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Luc Giffon
bolsonaro
Commits
ec55d270
Commit
ec55d270
authored
Mar 06, 2020
by
Charly Lamothe
Browse files
Starting to add a first version of weight density plot for stage4
parent
1db36b5d
Changes
1
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Inline
Side-by-side
code/compute_results.py
View file @
ec55d270
...
...
@@ -28,7 +28,6 @@ def extract_scores_across_seeds_and_extracted_forest_sizes(models_dir, results_d
experiment_train_scores
=
dict
()
experiment_dev_scores
=
dict
()
experiment_test_scores
=
dict
()
experiment_weights
=
dict
()
all_extracted_forest_sizes
=
list
()
# Used to check if all losses were computed using the same metric (it should be the case)
...
...
@@ -45,7 +44,6 @@ def extract_scores_across_seeds_and_extracted_forest_sizes(models_dir, results_d
experiment_train_scores
[
seed
]
=
list
()
experiment_dev_scores
[
seed
]
=
list
()
experiment_test_scores
[
seed
]
=
list
()
experiment_weights
[
seed
]
=
list
()
# List the forest sizes in models/{experiment_id}/seeds/{seed}/extracted_forest_sizes
extracted_forest_sizes
=
os
.
listdir
(
extracted_forest_sizes_root_path
)
...
...
@@ -66,8 +64,6 @@ def extract_scores_across_seeds_and_extracted_forest_sizes(models_dir, results_d
experiment_test_scores
[
seed
].
append
(
model_raw_results
.
test_score
)
# Save the metric
experiment_score_metrics
.
append
(
model_raw_results
.
score_metric
)
# Save the weights
#experiment_weights[seed].append(model_raw_results.model_weights)
# Sanity checks
if
len
(
set
(
experiment_score_metrics
))
>
1
:
...
...
@@ -76,7 +72,7 @@ def extract_scores_across_seeds_and_extracted_forest_sizes(models_dir, results_d
raise
ValueError
(
"The extracted forest sizes aren't the sames across seeds."
)
return
experiment_train_scores
,
experiment_dev_scores
,
experiment_test_scores
,
\
all_extracted_forest_sizes
[
0
],
experiment_score_metrics
[
0
]
#, experiment_weights
all_extracted_forest_sizes
[
0
],
experiment_score_metrics
[
0
]
def
extract_scores_across_seeds_and_forest_size
(
models_dir
,
results_dir
,
experiment_id
,
extracted_forest_sizes_number
):
experiment_id_path
=
models_dir
+
os
.
sep
+
str
(
experiment_id
)
# models/{experiment_id}
...
...
@@ -123,6 +119,37 @@ def extract_scores_across_seeds_and_forest_size(models_dir, results_dir, experim
return
experiment_train_scores
,
experiment_dev_scores
,
experiment_test_scores
,
experiment_score_metrics
[
0
]
def
extract_weights_across_seeds
(
models_dir
,
results_dir
,
experiment_id
):
experiment_id_path
=
models_dir
+
os
.
sep
+
str
(
experiment_id
)
# models/{experiment_id}
experiment_seed_root_path
=
experiment_id_path
+
os
.
sep
+
'seeds'
# models/{experiment_id}/seeds
experiment_weights
=
dict
()
# For each seed results stored in models/{experiment_id}/seeds
seeds
=
os
.
listdir
(
experiment_seed_root_path
)
seeds
.
sort
(
key
=
int
)
for
seed
in
seeds
:
experiment_seed_path
=
experiment_seed_root_path
+
os
.
sep
+
seed
# models/{experiment_id}/seeds/{seed}
extracted_forest_sizes_root_path
=
experiment_seed_path
+
os
.
sep
+
'extracted_forest_sizes'
# models/{experiment_id}/seeds/{seed}/forest_size
# {{seed}:[]}
experiment_weights
[
seed
]
=
list
()
# List the forest sizes in models/{experiment_id}/seeds/{seed}/extracted_forest_sizes
extracted_forest_sizes
=
os
.
listdir
(
extracted_forest_sizes_root_path
)
extracted_forest_sizes
=
[
nb_tree
for
nb_tree
in
extracted_forest_sizes
if
not
'no_weights'
in
nb_tree
]
extracted_forest_sizes
.
sort
(
key
=
int
)
all_extracted_forest_sizes
.
append
(
list
(
map
(
int
,
extracted_forest_sizes
)))
for
extracted_forest_size
in
extracted_forest_sizes
:
# models/{experiment_id}/seeds/{seed}/extracted_forest_sizes/{extracted_forest_size}
extracted_forest_size_path
=
extracted_forest_sizes_root_path
+
os
.
sep
+
extracted_forest_size
# Load models/{experiment_id}/seeds/{seed}/extracted_forest_sizes/{extracted_forest_size}/model_raw_results.pickle file
model_raw_results
=
ModelRawResults
.
load
(
extracted_forest_size_path
)
# Save the weights
experiment_weights
[
seed
].
append
(
model_raw_results
.
model_weights
)
return
experiment_weights
if
__name__
==
"__main__"
:
# get environment variables in .env
load_dotenv
(
find_dotenv
(
'.env'
))
...
...
@@ -400,6 +427,10 @@ if __name__ == "__main__":
xlabel
=
'Number of trees extracted'
,
ylabel
=
experiments_score_metric
,
title
=
'Loss values of {}
\n
using best params of previous stages'
.
format
(
args
.
dataset_name
))
experiment_weights
=
extract_weights_across_seeds
(
args
.
models_dir
,
args
.
results_dir
,
args
.
experiment_ids
[
2
])
Plotter
.
weight_density
(
experiment_weights
,
os
.
path
.
join
(
output_path
,
'weight_density.png'
))
elif
args
.
stage
==
5
:
# Retreive the extracted forest sizes number used in order to have a base forest axis as long as necessary
extracted_forest_sizes_number
=
retreive_extracted_forest_sizes_number
(
args
.
models_dir
,
args
.
experiment_ids
[
1
])
...
...
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