TensorFlow Estimator clear_deivces in exporters?
The S.O. question load SavedModel
with different device placement explores how to use the Estimator
API to save a model and load it on a different device.
According to several questions so far, once a model has been saved with a manual device
placement, this is not feasible. However, according to @Yiding:
your question 1 can work only if you clear all devices when you export the model in the original tensorflow code, with flag
clear_devices=True
.
If we look at the TensorFlow docs for BestExporter
__init__(
name='best_exporter',
serving_input_receiver_fn=None,
event_file_pattern='eval/*.tfevents.*',
compare_fn=_loss_smaller,
assets_extra=None,
as_text=False,
exports_to_keep=5
)
it is apparent that clear_devices
is not an option.
So how can I get around this?
python tensorflow export tensorflow-estimator
add a comment |
The S.O. question load SavedModel
with different device placement explores how to use the Estimator
API to save a model and load it on a different device.
According to several questions so far, once a model has been saved with a manual device
placement, this is not feasible. However, according to @Yiding:
your question 1 can work only if you clear all devices when you export the model in the original tensorflow code, with flag
clear_devices=True
.
If we look at the TensorFlow docs for BestExporter
__init__(
name='best_exporter',
serving_input_receiver_fn=None,
event_file_pattern='eval/*.tfevents.*',
compare_fn=_loss_smaller,
assets_extra=None,
as_text=False,
exports_to_keep=5
)
it is apparent that clear_devices
is not an option.
So how can I get around this?
python tensorflow export tensorflow-estimator
add a comment |
The S.O. question load SavedModel
with different device placement explores how to use the Estimator
API to save a model and load it on a different device.
According to several questions so far, once a model has been saved with a manual device
placement, this is not feasible. However, according to @Yiding:
your question 1 can work only if you clear all devices when you export the model in the original tensorflow code, with flag
clear_devices=True
.
If we look at the TensorFlow docs for BestExporter
__init__(
name='best_exporter',
serving_input_receiver_fn=None,
event_file_pattern='eval/*.tfevents.*',
compare_fn=_loss_smaller,
assets_extra=None,
as_text=False,
exports_to_keep=5
)
it is apparent that clear_devices
is not an option.
So how can I get around this?
python tensorflow export tensorflow-estimator
The S.O. question load SavedModel
with different device placement explores how to use the Estimator
API to save a model and load it on a different device.
According to several questions so far, once a model has been saved with a manual device
placement, this is not feasible. However, according to @Yiding:
your question 1 can work only if you clear all devices when you export the model in the original tensorflow code, with flag
clear_devices=True
.
If we look at the TensorFlow docs for BestExporter
__init__(
name='best_exporter',
serving_input_receiver_fn=None,
event_file_pattern='eval/*.tfevents.*',
compare_fn=_loss_smaller,
assets_extra=None,
as_text=False,
exports_to_keep=5
)
it is apparent that clear_devices
is not an option.
So how can I get around this?
python tensorflow export tensorflow-estimator
python tensorflow export tensorflow-estimator
asked Nov 21 '18 at 10:09
SumNeuronSumNeuron
1,323826
1,323826
add a comment |
add a comment |
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