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pytensor
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1bb10871
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1bb10871
authored
10月 25, 2012
作者:
lamblin
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Merge pull request #1023 from nouiz/doc_python_mem
Doc python mem
上级
b8e79c60
1d02cf5b
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8 个修改的文件
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NEWS.txt
NEWS.txt
+0
-2
NEWS.txt
doc/NEWS.txt
+0
-2
index.txt
doc/index.txt
+1
-1
install.txt
doc/install.txt
+1
-1
conv.txt
doc/library/tensor/nnet/conv.txt
+1
-1
index.txt
doc/tutorial/index.txt
+1
-0
python-memory-management.txt
doc/tutorial/python-memory-management.txt
+3
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python.txt
doc/tutorial/python.txt
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-0
没有找到文件。
NEWS.txt
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1bb10871
...
@@ -23,8 +23,6 @@ Highlights:
...
@@ -23,8 +23,6 @@ Highlights:
Known bugs:
Known bugs:
* A few crash cases that will be fixed by the final release.
* A few crash cases that will be fixed by the final release.
* CAReduce with NaN in inputs do not return the correct output. (reported by Pascal L.)
* This is used in tensor.{all,any,max,mean,prod,sum} and in the grad of PermuteRowElements.
Bug fixes:
Bug fixes:
* Outputs of Scan nodes could contain corrupted values: some parts of the
* Outputs of Scan nodes could contain corrupted values: some parts of the
...
...
doc/NEWS.txt
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1bb10871
...
@@ -23,8 +23,6 @@ Highlights:
...
@@ -23,8 +23,6 @@ Highlights:
Known bugs:
Known bugs:
* A few crash cases that will be fixed by the final release.
* A few crash cases that will be fixed by the final release.
* CAReduce with NaN in inputs do not return the correct output. (reported by Pascal L.)
* This is used in tensor.{all,any,max,mean,prod,sum} and in the grad of PermuteRowElements.
Bug fixes:
Bug fixes:
* Outputs of Scan nodes could contain corrupted values: some parts of the
* Outputs of Scan nodes could contain corrupted values: some parts of the
...
...
doc/index.txt
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1bb10871
...
@@ -50,7 +50,7 @@ installation and configuration, see :ref:`installing Theano <install>`.
...
@@ -50,7 +50,7 @@ installation and configuration, see :ref:`installing Theano <install>`.
Master Tests Status:
Master Tests Status:
.. image:: https://secure.travis-ci.org/Theano/Theano.png
.. image:: https://secure.travis-ci.org/Theano/Theano.png
?branch=master
:target: http://travis-ci.org/Theano/Theano/builds
:target: http://travis-ci.org/Theano/Theano/builds
.. _available on PyPI: http://pypi.python.org/pypi/Theano
.. _available on PyPI: http://pypi.python.org/pypi/Theano
...
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doc/install.txt
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1bb10871
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@@ -206,7 +206,7 @@ Bleeding-edge install instructions
...
@@ -206,7 +206,7 @@ Bleeding-edge install instructions
Master Tests Status:
Master Tests Status:
.. image:: https://secure.travis-ci.org/Theano/Theano.png
.. image:: https://secure.travis-ci.org/Theano/Theano.png
?branch=master
:target: http://travis-ci.org/Theano/Theano/builds
:target: http://travis-ci.org/Theano/Theano/builds
If you are a developer of Theano, then check out the :ref:`dev_start_guide`.
If you are a developer of Theano, then check out the :ref:`dev_start_guide`.
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doc/library/tensor/nnet/conv.txt
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1bb10871
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@@ -8,7 +8,7 @@
...
@@ -8,7 +8,7 @@
Two similar implementation exists for conv2d:
Two similar implementation exists for conv2d:
:func:`signal.conv2d <theano.tensor.signal.conv.conv2d>` and
:func:`signal.conv2d <theano.tensor.signal.conv.conv2d>` and
:func:`nnet.conv2d <theano.tensor.nnet.conv.conv2d>. The former implements a traditional
:func:`nnet.conv2d <theano.tensor.nnet.conv.conv2d>
`
. The former implements a traditional
2D convolution, while the latter implements the convolutional layers
2D convolution, while the latter implements the convolutional layers
present in convolutional neural networks (where filters are 3D and pool
present in convolutional neural networks (where filters are 3D and pool
over several input channels).
over several input channels).
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doc/tutorial/index.txt
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1bb10871
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@@ -43,3 +43,4 @@ you out.
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@@ -43,3 +43,4 @@ you out.
debug_faq
debug_faq
extending_theano
extending_theano
faq
faq
python-memory-management
doc/tutorial/python-memory-management.
rs
t
→
doc/tutorial/python-memory-management.
tx
t
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1bb10871
.. _python-memory-management:
Python Memory Management
Python Memory Management
========================
========================
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@@ -156,7 +158,7 @@ on a 32-bit platform and
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@@ -156,7 +158,7 @@ on a 32-bit platform and
96 [4, 'toaster', 230.1]
96 [4, 'toaster', 230.1]
on a 64-bit platform. An empty list eats up 72 bytes. The size of an
on a 64-bit platform. An empty list eats up 72 bytes. The size of an
empty, 64-bit C++ ``std::list()``is only 16 bytes, 4-5 times less. What
empty, 64-bit C++ ``std::list()``
is only 16 bytes, 4-5 times less. What
about tuples? (and dictionaries?):
about tuples? (and dictionaries?):
::
::
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doc/tutorial/python.txt
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1bb10871
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@@ -11,3 +11,5 @@ tutorials/exercises if you need to learn it or only need a refresher:
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@@ -11,3 +11,5 @@ tutorials/exercises if you need to learn it or only need a refresher:
* `Python Challenge <http://www.pythonchallenge.com/>`__
* `Python Challenge <http://www.pythonchallenge.com/>`__
* `Dive into Python <http://diveintopython.net/>`__
* `Dive into Python <http://diveintopython.net/>`__
* `Google Python Class <http://code.google.com/edu/languages/google-python-class/index.html>`__
* `Google Python Class <http://code.google.com/edu/languages/google-python-class/index.html>`__
We have a tutorial on how :ref:`python manage its memory <python-memory-management>`
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