From cb400cc6bb846326a030e083936bc9854f62b54b Mon Sep 17 00:00:00 2001
From: Charly LAMOTHE <lamothe.c@intlocal.univ-amu.fr>
Date: Sun, 3 Nov 2019 13:40:36 +0100
Subject: [PATCH] - Finish training part (TODO: normalization implementation) -
Add error handling module (TODO: add logging over the code) - Record dataset
parameters and model parameters - Begin compute_results, plotter and
visualize files
---
bolsonaro/__init__.py | 3 +
bolsonaro/data/dataset_loader.py | 5 +-
bolsonaro/data/dataset_parameters.py | 16 ++++
bolsonaro/error_handling/__init__.py | 29 +++++++
bolsonaro/error_handling/color_print.py | 61 ++++++++++++++
bolsonaro/error_handling/console_logger.py | 81 +++++++++++++++++++
.../error_handling/exception_decorators.py | 55 +++++++++++++
bolsonaro/error_handling/logger_factory.py | 66 +++++++++++++++
bolsonaro/models/model_factory.py | 8 +-
bolsonaro/models/model_parameters.py | 32 ++++++++
bolsonaro/models/omp_forest_regressor.py | 19 +++--
bolsonaro/trainer.py | 38 +++++----
bolsonaro/utils.py | 10 +++
bolsonaro/visualization/plotter.py | 26 +++++-
compute_results.py | 21 +++++
train.py | 66 ++++++++++-----
visualize.py | 8 ++
17 files changed, 490 insertions(+), 54 deletions(-)
create mode 100644 bolsonaro/error_handling/__init__.py
create mode 100644 bolsonaro/error_handling/color_print.py
create mode 100644 bolsonaro/error_handling/console_logger.py
create mode 100644 bolsonaro/error_handling/exception_decorators.py
create mode 100644 bolsonaro/error_handling/logger_factory.py
create mode 100644 bolsonaro/models/model_parameters.py
create mode 100644 compute_results.py
diff --git a/bolsonaro/__init__.py b/bolsonaro/__init__.py
index e69de29..ce8e424 100644
--- a/bolsonaro/__init__.py
+++ b/bolsonaro/__init__.py
@@ -0,0 +1,3 @@
+import os
+
+LOG_PATH = os.path.abspath(os.path.dirname(__file__) + os.sep + '..' + os.sep + '..' + os.sep + 'log')
diff --git a/bolsonaro/data/dataset_loader.py b/bolsonaro/data/dataset_loader.py
index 1e4264e..c510a90 100644
--- a/bolsonaro/data/dataset_loader.py
+++ b/bolsonaro/data/dataset_loader.py
@@ -66,11 +66,12 @@ class DatasetLoader(object):
X, y = dataset_loading_func(return_X_y=True)
X_train, X_test, y_train, y_test = train_test_split(X, y,
test_size=dataset_parameters.test_size,
- random_state=dataset_parameters.seed)
+ random_state=dataset_parameters.random_state)
X_train, X_dev, y_train, y_dev = train_test_split(X_train, y_train,
test_size=dataset_parameters.dev_size,
- random_state=dataset_parameters.seed)
+ random_state=dataset_parameters.random_state)
+ # TODO
if dataset_parameters.normalize:
pass
diff --git a/bolsonaro/data/dataset_parameters.py b/bolsonaro/data/dataset_parameters.py
index e820b8f..556c960 100644
--- a/bolsonaro/data/dataset_parameters.py
+++ b/bolsonaro/data/dataset_parameters.py
@@ -1,3 +1,7 @@
+import json
+import os
+
+
class DatasetParameters(object):
def __init__(self, name, test_size, dev_size, random_state, normalize):
@@ -26,3 +30,15 @@ class DatasetParameters(object):
@property
def normalize(self):
return self._normalize
+
+ def save(self, directory_path, experiment_id):
+ with open(directory_path + os.sep + 'dataset_parameters_{}.json'.format(experiment_id), 'w') as output_file:
+ json.dump({
+ 'name': self._name,
+ 'test_size': self._test_size,
+ 'dev_size': self._dev_size,
+ 'random_state': self._random_state,
+ 'normalize': self._normalize
+ },
+ output_file,
+ indent=4)
diff --git a/bolsonaro/error_handling/__init__.py b/bolsonaro/error_handling/__init__.py
new file mode 100644
index 0000000..a8ca18d
--- /dev/null
+++ b/bolsonaro/error_handling/__init__.py
@@ -0,0 +1,29 @@
+ #####################################################################################
+ # MIT License #
+ # #
+ # Copyright (C) 2019 Charly Lamothe #
+ # #
+ # This file is part of VQ-VAE-Speech. #
+ # #
+ # Permission is hereby granted, free of charge, to any person obtaining a copy #
+ # of this software and associated documentation files (the "Software"), to deal #
+ # in the Software without restriction, including without limitation the rights #
+ # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell #
+ # copies of the Software, and to permit persons to whom the Software is #
+ # furnished to do so, subject to the following conditions: #
+ # #
+ # The above copyright notice and this permission notice shall be included in all #
+ # copies or substantial portions of the Software. #
+ # #
+ # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR #
+ # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, #
+ # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE #
+ # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER #
+ # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, #
+ # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE #
+ # SOFTWARE. #
+ #####################################################################################
+
+import os
+
+LOG_PATH = os.path.abspath(os.path.dirname(__file__) + os.sep + '..' + os.sep + '..' + os.sep + 'log')
