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Fix math and update timming #40

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Merged
merged 2 commits into from
Oct 2, 2014
Merged

Fix math and update timming #40

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93de4ed
Fix the math in lenet
nouiz Oct 2, 2014
fef6057
Update speed timing to faster results.
nouiz Oct 2, 2014
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6 changes: 4 additions & 2 deletions code/test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -77,9 +77,9 @@ def speed():
# 580 for the GPU. OS=Fedora 14, gcc=4.5.1, python/BLAS from EPD
# 7.1-2 (python 2.7.2, mkl unknow). BLAS with only 1 thread.

expected_times_64 = numpy.asarray([10.0, 22.5, 76.1, 73.7, 116.4,
expected_times_64 = numpy.asarray([9.8, 22.5, 76.1, 73.7, 116.4,
346.9, 381.9, 558.1, 186.3])
expected_times_32 = numpy.asarray([11.6, 29.6, 42.5, 66.5, 71,
expected_times_32 = numpy.asarray([8.1, 17.9, 42.5, 66.5, 71,
191.2, 226.8, 432.8, 176.2])

# Number with just 1 decimal are new value that are faster with
Expand Down Expand Up @@ -219,6 +219,7 @@ def do_tests():
print >> sys.stderr, 'gpu % expected/get', (
expected_times_gpu / gpu_times)

print
if do_float64 and do_float32:
print >> sys.stderr, 'float64/float32', (
float64_times / float32_times)
Expand All @@ -239,6 +240,7 @@ def compare(x, y):
# time and the real time, we consider this an error.
return sum((ratio < 0.95) + (ratio > 1.05))

print
if do_float64:
err = compare(expected_times_64, float64_times)
print >> sys.stderr, 'speed_failure_float64=' + str(err)
Expand Down
4 changes: 2 additions & 2 deletions doc/lenet.txt
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Expand Up @@ -139,10 +139,10 @@ feature map :math:`h^k` is obtained as follows (for :math:`tanh` non-linearities

.. Note::
Recall the following definition of convolution for a 1D signal.
:math:`o[n] = f[n]*g[n] = \sum_{u=-\infty}^{\infty} f[u] g[u-n] = \sum_{u=-\infty}^{\infty} f[n-u] g[u]`.
:math:`o[n] = f[n]*g[n] = \sum_{u=-\infty}^{\infty} f[u] g[n-u] = \sum_{u=-\infty}^{\infty} f[n-u] g[u]`.

This can be extended to 2D as follows:
:math:`o[m,n] = f[m,n]*g[m,n] = \sum_{u=-\infty}^{\infty} \sum_{v=-\infty}^{\infty} f[u,v] g[u-m,v-n]`.
:math:`o[m,n] = f[m,n]*g[m,n] = \sum_{u=-\infty}^{\infty} \sum_{v=-\infty}^{\infty} f[u,v] g[m-u,n-v]`.

To form a richer representation of the data, hidden layers are composed of
a set of multiple feature maps, :math:`\{h^{(k)}, k=0..K\}`.
Expand Down