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pytensor
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2718da3f
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2718da3f
authored
4月 22, 2015
作者:
orhanf
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faq.txt
doc/faq.txt
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optimizations.txt
doc/optimizations.txt
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doc/faq.txt
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2718da3f
...
@@ -79,7 +79,7 @@ garbage collection will keep all intermediate results' memory space to allow to
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@@ -79,7 +79,7 @@ garbage collection will keep all intermediate results' memory space to allow to
reuse them during the next call to the same Theano function, if they are of the
reuse them during the next call to the same Theano function, if they are of the
correct shape. The shape could change if the shapes of the inputs change.
correct shape. The shape could change if the shapes of the inputs change.
.. unsafe_optimization:
..
_
unsafe_optimization:
Unsafe optimization
Unsafe optimization
===================
===================
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doc/optimizations.txt
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2718da3f
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@@ -54,6 +54,7 @@ Optimization FAST_RUN FAST_COMPILE
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@@ -54,6 +54,7 @@ Optimization FAST_RUN FAST_COMPILE
:term:`elemwise fusion` x
:term:`elemwise fusion` x
:term:`GPU transfer` x
:term:`GPU transfer` x
:term:`local_log_softmax` x x
:term:`local_log_softmax` x x
:term:`local_remove_all_assert`
========================================================= ========= ============ =============
========================================================= ========= ============ =============
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@@ -258,3 +259,13 @@ Optimization FAST_RUN FAST_COMPILE
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@@ -258,3 +259,13 @@ Optimization FAST_RUN FAST_COMPILE
It can happen due to rounding errors that the softmax probability of one value gets to 0.
It can happen due to rounding errors that the softmax probability of one value gets to 0.
Taking the log of 0 would generate -inf that will probably generate NaN later.
Taking the log of 0 would generate -inf that will probably generate NaN later.
We return a closer answer.
We return a closer answer.
local_remove_all_assert
This is an unsafe optimization.
For the fastest possible Theano, this optimization can be enabled by
setting ``optimizer_including=local_remove_all_assert`` which will
remove all assertions in the graph for checking user inputs are valid.
Use this optimization if you are sure everthing is valid in your graph.
See :ref:`unsafe_optimization`
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