diff --git a/bolsonaro/error_handling/color_print.py b/bolsonaro/error_handling/color_print.py
new file mode 100644
index 0000000..b577e5a
--- /dev/null
+++ b/bolsonaro/error_handling/color_print.py
@@ -0,0 +1,61 @@
+ #####################################################################################
+ # MIT License #
+ # #
+ # Copyright (C) 2019 Charly Lamothe #
+ # #
+ # This file is part of VQ-VAE-Speech. #
+ # #
+ # Permission is hereby granted, free of charge, to any person obtaining a copy #
+ # of this software and associated documentation files (the "Software"), to deal #
+ # in the Software without restriction, including without limitation the rights #
+ # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell #
+ # copies of the Software, and to permit persons to whom the Software is #
+ # furnished to do so, subject to the following conditions: #
+ # #
+ # The above copyright notice and this permission notice shall be included in all #
+ # copies or substantial portions of the Software. #
+ # #
+ # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR #
+ # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, #
+ # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE #
+ # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER #
+ # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, #
+ # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE #
+ # SOFTWARE. #
+ #####################################################################################
+
+import sys
+
+
+class ColorPrint(object):
+ """ Colored printing functions for strings that use universal ANSI escape sequences.
+
+ fail: bold red, pass: bold green, warn: bold yellow,
+ info: bold blue, bold: bold white
+
+ :source: https://stackoverflow.com/a/47622205
+ """
+
+ @staticmethod
+ def print_fail(message, end='\n'):
+ sys.stderr.write('\x1b[1;31m' + message.strip() + '\x1b[0m' + end)
+
+ @staticmethod
+ def print_pass(message, end='\n'):
+ sys.stdout.write('\x1b[1;32m' + message.strip() + '\x1b[0m' + end)
+
+ @staticmethod
+ def print_warn(message, end='\n'):
+ sys.stderr.write('\x1b[1;33m' + message.strip() + '\x1b[0m' + end)
+
+ @staticmethod
+ def print_info(message, end='\n'):
+ sys.stdout.write('\x1b[1;34m' + message.strip() + '\x1b[0m' + end)
+
+ @staticmethod
+ def print_major_fail(message, end='\n'):
+ sys.stdout.write('\x1b[1;35m' + message.strip() + '\x1b[0m' + end)
+
+ @staticmethod
+ def print_bold(message, end='\n'):
+ sys.stdout.write('\x1b[1;37m' + message.strip() + '\x1b[0m' + end)
diff --git a/bolsonaro/error_handling/console_logger.py b/bolsonaro/error_handling/console_logger.py
new file mode 100644
index 0000000..7014b4c
--- /dev/null
+++ b/bolsonaro/error_handling/console_logger.py
@@ -0,0 +1,81 @@
+ #####################################################################################
+ # MIT License #
+ # #
+ # Copyright (C) 2019 Charly Lamothe #
+ # #
+ # This file is part of VQ-VAE-Speech. #
+ # #
+ # Permission is hereby granted, free of charge, to any person obtaining a copy #
+ # of this software and associated documentation files (the "Software"), to deal #
+ # in the Software without restriction, including without limitation the rights #
+ # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell #
+ # copies of the Software, and to permit persons to whom the Software is #
+ # furnished to do so, subject to the following conditions: #
+ # #
+ # The above copyright notice and this permission notice shall be included in all #
+ # copies or substantial portions of the Software. #
+ # #
+ # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR #
+ # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, #
+ # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE #
+ # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER #
+ # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, #
+ # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE #
+ # SOFTWARE. #
+ #####################################################################################
+
+from error_handling.color_print import ColorPrint
+
+import sys
+import traceback
+import os
+
+
+class ConsoleLogger(object):
+
+ @staticmethod
+ def status(message):
+ if os.name == 'nt':
+ print('[~] {message}'.format(message=message))
+ else:
+ ColorPrint.print_info('[~] {message}'.format(message=message))
+
+ @staticmethod
+ def success(message):
+ if os.name == 'nt':
+ print('[+] {message}'.format(message=message))
+ else:
+ ColorPrint.print_pass('[+] {message}'.format(message=message))
+
+ @staticmethod
+ def error(message):
+ if sys.exc_info()[2]:
+ line = traceback.extract_tb(sys.exc_info()[2])[-1].lineno
+ error_message = '[-] {message} with cause: {cause} (line {line})'.format( \
+ message=message, cause=str(sys.exc_info()[1]), line=line)
+ else:
+ error_message = '[-] {message}'.format(message=message)
+ if os.name == 'nt':
+ print(error_message)
+ else:
+ ColorPrint.print_fail(error_message)
+
+ @staticmethod
