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Questions - pytorch

How can I find multiple maximum indices of a torch tensor?

If I have a tensor which has multiple maximum values how can I get all the indices of maximum value. I have tried torch.argmax(tensor) but it only gives me the first index. >>> a_list = [3,23...
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H.Jamil

python

pytorch

tensor

Votes: 0

Answers: 1

Latest Answer

Find the maximum value, then find all elements with that value. (x == torch.max(x)).nonzero() Note: nonzero may also be called with as_tuple=True, which may be helpful.
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Mateen Ulhaq

Using the encoder part only from T5 model

I want to build a classification model that needs only the encoder part of language models. I have tried Bert, Roberta, xlnet, and so far I have been successful. I now want to test the encoder part on...
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ls_grep

deep-learning

pytorch

huggingface-transformers

transformer-model

encoder-decoder

Votes: 0

Answers: 1

Latest Answer

Load T5 encoder checkpoint only: from transformers import T5EncoderModel T5EncoderModel._keys_to_ignore_on_load_unexpected = ["decoder.*"] auto_model = T5EncoderModel.from_pretrained("t...
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Dương Xuân Hiếu

How to get the ROC curve of a neural network?

I'm trying to get the ROC curve for my Neural Network. My network uses pytorch and im using sklearn to get the ROC curve. My model outputs the binary right and wrong and also the probability of the ou...
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Samuel Fipps

python

scikit-learn

neural-network

pytorch

roc

Votes: 0

Answers: 1

Latest Answer

Function roc_curve expects array with true labels y_true and array with probabilities for positive class y_score (which usually means class 1). Therefore what you need is not _, pred = torch.max(outpu...
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draw

Pytorch-> LSTM-> RuntimeError: input must have 3 dimensions, got 2

I'm facing error in LSTM input dimensions with following model code: class Model(nn.Module): def __init__(self, input_size, hidden_size, num_layers, num_keys): super(Model, self).__init__() se...
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annonyos

python

pytorch

classification

lstm

Votes: 0

Answers: 1

Latest Answer

I got it, the input data containing -1 values. I have used map function to convert negative integers into positive as following: line = tuple(map(int, line.strip().split())) Please make it sure for ...
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annonyos

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