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tensorflow: is there a way to specify XLA_GPU with tensorflow?

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0

$begingroup$

following code is used to specify device on which tf node is running on

with tf.device('/gpu:0'):
 a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

i have already known:
this post, tensorflow doc and xla demo

what i want to know is:

is there a way to specify XLA_GPU as the device on which tf node is running on

with tf.device('/XLA_GPU:0'):
 a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

executing the code above gives ValueError: Unknown attribute: 'device' in '/job:localhost/replica:0/task:0/device:/XLA_GPU:0'

this is 100% reproducible on google colab.

python tensorflow

share|improve this question

asked Mar 16 at 12:32

fu DLfu DL

83

$endgroup$

migrated from ai.stackexchange.com 2 days ago

This question came from our site for people interested in conceptual questions about life and challenges in a world where "cognitive" functions can be mimicked in purely digital environment.

add a comment | 

0

$begingroup$

following code is used to specify device on which tf node is running on

with tf.device('/gpu:0'):
 a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

i have already known:
this post, tensorflow doc and xla demo

what i want to know is:

is there a way to specify XLA_GPU as the device on which tf node is running on

with tf.device('/XLA_GPU:0'):
 a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

executing the code above gives ValueError: Unknown attribute: 'device' in '/job:localhost/replica:0/task:0/device:/XLA_GPU:0'

this is 100% reproducible on google colab.

python tensorflow

share|improve this question

asked Mar 16 at 12:32

fu DLfu DL

83

$endgroup$

migrated from ai.stackexchange.com 2 days ago

This question came from our site for people interested in conceptual questions about life and challenges in a world where "cognitive" functions can be mimicked in purely digital environment.

add a comment | 

$begingroup$

following code is used to specify device on which tf node is running on

with tf.device('/gpu:0'):
 a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

i have already known:
this post, tensorflow doc and xla demo

what i want to know is:

is there a way to specify XLA_GPU as the device on which tf node is running on

with tf.device('/XLA_GPU:0'):
 a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

executing the code above gives ValueError: Unknown attribute: 'device' in '/job:localhost/replica:0/task:0/device:/XLA_GPU:0'

this is 100% reproducible on google colab.

python tensorflow

share|improve this question

asked Mar 16 at 12:32

fu DLfu DL

83

$endgroup$

with tf.device('/gpu:0'):
 a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

with tf.device('/XLA_GPU:0'):
 a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

share|improve this question

asked Mar 16 at 12:32

fu DLfu DL

83

share|improve this question

asked Mar 16 at 12:32

fu DLfu DL

83

asked Mar 16 at 12:32

fu DLfu DL

83

asked Mar 16 at 12:32

fu DLfu DL

83

with tf.device('device:XLA_GPU:0'):
 a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

with tf.device('device:XLA_GPU:0'):
 a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

with tf.device('device:XLA_GPU:0'):
 a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

with tf.device('device:XLA_GPU:0'):
 a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

with tf.device('device:XLA_GPU:0'):
 a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')