In PyTorch I have a 5D tensor X of dimensions B x 9 x C x H x W. I want to convert it into a 4D tensor Y with dimensions B x 9C x H x W such that concatenation happens channel wise. To illustrate let, Then in the tensor Y, a to i should be channel wise concatenated.
Tag: tensor
How to get the last index of model’s prediction?
I am new to PyTorch. I have a variable pred which has a list of a tensor. So I wanted to access the last element which is the class. I did that by first converting the list into a tensor. Now, how do I access the last element or is there any better/efficient way of doing this? EDIT: For further
How to append rank 1 tensors using only tensorflow operations?
Say I have two rank 1 tensors of different (important) length: Now I want to append y to the end of x to give me the tensor: But I can’t seem to figure out how. I will be doing this inside a function that I will decorate with tf.function, and it is my understanding that everything needs to be tensorflow
How to convert a PyTorch sparse_coo_tensor into a PyTorch dense tensor?
I create a sparse_coo tensor in PyTorch: Now I want to convert a PyTorch sparse tensor into a PyTorch dense tensor. Which function can be used? Answer you can use to_dense as suggested in this example : And by the way, the documentation is here
What does .view() do in PyTorch?
What does .view() do to a tensor x? What do negative values mean? Answer view() reshapes the tensor without copying memory, similar to numpy’s reshape(). Given a tensor a with 16 elements: To reshape this tensor to make it a 4 x 4 tensor, use: Now a will be a 4 x 4 tensor. Note that after the reshape the