+ def warn(message):
+ if os.name == 'nt':
+ print('[-] {message}'.format(message=message))
+ else:
+ ColorPrint.print_warn('[-] {message}'.format(message=message))
+
+ @staticmethod
+ def critical(message):
+ if sys.exc_info()[2]:
+ line = traceback.extract_tb(sys.exc_info()[2])[-1].lineno
+ error_message = '[!] {message} with cause: {cause} (line {line})'.format( \
+ message=message, cause=str(sys.exc_info()[1]), line=line)
+ else:
+ error_message = '[!] {message}'.format(message=message)
+ if os.name == 'nt':
+ print(error_message)
+ else:
+ ColorPrint.print_major_fail(error_message)
diff --git a/bolsonaro/error_handling/exception_decorators.py b/bolsonaro/error_handling/exception_decorators.py
new file mode 100644
index 0000000..428c618
--- /dev/null
+++ b/bolsonaro/error_handling/exception_decorators.py
@@ -0,0 +1,55 @@
+ #####################################################################################
+ # MIT License #
+ # #
+ # Copyright (C) 2019 Charly Lamothe #
+ # #
+ # This file is part of VQ-VAE-Speech. #
+ # #
+ # Permission is hereby granted, free of charge, to any person obtaining a copy #
+ # of this software and associated documentation files (the "Software"), to deal #
+ # in the Software without restriction, including without limitation the rights #
+ # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell #
+ # copies of the Software, and to permit persons to whom the Software is #
+ # furnished to do so, subject to the following conditions: #
+ # #
+ # The above copyright notice and this permission notice shall be included in all #
+ # copies or substantial portions of the Software. #
+ # #
+ # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR #
+ # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, #
+ # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE #
+ # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER #
+ # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, #
+ # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE #
+ # SOFTWARE. #
+ #####################################################################################
+
+from functools import wraps
+
+
+class InvalidRaiseException(Exception):
+ pass
+
+
+def only_throws(E):
+ """
+ :source: https://stackoverflow.com/a/18289516
+ """
+
+ def decorator(f):
+ @wraps(f)
+ def wrapped(*args, **kwargs):
+ try:
+ return f(*args, **kwargs)
+ except E:
+ raise
+ except InvalidRaiseException:
+ raise
+ except Exception as e:
+ raise InvalidRaiseException(
+ 'got %s, expected %s, from %s' % (e.__class__.__name__, E.__name__, f.__name__)
+ )
+
+ return wrapped
+
+ return decorator
diff --git a/bolsonaro/error_handling/logger_factory.py b/bolsonaro/error_handling/logger_factory.py
new file mode 100644
index 0000000..f524851
--- /dev/null
+++ b/bolsonaro/error_handling/logger_factory.py
@@ -0,0 +1,66 @@
+ #####################################################################################
+ # MIT License #
+ # #
+ # Copyright (C) 2019 Charly Lamothe #
+ # #
+ # This file is part of VQ-VAE-Speech. #
+ # #
+ # Permission is hereby granted, free of charge, to any person obtaining a copy #
+ # of this software and associated documentation files (the "Software"), to deal #
+ # in the Software without restriction, including without limitation the rights #
+ # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell #
+ # copies of the Software, and to permit persons to whom the Software is #
+ # furnished to do so, subject to the following conditions: #
+ # #
+ # The above copyright notice and this permission notice shall be included in all #
+ # copies or substantial portions of the Software. #
+ # #
+ # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR #
+ # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, #
+ # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE #
+ # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER #
+ # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, #
+ # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE #
+ # SOFTWARE. #
+ #####################################################################################
+
+import logging
+from logging.handlers import RotatingFileHandler
+import os
+import errno
+
+
+class LoggerFactory(object):
+
+ @staticmethod
+ def create(path, module_name):
+ # Create logger
+ logger = logging.getLogger(module_name)
+ logger.setLevel(logging.DEBUG)
+
+ try:
+ os.makedirs(path)
+ except OSError as e:
+ if e.errno != errno.EEXIST:
+ raise
+
+ # Create file handler
+ fh = RotatingFileHandler(path + os.sep + module_name + '.log', maxBytes=1000000, backupCount=5)
+ fh.setLevel(logging.DEBUG)
+
+ # Create console handler
+ ch = logging.StreamHandler()
+ ch.setLevel(logging.DEBUG)
+
+ # Create formatter
+ formatter = logging.Formatter('%(asctime)s - %(filename)s:%(lineno)s - %(name)s - %(levelname)s - %(message)s')
+
+ # Add formatter to handlers
+ fh.setFormatter(formatter)
+ ch.setFormatter(formatter) # TODO: add another formatter to the console logger?
