time.
  - InProgress May 11 2019: Softmax Beyond the Basics, Softmax in textbooks and university lecture slides
  - Coming soon: logsoftmax function explained — — — 