Understanding Dropout Layer In PyTorch
Dropout() in PyTorch: - Randomly zeros or multiplies elements from input tensor. - p (default=0.5): probability of an element to be zeroed (0 <= x <= 1). - inplace (default=False): performs operation in-place, keep False for stability.
Buy Me a Coffee☕ *Memos: My post explains Dropout Layer. My post explains manual_seed(). My post explains requires_grad. Dropout() can get the 0D or more D tensor of the zero or more elements randomly zeroed or multiplied from the 0D or more D tensor of zero or more elements as shown below: *Memos: The 1st argument for initialization is p(Optional-Default:0.5-Type:float): *Memos: It's the probability of an element to be zeroed. It must be 0 <= x <= 1. The 2nd argument for initialization is inplace(Optional-Default:False-Type:bool): It does in-place operation. Keep it False because it's...