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machine-learning
MLAir
Commits
67bb6e0d
Commit
67bb6e0d
authored
5 years ago
by
Felix Kleinert
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update readme
parent
613a5e07
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Pipeline
#37663
failed
5 years ago
Stage: test
Stage: pages
Stage: deploy
Changes
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README.md
+1
-1
1 addition, 1 deletion
README.md
run.py
+3
-3
3 additions, 3 deletions
run.py
with
4 additions
and
4 deletions
README.md
+
1
−
1
View file @
67bb6e0d
...
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@@ -15,7 +15,7 @@ We assume that you have downloaded or cloned the project from GitLab or
*
Make sure that CUDA 10.0 is installed if you want to use Nvidia GPUs (compatible with TensorFlow 1.13.1).
Depending on your system (GPU available or not) you can create a virtual environment by executing
`python3 -m venv venv`
. Make sure that the venv is activated (
`source venv/bin/activate`
). Afterwards
`python3
.6
-m venv venv`
. Make sure that the venv is activated (
`source venv/bin/activate`
). Afterwards
you can install the requirements into the venv:
*
CPU version:
`pip install -r requirements.txt`
*
GPU version:
`pip install -r requirements_gpu.txt`
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run.py
+
3
−
3
View file @
67bb6e0d
...
...
@@ -17,7 +17,7 @@ from src.run_modules.training import Training
def
main
(
parser_args
):
station_filename
=
"
German_background_stations.json
"
# "German_stations.json"
station_filename
=
"
German_background_stations.json
"
with
open
(
station_filename
)
as
jfile
:
stations
=
json
.
load
(
jfile
)
...
...
@@ -27,11 +27,11 @@ def main(parser_args):
data_path
=
f
"
{
os
.
getcwd
()
}
/raw_input_IntelliO3-ts/
"
,
# hpc_hosts=["yo"], #
stations
=
stations
,
# stations=['DEBW107', 'DEBY081', 'DEBW013', 'DEBW076', 'DEBW087', 'DEBW001']
,
evaluate_bootstraps
=
False
,
station_type
=
'
background
'
,
window_lead_time
=
4
,
window_history_size
=
6
,
trainable
=
False
,
create_new_model
=
False
,
permute_data_on_training
=
True
,
extreme_values
=
3.
,
train_min_length
=
365
,
val_min_length
=
365
,
test_min_length
=
365
,
create_new_bootstraps
=
Tru
e
,
create_new_bootstraps
=
Fals
e
,
plot_list
=
[
"
PlotMonthlySummary
"
,
"
PlotStationMap
"
,
"
PlotClimatologicalSkillScore
"
,
"
PlotCompetitiveSkillScore
"
,
"
PlotBootstrapSkillScore
"
,
"
PlotConditionalQuantiles
"
,
"
PlotAvailability
"
],
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