I suspect your test_image has an additional alpha channel per pixel, thus it has 4 channels instead of only three. Try: test_image = Image.open(test_image_name).convert(‘RGB’)
.data was an attribute of Variable (object representing Tensor with history tracking e.g. for automatic update), not Tensor. Actually, .data was giving access to the Variable‘s underlying Tensor. However, since PyTorch version 0.4.0, Variable and Tensor have been merged (into an updated Tensor structure), so .data disappeared along the previous Variable object (well Variable is … Read more
I just wanted to report my findings about loading a gensim embedding with PyTorch. Solution for PyTorch 0.4.0 and newer: From v0.4.0 there is a new function from_pretrained() which makes loading an embedding very comfortable. Here is an example from the documentation. import torch import torch.nn as nn # FloatTensor containing pretrained weights weight = … Read more
Explanation For neural networks, we usually use loss to assess how well the network has learned to classify the input image (or other tasks). The loss term is usually a scalar value. In order to update the parameters of the network, we need to calculate the gradient of loss w.r.t to the parameters, which is … Read more
The pytorch package that you’re installing comes with both cpu and gpu support, thus has a large size. It seems you’re using the free version of heroku, and only require the cpu support. The solution is to install the pytorch package for cpu only i.e. In requirements.txt, write the wheel file path corresponding to the … Read more
Yes, that is possible. Just create the objects by yourself, e.g. import torch.utils.data as data_utils train = data_utils.TensorDataset(features, targets) train_loader = data_utils.DataLoader(train, batch_size=50, shuffle=True) where features and targets are tensors. features has to be 2-D, i.e. a matrix where each line represents one training sample, and targets may be 1-D or 2-D, depending on whether … Read more
I assume you are asking whether these data augmentation transforms (e.g. RandomHorizontalFlip) actually increase the size of the dataset as well, or are they applied on each item in the dataset one by one and not adding to the size of the dataset. Running the following simple code snippet we could observe that the latter … Read more
you can use this formula [(W−K+2P)/S]+1. W is the input volume – in your case 128 K is the Kernel size – in your case 5 P is the padding – in your case 0 i believe S is the stride – which you have not provided. So, we input into the formula: Output_Shape = … Read more
stack Concatenates sequence of tensors along a new dimension. cat Concatenates the given sequence of seq tensors in the given dimension. So if A and B are of shape (3, 4): torch.cat([A, B], dim=0) will be of shape (6, 4) torch.stack([A, B], dim=0) will be of shape (2, 3, 4)
Anyone who is looking for the solution refer below: It seems command to install torch not is working as expected, instead, you can try to install PyTorch using below command. It’s working and solved my above-mentioned issue. Run below command(for below-specified OS, package-manager, Language): # for OS: Windows, package-manager: pip, Language: python3.6 (below command is … Read more