From 0fce03191cd24b47d58d1b264fc3d765c22f7bd0 Mon Sep 17 00:00:00 2001
From: Charly LAMOTHE <lamothe.c@intlocal.univ-amu.fr>
Date: Fri, 8 Nov 2019 10:38:41 +0100
Subject: [PATCH] Add the weights normalization parameter (but not implemented
yet)
---
code/bolsonaro/models/model_parameters.py | 7 ++++++-
code/bolsonaro/models/omp_forest_regressor.py | 3 ++-
code/train.py | 3 +++
3 files changed, 11 insertions(+), 2 deletions(-)
diff --git a/code/bolsonaro/models/model_parameters.py b/code/bolsonaro/models/model_parameters.py
index 768d207..d098196 100644
--- a/code/bolsonaro/models/model_parameters.py
+++ b/code/bolsonaro/models/model_parameters.py
@@ -5,11 +5,12 @@ import os
class ModelParameters(object):
- def __init__(self, forest_size, extracted_forest_size, normalize_D, subsets_used, seed=None):
+ def __init__(self, forest_size, extracted_forest_size, normalize_D, subsets_used, normalize_weights, seed):
self._forest_size = forest_size
self._extracted_forest_size = extracted_forest_size
self._normalize_D = normalize_D
self._subsets_used = subsets_used
+ self._normalize_weights = normalize_weights
self._seed = seed
@property
@@ -28,6 +29,10 @@ class ModelParameters(object):
def subsets_used(self):
return self._subsets_used
+ @property
+ def normalize_weights(self):
+ return self._normalize_weights
+
@property
def seed(self):
return self._seed
diff --git a/code/bolsonaro/models/omp_forest_regressor.py b/code/bolsonaro/models/omp_forest_regressor.py
index 5075424..3e95d12 100644
--- a/code/bolsonaro/models/omp_forest_regressor.py
+++ b/code/bolsonaro/models/omp_forest_regressor.py
@@ -56,7 +56,8 @@ class OmpForestRegressor(BaseEstimator):
if self._models_parameters.normalize_D:
D /= self._forest_norms
- predictions = D @ self.weights
+ # TODO: use self._models_parameters.normalize_weights here
+ predictions = D @ self._weights
return predictions
diff --git a/code/train.py b/code/train.py
index 72abcf6..eca2594 100644
--- a/code/train.py
+++ b/code/train.py
@@ -31,6 +31,7 @@ if __name__ == "__main__":
DEFAULT_RANDOM_SEED_NUMBER = 1
DEFAULT_SUBSETS_USED = 'train,dev'
DEFAULT_DISABLE_PROGRESS = False
+ DEFAULT_normalize_weights = False
begin_random_seed_range = 1
end_random_seed_range = 2000
@@ -48,6 +49,7 @@ if __name__ == "__main__":
parser.add_argument('--seeds', nargs='+', type=int, default=None, help='Specific a list of seeds instead of generate them randomly')
parser.add_argument('--subsets_used', nargs='+', type=str, default=DEFAULT_SUBSETS_USED, help='train,dev: forest on train, OMP on dev. train+dev,train+dev: both forest and OMP on train+dev. train,train+dev: forest on train+dev and OMP on dev.')
parser.add_argument('--disable_progress', action='store_true', default=DEFAULT_DISABLE_PROGRESS, help='Disable the progress bars.')
+ parser.add_argument('--normalize_weights', action='store_true', default=DEFAULT_normalize_weights, help='Divide the predictions by the weights sum.')
args = parser.parse_args()
pathlib.Path(args.models_dir).mkdir(parents=True, exist_ok=True)
@@ -102,6 +104,7 @@ if __name__ == "__main__":
extracted_forest_size=extracted_forest_size,
normalize_D=args.normalize_D,
subsets_used=args.subsets_used,
+ normalize_weights=args.normalize_weights,
seed=seed
)
model_parameters.save(sub_models_dir, experiment_id)
--
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