+
+ # Add fh and ch to logger
+ logger.addHandler(fh)
+ logger.addHandler(ch)
+
+ return logger
diff --git a/bolsonaro/models/model_factory.py b/bolsonaro/models/model_factory.py
index a2f02a6..5bad7f4 100644
--- a/bolsonaro/models/model_factory.py
+++ b/bolsonaro/models/model_factory.py
@@ -6,15 +6,11 @@ from bolsonaro.data.task import Task
class ModelFactory(object):
@staticmethod
- def build(task, forest_size, extracted_forest_size, seed=None):
+ def build(task, model_parameters):
if task == Task.CLASSIFICATION:
model_func = OmpForestClassifier
elif task == Task.REGRESSION:
model_func = OmpForestRegressor
else:
raise ValueError("Unsupported task '{}'".format(task))
- return model_func(
- forest_size=forest_size,
- extracted_forest_size=extracted_forest_size,
- seed=seed
- )
+ return model_func(model_parameters)
diff --git a/bolsonaro/models/model_parameters.py b/bolsonaro/models/model_parameters.py
new file mode 100644
index 0000000..b1fec8c
--- /dev/null
+++ b/bolsonaro/models/model_parameters.py
@@ -0,0 +1,32 @@
+import json
+import os
+
+
+class ModelParameters(object):
+
+ def __init__(self, forest_size, extracted_forest_size, seed=None):
+ self._forest_size = forest_size
+ self._extracted_forest_size = extracted_forest_size
+ self._seed = seed
+
+ @property
+ def forest_size(self):
+ return self._forest_size
+
+ @property
+ def extracted_forest_size(self):
+ return self._extracted_forest_size
+
+ @property
+ def seed(self):
+ return self._seed
+
+ def save(self, directory_path, experiment_id):
+ with open(directory_path + os.sep + 'model_parameters_{}.json'.format(experiment_id), 'w') as output_file:
+ json.dump({
+ 'forest_size': self._forest_size,
+ 'extracted_forest_size': self._extracted_forest_size,
+ 'seed': self._seed
+ },
+ output_file,
+ indent=4)
diff --git a/bolsonaro/models/omp_forest_regressor.py b/bolsonaro/models/omp_forest_regressor.py
index 17d99aa..be60cae 100644
--- a/bolsonaro/models/omp_forest_regressor.py
+++ b/bolsonaro/models/omp_forest_regressor.py
@@ -1,14 +1,14 @@
-from sklearn.base import BaseEstimator
from sklearn.ensemble import RandomForestRegressor
from sklearn.linear_model import OrthogonalMatchingPursuit
+from sklearn.base import BaseEstimator
class OmpForestRegressor(BaseEstimator):
- def __init__(self, forest_size, extracted_forest_size, seed=None):
- self._regressor = RandomForestRegressor(n_estimators=forest_size,
- random_state=seed)
- self._extracted_forest_size = extracted_forest_size
+ def __init__(self, models_parameters):
+ self._regressor = RandomForestRegressor(n_estimators=models_parameters.forest_size,
+ random_state=models_parameters.seed)
+ self._models_parameters = models_parameters
def fit(self, X_train, y_train):
self._forest = self._train_forest(X_train, y_train)
@@ -25,14 +25,19 @@ class OmpForestRegressor(BaseEstimator):
def weights(self):
return self._weights
+ @property
+ def models_parameters(self):
+ return self._models_parameters
+
def _train_forest(self, X_train, y_train):
self._regressor.fit(X_train, y_train)
forest = self._regressor.estimators_
return forest
def _extract_subforest(self, X_train, y_train):
- D = [[tree.predict([elem])[0] for tree in forest] for elem in X_train]
- omp = OrthogonalMatchingPursuit(n_nonzero_coefs=self._extracted_forest_size,
+ D = [[tree.predict([elem])[0] for tree in self._forest] for elem in X_train]
+ omp = OrthogonalMatchingPursuit(
