Wednesday, March 13, 2019
Flatten, Reshape, and Squeeze Explained - Tensors for Deep Learning with...
Matrix is a rank 2 tensor. There are two axis one is an array, one is individual numbers.
Check the dimensions of tensors using .size() or .shape()
Obtain the rank of the tensor by checking the length of its shape
len(tensor.shape) #returns 2 for matrix
number of elements in the tensor, is the product of the component values in the shape torch.tensor(my_tensor.shape).prod()
my_tensor.numel() #number of elements
number of elements is important in reshaping
reshaping does not change underlining data just change the shape
AutoML machine learning deep learning without code by Uber, Ludwig allows users to train and make inference deep learning model without co...
In this downtown startup work space design the designers used fat boy bean bags and an extra wide step tiered staircase to create work space...
Google's algorithm has pushed websites to deploy mobile friendly websites, but sometimes business owners and developers really need to a...
The bogus request from P2PU to hunt for HTML tags in real life has yielded a lot of good thoughts. My first impression was that this is stup...