srch

Dec 08, 2018 · So first let me describe my use case. I have a tensor of shape NxCxseq_len. I have an index tensor of shape NxK (basically K from each batch) where K denotes the indices from the seq_len axis and I need to pick these specific samples.

torch.masked_select. torch.masked_select(input, mask, *, out=None) → Tensor. Returns a new 1-D tensor which indexes the input tensor according to the boolean mask mask which is a BoolTensor. The shapes of the mask tensor and the input tensor don’t need to match, but they must be broadcastable. Note.

Let's say you have a matrix a , and a bool mask m (with the same shape as a ) and you want to compute a.mean(dim=1) but only on elements that ...

Jan 13, 2022 · Defining class weights for BCE with multi-channel gaussian masks. vision. YASJAY (Srinath) January 13, 2022, 6:57pm #1.

torch.masked_select. Returns a new 1-D tensor which indexes the input tensor according to the boolean mask mask which is a BoolTensor. The shapes of the mask tensor and the input tensor don’t need to match, but they must be broadcastable. input ( Tensor) – the input tensor. out ( Tensor, optional) – the output tensor.

06.12.2020 · May I ask how to do masked argmax in Pytorch? For example I have a tensor t and a mask m: t = torch.tensor([20, 10, 50, 40]) m = numpy.array([True, True, False, True]) The masked argmax is 3 (corresponds to 40 in t) Thank you very much.

Does anyone know how to quickly apply a mask to a torch tensor? Say I have a tensor t_in with some values in it and a mask t_mask with ...

One tiny part of the crazy-complex Transformer code is tensor masking using the PyTorch masked_fill() function. You use a mask when you have ...

🐛 Describe the bug Indexing pytorch tensors behaves not the same as indexing numpy arrays. MWE that raises an IndexError: print('numpy arrays:') import numpy t = numpy.arange(2).reshape(1,1...

Jan 05, 2020 · I have a 84x84 pytorch tensor named target . I need to mask it with an 84x84 boolean numpy array which consists of True and False . This mask array is called mask.

05.01.2020 · I need to mask it with an 84x84 boolean numpy array which consists of True and False . This mask array is called mask ... [mask] , I get the er… I have a 84x84 pytorch tensor named target . I need to mask it with an 84x84 boolean numpy array which consists of True and False . This mask array is called mask. When I do ...

04.01.2020 · Pytorch mask tensor with boolean numpy array. Ask Question Asked 1 year, 11 months ago. Active 1 year, 11 months ago. Viewed 5k times 0 1. I have a 84x84 pytorch tensor named target. I need to mask it with an 84x84 boolean numpy array which consists of True and False. When I do target ...

Apr 05, 2020 · By using np.where to find the indices where there are zeroes in mask we get: m = mask == 0 i, _, l = np.where(m) i # array([0, 1, 1]) l # array([0, 1, 3]) Hence we'll be replacing the 0th column from the first 2D array and the 1st and 3rd from the second 2D array. We can now use these arrays to replace along the corresponding axes indexing as:

14.08.2019 · In numpy I could do the following: t_result = np.ma.array (t_in, mask=t_mask) That would mask all the values of t_in where the value of the equivalent index of t_mask is 0. Then I can do operations such as t_result.sum () and it will only give me the sum of the non-masked values. I’m primarily looking to do just that, but cannot get my head ...

def extract_bboxes(mask):. """Compute bounding boxes from masks. mask: [height, width, num_instances]. Mask pixels are either 1 or 0. Returns: bbox array ...

Aug 14, 2019 · In numpy I could do the following: t_result = np.ma.array (t_in, mask=t_mask) That would mask all the values of t_in where the value of the equivalent index of t_mask is 0. Then I can do operations such as t_result.sum () and it will only give me the sum of the non-masked values. I’m primarily looking to do just that, but cannot get my head ...

08.12.2018 · How do I convert a 2d mask to index while retaining the dimensions. like if my mask is of shape Nx1000. How do i use this to create a index tensor of size (N,) as each sample in the batch may not have the same number of masked elements. Thanks

The BaseMask interface allows accessing a mask in the following ways: ... It can be accessed as an array of integers which may be beneficial for some ...

Masks¶. In tasks like instance and panoptic segmentation, masks are commonly defined, and are defined by this package, as a multi-dimensional array (e.g. a NumPy array or a PyTorch tensor) with the following shape:

What the above code is doing is very simple, it reads an image from disk with cv2.imread(path) and saves the resulting numpy.array in training_data variable.

I think there is some confusion with the types. But this works. import torch tensor = torch.randn(84,84) c ...