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Questions - ragged-tensors

how to pad sequences in a tensor slice dataset in TensorFlow?

I have a tensor slice dataset made from two ragged tensors. tensor_a is like: <tf.RaggedTensor [[3, 3, 5], [3, 3, 14, 4, 17, 20], [3, 14, 22, 17]]> tensor_b is like: <tf.RaggedTensor [[-1, 1,...
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pieckannie

python

tensorflow

padding

ragged-tensors

Votes: 0

Answers: 1

Latest Answer

You could try something like this: import tensorflow as tf tensor_a = tf.ragged.constant([[3, 3, 5], [3, 3, 14, 4, 17, 20], [3, 14, 22, 17]]) tensor_b = tf.ragged.constant([[-1, 1, -1], [-1, -1, 1, -...
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AloneTogether

How to save ragged tensor as a file?

How can I save a ragged tensor as a file on my disk and then reuse it in calculations opening it from the disk? Tensor consists of a nested array of numbers with 4 signs after the point. (I'm working ...
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Vvictory

python

keras

tensor

ragged-tensors

Votes: 0

Answers: 1

Latest Answer

I don't know your context but, You can save any object to a file using the pickle module. Like this import pickle the_object = object with open("a_file_name.pkl", "wb") as f: ...
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osbm

Sample from ragged tensor

I have a raggedTensor of row_lens going from 1 to up to 10k. I would like to select elements randomly from it with an upper limit on the number per row in a scalable way. Like in this example: vect = ...
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Nodiz

python

tensorflow

ragged-tensors

Votes: 0

Answers: 1

Latest Answer

You can try using tf.map_fn in graph mode: import tensorflow as tf vect = tf.ragged.constant([[1,2,3],[4,5],[6],[7,8,9,10,11,12,13]]) @tf.function def sample(x, samples=3): length = tf.shape(x)[0]...
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AloneTogether

IndexError: Dimension out of range (expected to be in range of [-2, 1], but got 3)

I created a random function with the line below x = torch.randn(4, 3) and used the transpose function as shown here torch.transpose(x, 0, 1) I got the error line below. Who can assist with a solutio...
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Lamosh

python

function

pytorch

transpose

ragged-tensors

python

function

pytorch

transpose

ragged-tensors

Votes: 0

Answers: 1

Latest Answer

You are trying to transpose x = torch.randn(4, 3), which is 2D. torch.transpose(x, 0, 1) works fine because you swap dimensions 0 and 1. But then, you try to swap dimensions 0 and 3 by doing torch.tra...
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Yekaterina

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