python - How to resize a PyTorch tensor? - Stack Overflow
stackoverflow.com › questions › 58676688Nov 03, 2019 · import torch.nn.functional as nnf x = torch.rand(5, 1, 44, 44) out = nnf.interpolate(x, size=(224, 224), mode='bicubic', align_corners=False) If you really care about the accuracy of the interpolation, you should have a look at ResizeRight: a pytorch/numpy package that accurately deals with all sorts of "edge cases" when resizing images. This can have effect when directly merging features of different scales: inaccurate interpolation may result with misalignments.
One-Dimensional Tensors in Pytorch
machinelearningmastery.com › one-dimensional1 day ago · One-Dimensional Tensors in Pytorch. PyTorch is an open-source deep learning framework based on Python language. It allows you to build, train, and deploy deep learning models, offering a lot of versatility and efficiency. PyTorch is primarily focused on tensor operations while a tensor can be a number, matrix, or a multi-dimensional array.
torch.Tensor — PyTorch 1.10.1 documentation
pytorch.org › docs › stableTensor.new_full. Returns a Tensor of size size filled with fill_value. Tensor.new_empty. Returns a Tensor of size size filled with uninitialized data. Tensor.new_ones. Returns a Tensor of size size filled with 1. Tensor.new_zeros. Returns a Tensor of size size filled with 0. Tensor.is_cuda. Is True if the Tensor is stored on the GPU, False ...
torch.Tensor — PyTorch 1.10.1 documentation
https://pytorch.org/docs/stable/tensorstorch.ByteTensor. /. 1. Sometimes referred to as binary16: uses 1 sign, 5 exponent, and 10 significand bits. Useful when precision is important at the expense of range. 2. Sometimes referred to as Brain Floating Point: uses 1 sign, 8 exponent, and 7 significand bits. Useful when range is important, since it has the same number of exponent bits ...