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sec2.1_ml
deeplearning
Commits
3cdf1543
Commit
3cdf1543
authored
Aug 02, 2018
by
Marius Kriegerowski
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upd
parent
d7613c7a
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3 changed files
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28 additions
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1 deletion
+28
-1
pinky/README.md
pinky/README.md
+16
-0
pinky/src/model.py
pinky/src/model.py
+3
-1
pinky/src/optimize.py
pinky/src/optimize.py
+9
-0
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pinky/README.md
View file @
3cdf1543
...
...
@@ -18,3 +18,19 @@ You can dump your examples to TFRecordDatasets to accelerate io operations:
and use the newly created config file to run
`--train`
Tests
-----
-
basic learning (synthetics, real data)
-
synthetics, layered cake, train with top and bottom layer containing events.
Validate with events within middle layer
-
test extrapolation with fault plane geometry
-
synthetic pretraining
-
hyperparameter optimization using skopt
Outlook
-------
-
increase z error weight -> improve z estimates
pinky/src/model.py
View file @
3cdf1543
...
...
@@ -68,6 +68,8 @@ class Model(Object):
:param kernel_width: convolution kernel size accross time axis
(Needs some debugging and checking)
TODO:
- cross_channel_kernel
'''
_
,
n_channels
,
n_samples
,
_
=
input
.
shape
...
...
@@ -113,7 +115,7 @@ class Model(Object):
# tf.summary.image('input', features)
for
ilayer
in
range
(
params
.
get
(
'n_layers'
,
3
)):
input
=
self
.
time_axis_cnn
(
input
,
n_filters
,
1
,
input
=
self
.
time_axis_cnn
(
input
,
n_filters
*
(
1
+
ilayer
)
,
1
,
kernel_width
=
int
(
kernel_width
+
ilayer
*
kernel_width_factor
),
name
=
'conv_%s'
%
ilayer
,
training
=
training
)
# conv = self.time_axis_cnn(conv, n_filters*2, 1, kernel_width=2, name='conv2',
...
...
pinky/src/optimize.py
View file @
3cdf1543
import
matplotlib
as
mpl
mpl
.
use
(
'PDF'
)
import
os
from
.util
import
delete_if_exists
from
skopt
import
gp_minimize
...
...
@@ -32,6 +35,12 @@ class Optimizer(Object):
path_out
=
String
.
T
(
default
=
'optimizer-results'
,
help
=
'base path where to store results, plots and logs'
)
def
__init__
(
self
,
**
kwargs
):
'''
TODO:
- optimize kernel heigth (cross_channel_kernel)
'''
super
().
__init__
(
**
kwargs
)
self
.
model
=
None
self
.
result
=
None
...
...
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