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tensorflow: is there a way to specify XLA_GPU with tensorflow?
TensorFlow with PhonegapIs there a way to send data from Tensorflow to Arduino by Bluetooth?Is there a way to replace existing values with NaNRegression with Neural Networks in Tensorflow problemData extraction with TensorflowWhile using TensorFlow, is there some way I can 'create' the input values on the fly?Logistic Regression with Tensorflowproblems with installing tensorflow using anacondaIs there any way to make tensorflow serving server with multiple models linked dataflow?tensorflow: is there a way to specify XLA_GPU with tensorflow?
$begingroup$
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
$endgroup$
migrated from ai.stackexchange.com 9 hours 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
$endgroup$
migrated from ai.stackexchange.com 9 hours 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
$endgroup$
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
python tensorflow
asked yesterday
fu DLfu DL
83
83
migrated from ai.stackexchange.com 9 hours 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.
migrated from ai.stackexchange.com 9 hours 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 |
add a comment |
1 Answer
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$begingroup$
try 'device:XLA_GPU:0'
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')
$endgroup$
add a comment |
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1 Answer
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$begingroup$
try 'device:XLA_GPU:0'
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')
$endgroup$
add a comment |
$begingroup$
try 'device:XLA_GPU:0'
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')
$endgroup$
add a comment |
$begingroup$
try 'device:XLA_GPU:0'
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')
$endgroup$
try 'device:XLA_GPU:0'
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')
answered yesterday
Yong Jia
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