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Will a tensorflow model give different results if trained in a previous version
I have a tensorflow model trained in tf version 1.1 and python 2.7. I'm running it in tf version 1.10 and python 3.6. After feeding the same data into the model in both versions, the outputs are slightly different. Of 512 outputs, 7 do not match. Is this a versioning issue, or something else? I appreciate your help.
python python-3.x python-2.7 tensorflow
asked Nov 19 '18 at 17:41
aveevuaveevu
607
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I have a tensorflow model trained in tf version 1.1 and python 2.7. I'm running it in tf version 1.10 and python 3.6. After feeding the same data into the model in both versions, the outputs are slightly different. Of 512 outputs, 7 do not match. Is this a versioning issue, or something else? I appreciate your help.
python python-3.x python-2.7 tensorflow
asked Nov 19 '18 at 17:41
aveevuaveevu
607
add a comment |
I have a tensorflow model trained in tf version 1.1 and python 2.7. I'm running it in tf version 1.10 and python 3.6. After feeding the same data into the model in both versions, the outputs are slightly different. Of 512 outputs, 7 do not match. Is this a versioning issue, or something else? I appreciate your help.
python python-3.x python-2.7 tensorflow
asked Nov 19 '18 at 17:41
aveevuaveevu
607
I have a tensorflow model trained in tf version 1.1 and python 2.7. I'm running it in tf version 1.10 and python 3.6. After feeding the same data into the model in both versions, the outputs are slightly different. Of 512 outputs, 7 do not match. Is this a versioning issue, or something else? I appreciate your help.
python python-3.x python-2.7 tensorflow
python python-3.x python-2.7 tensorflow
asked Nov 19 '18 at 17:41
aveevuaveevu
607
asked Nov 19 '18 at 17:41
aveevuaveevu
607
asked Nov 19 '18 at 17:41
aveevuaveevu
607
asked Nov 19 '18 at 17:41
aveevuaveevu
607
asked Nov 19 '18 at 17:41
aveevuaveevu
607
607
add a comment |
add a comment |
1 Answer
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Since your Tensorflow code may contain internal random number generator, you might check if you forgot to seed the random generator with the tf.random.set_random_seed(seed) function.
answered Nov 19 '18 at 17:44
leoburgyleoburgy
1107
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1 Answer
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1 Answer
1
active
oldest
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Since your Tensorflow code may contain internal random number generator, you might check if you forgot to seed the random generator with the tf.random.set_random_seed(seed) function.
answered Nov 19 '18 at 17:44
leoburgyleoburgy
1107
add a comment |
Since your Tensorflow code may contain internal random number generator, you might check if you forgot to seed the random generator with the tf.random.set_random_seed(seed) function.
answered Nov 19 '18 at 17:44
leoburgyleoburgy
1107
add a comment |
Since your Tensorflow code may contain internal random number generator, you might check if you forgot to seed the random generator with the tf.random.set_random_seed(seed) function.
answered Nov 19 '18 at 17:44
leoburgyleoburgy
1107
Since your Tensorflow code may contain internal random number generator, you might check if you forgot to seed the random generator with the tf.random.set_random_seed(seed) function.
answered Nov 19 '18 at 17:44
leoburgyleoburgy
1107
answered Nov 19 '18 at 17:44
leoburgyleoburgy
1107
answered Nov 19 '18 at 17:44
leoburgyleoburgy
1107
answered Nov 19 '18 at 17:44
leoburgyleoburgy
1107
1107
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