Concatination of Ragged Tensors Raises Value Error

Question

I am following the view on youtube here,

it shows the code

text_1 = tf.ragged.constant(
    [['who','is', 'Goerge', 'Washington'],
     ['What', 'is', 'the', 'weather', 'tomorrow']])
text_2 = tf.ragged.constant(['goodnight'])

text = tf.concat(text_1, text_2)
print(text)

But it raises the ValueError as follows:

ValueError: Tensor conversion requested dtype int32 for Tensor with dtype string:

What is wrong please?

felixwege · Answer 1 · 2019-11-21T02:42:30.027

0

In the docs it says that concat takes a list of tensors and an axis as arguments, like so

text = tf.concat([text_1, text_2], axis=-1)

This raises a ValueError because the shapes of the tensors don't match. Please specify what you want to achieve.

Edit:

In the video you linked to there appears to be a syntax error in this line: text_2 = tf.ragged.constant(['goodnight']]). (The brackets don't match.) It should really be text_2 = tf.ragged.constant([['goodnight']]), which achieves the result printed below the operation in the video.

edited Nov 21 '19 at 02:42

answered Nov 21 '19 at 01:43

felixwege

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1
6

This is the point the video is making, the new datatype: tf.ragged. I included the video there. – chikitin Nov 21 '19 at 02:19

score 0 · Answer 2 · answered Jun 15 '22 at 13:05

The tf.concat requires one list of tensors and a axis. And the text_2 should have the same dimentions of text_1

text_1 = tf.ragged.constant(
    [['who', 'is', 'Goerge', 'Washington'],
     ['What', 'is', 'the', 'weather', 'tomorrow']])
text_2 = tf.ragged.constant([['goodnight']])

text = tf.concat([text_1, text_2], 0)
print(text)

Concatination of Ragged Tensors Raises Value Error

2 Answers2