Tensorflow - How to Convert int32 to string (using Python API for Tensorflow)
Simple question really but cannot seem to find a function in the TensorFlow docs or by googling.
How can I convert a tensor of type tf.int32 to one of type tf.string?
I tried simply casting it with something like this:
x = tf.constant([1,2,3], dtype=tf.int32)
x_as_string = tf.cast(x, dtype=tf.string) # hoping for this output: [ '1', '2', '3' ]
with tf.Session() as sess:
res = sess.run(x_as_string)
but hit the error message:
Cast int32 to string is not supported
Is there a simple function somewhere in the documentation that I am missing?
UPDATE:
To clarify: I realise I could 'work around' this issue using a python function with tf.py_func but asking if there is a solution in TensorFlow itself
python tensorflow
asked Nov 14 '18 at 13:09
Stewart_RStewart_R
4,30142448
add a comment |
Simple question really but cannot seem to find a function in the TensorFlow docs or by googling.
How can I convert a tensor of type tf.int32 to one of type tf.string?
I tried simply casting it with something like this:
x = tf.constant([1,2,3], dtype=tf.int32)
x_as_string = tf.cast(x, dtype=tf.string) # hoping for this output: [ '1', '2', '3' ]
with tf.Session() as sess:
res = sess.run(x_as_string)
but hit the error message:
Cast int32 to string is not supported
Is there a simple function somewhere in the documentation that I am missing?
UPDATE:
To clarify: I realise I could 'work around' this issue using a python function with tf.py_func but asking if there is a solution in TensorFlow itself
python tensorflow
asked Nov 14 '18 at 13:09
Stewart_RStewart_R
4,30142448
add a comment |
Simple question really but cannot seem to find a function in the TensorFlow docs or by googling.
How can I convert a tensor of type tf.int32 to one of type tf.string?
I tried simply casting it with something like this:
x = tf.constant([1,2,3], dtype=tf.int32)
x_as_string = tf.cast(x, dtype=tf.string) # hoping for this output: [ '1', '2', '3' ]
with tf.Session() as sess:
res = sess.run(x_as_string)
but hit the error message:
Cast int32 to string is not supported
Is there a simple function somewhere in the documentation that I am missing?
UPDATE:
To clarify: I realise I could 'work around' this issue using a python function with tf.py_func but asking if there is a solution in TensorFlow itself
python tensorflow
asked Nov 14 '18 at 13:09
Stewart_RStewart_R
4,30142448
Simple question really but cannot seem to find a function in the TensorFlow docs or by googling.
How can I convert a tensor of type tf.int32 to one of type tf.string?
I tried simply casting it with something like this:
x = tf.constant([1,2,3], dtype=tf.int32)
x_as_string = tf.cast(x, dtype=tf.string) # hoping for this output: [ '1', '2', '3' ]
with tf.Session() as sess:
res = sess.run(x_as_string)
but hit the error message:
Cast int32 to string is not supported
Is there a simple function somewhere in the documentation that I am missing?
UPDATE:
To clarify: I realise I could 'work around' this issue using a python function with tf.py_func but asking if there is a solution in TensorFlow itself
python tensorflow
python tensorflow
asked Nov 14 '18 at 13:09
Stewart_RStewart_R
4,30142448
asked Nov 14 '18 at 13:09
Stewart_RStewart_R
4,30142448
asked Nov 14 '18 at 13:09
Stewart_RStewart_R
4,30142448
asked Nov 14 '18 at 13:09
Stewart_RStewart_R
4,30142448
asked Nov 14 '18 at 13:09
Stewart_RStewart_R
4,30142448
4,30142448
add a comment |
add a comment |
1 Answer
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You can do that with the newly added (v1.12.0) tf.strings.format:
import tensorflow as tf
x = tf.constant([1, 2, 3], dtype=tf.int32)
x_as_string = tf.map_fn(lambda xi: tf.strings.format('{}', xi), x, dtype=tf.string)
with tf.Session() as sess:
res = sess.run(x_as_string)
print(res)
# [b'1' b'2' b'3']
answered Nov 14 '18 at 16:59
jdehesajdehesa
23.9k43554
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
You can do that with the newly added (v1.12.0) tf.strings.format:
import tensorflow as tf
x = tf.constant([1, 2, 3], dtype=tf.int32)
x_as_string = tf.map_fn(lambda xi: tf.strings.format('{}', xi), x, dtype=tf.string)
with tf.Session() as sess:
res = sess.run(x_as_string)
print(res)
# [b'1' b'2' b'3']
answered Nov 14 '18 at 16:59
jdehesajdehesa
23.9k43554
add a comment |
You can do that with the newly added (v1.12.0) tf.strings.format:
import tensorflow as tf
x = tf.constant([1, 2, 3], dtype=tf.int32)
x_as_string = tf.map_fn(lambda xi: tf.strings.format('{}', xi), x, dtype=tf.string)
with tf.Session() as sess:
res = sess.run(x_as_string)
print(res)
# [b'1' b'2' b'3']
answered Nov 14 '18 at 16:59
jdehesajdehesa
23.9k43554
add a comment |
You can do that with the newly added (v1.12.0) tf.strings.format:
import tensorflow as tf
x = tf.constant([1, 2, 3], dtype=tf.int32)
x_as_string = tf.map_fn(lambda xi: tf.strings.format('{}', xi), x, dtype=tf.string)
with tf.Session() as sess:
res = sess.run(x_as_string)
print(res)
# [b'1' b'2' b'3']
answered Nov 14 '18 at 16:59
jdehesajdehesa
23.9k43554
You can do that with the newly added (v1.12.0) tf.strings.format:
import tensorflow as tf
x = tf.constant([1, 2, 3], dtype=tf.int32)
x_as_string = tf.map_fn(lambda xi: tf.strings.format('{}', xi), x, dtype=tf.string)
with tf.Session() as sess:
res = sess.run(x_as_string)
print(res)
# [b'1' b'2' b'3']
answered Nov 14 '18 at 16:59
jdehesajdehesa
23.9k43554
answered Nov 14 '18 at 16:59
jdehesajdehesa
23.9k43554
answered Nov 14 '18 at 16:59
jdehesajdehesa
23.9k43554
answered Nov 14 '18 at 16:59
jdehesajdehesa
23.9k43554
23.9k43554
add a comment |
add a comment |
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