30.12.2021 · Is it possible to assign values to an sparse tensor after initialization? I tried. import torch a = torch.sparse_coo_tensor(size=(3,4)) a[1,2] = 1 which gave me the clear answer: "Cannot assign to a sparse tensor". Is there any workaround or other way to update values?
18.09.2018 · What about. tensor[tensor==4] = 16 Assuming you want to replace for example each 4 with a 16. Edit: you could also do this with a tensor, but you would need to do it like tensor[tensor==4] = sixteens_tensor.clone() if you want to do it in autograd on a leaf variable. Also the sixteens_tensor must contain exactly as many values as there are 4s in tensor
TensorFlow allows you to define Variable objects, whose values can be changed. When creating a variable, you can set an initial value explicitly, or you can use ...
16.06.2020 · TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks. convert_to_tensor () is used to convert the given value to a Tensor. Syntax: tensorflow.convert_to_tensor ( value, dtype, dtype_hint, name ) Parameters: value: It is the value that needed to be converted to Tensor.
01.02.2020 · Convert this vector into two arrays containing the actual indices (idx_keep, idx_replace). This may be done in many ways but I believe using tf.where is the most concise method. Create a vector with the values to be replaced. In this example, the new value will be -inf, replicated N times where N = number of elements to be replaces = len(idx ...
28.05.2021 · t=tensor([0.1 0.2 0.3 0.4 0.5 0.6]) now i need to modify this existing tensor t as follows: t=tensor([0.1 0.2 0.7 0.4 0.8 0.6]) I tried as follows: t=tensor([0.1 0.2 ...
How to replace certain values in Tensorflow tensor with the values of the other tensor? I have a Tensorflow tensor A of size (64, 2, 82, 1), and I want to ...
06.05.2016 · However, I have no idea about how to modify the values in tensor like the way using numpy. The best way of doing so is that it is able to modify tensor directly. Yet, it seems not possible in the current version of Tensorflow. An alternative way is changing tensor to ndarray for the process, and then use tf.convert_to_tensor to change back.