+ n_nonzero_coefs=self._models_parameters.extracted_forest_size,
fit_intercept=False, normalize=False)
omp.fit(D, y_train)
weights = omp.coef_
diff --git a/bolsonaro/trainer.py b/bolsonaro/trainer.py
index cb9f9fe..7c1436b 100644
--- a/bolsonaro/trainer.py
+++ b/bolsonaro/trainer.py
@@ -1,26 +1,30 @@
-from bolsonaro.utils import resolve_output_file_name
+from bolsonaro.error_handling.logger_factory import LoggerFactory
+from . import LOG_PATH
import pickle
+import os
+import time
+import datetime
class Trainer(object):
- def __init__(self, dataset, model, results_dir, models_dir):
+ def __init__(self, dataset):
self._dataset = dataset
- self._model = model
- self._results_dir = results_dir
- self._models_dir = models_dir
+ self._logger = LoggerFactory.create(LOG_PATH, __name__)
- def process(self):
- self._model.fit(self._dataset.X_train, self._dataset.y_train)
- output_file_name = resolve_output_file_name(
- self._dataset.dataset_parameters,
- self._model.model_parameters,
- self._results_dir,
- self._models_dir
- )
- with open(output_file_name, 'wb') as output_file:
- pickle.dump(output_file, {
+ def iterate(self, model, models_dir):
+ self._logger.info('Training model using train set...')
+ begin_time = time.time()
+ model.fit(self._dataset.X_train, self._dataset.y_train)
+ end_time = time.time()
- })
- # save forest and weights here
+ output_file_path = models_dir + os.sep + 'model.pickle'
+ self._logger.info('Saving trained model to {}'.format(output_file_path))
+ with open(output_file_path, 'wb') as output_file:
+ pickle.dump({
+ 'forest': model.forest,
+ 'weights': model.weights,
+ 'training_time': end_time - begin_time,
+ 'datetime': datetime.datetime.now()
+ }, output_file)
diff --git a/bolsonaro/utils.py b/bolsonaro/utils.py
index e69de29..2affd37 100644
--- a/bolsonaro/utils.py
+++ b/bolsonaro/utils.py
@@ -0,0 +1,10 @@
+import os
+
+
+def resolve_experiment_id(models_dir):
+ ids = [x for x in os.listdir(models_dir)
+ if os.path.isdir(models_dir + os.sep + x)]
+ if len(ids) > 0:
+ ids.sort(key=int)
+ return int(max(ids)) + 1
+ return 1
diff --git a/bolsonaro/visualization/plotter.py b/bolsonaro/visualization/plotter.py
index 01f0f03..c119d47 100644
--- a/bolsonaro/visualization/plotter.py
+++ b/bolsonaro/visualization/plotter.py
@@ -1,3 +1,27 @@
+import matplotlib.pyplot as plt
+import numpy as np
+from sklearn.neighbors.kde import KernelDensity
+
+
class Plotter(object):
-
\ No newline at end of file
+ @staticmethod
+ def weight_density(weights):
+ """
+ TODO: to complete
+ """
+ X_plot = [np.exp(elem) for elem in weights]
+ fig, ax = plt.subplots()
+
+ for kernel in ['gaussian', 'tophat', 'epanechnikov']:
+ kde = KernelDensity(kernel=kernel, bandwidth=0.5).fit(X_plot)
+ log_dens = kde.score_samples(X_plot)
+ ax.plot(X_plot[:, 0], np.exp(log_dens), '-',
+ label="kernel = '{0}'".format(kernel))
+
+ ax.legend(loc='upper left')
+ ax.plot(X[:, 0], -0.005 - 0.01 * np.random.random(X.shape[0]), '+k')
+
+ ax.set_xlim(-4, 9)
+ ax.set_ylim(-0.02, 0.4)
+ plt.show()
diff --git a/compute_results.py b/compute_results.py
new file mode 100644
index 0000000..ba80f0b
--- /dev/null
+++ b/compute_results.py
@@ -0,0 +1,21 @@
+import argparse
+import pathlib
+
+
+if __name__ == "__main__":
+ default_results_dir = 'results'
+ default_models_dir = 'models'
+ default_experiment_id = -1
+
+ parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+ parser.add_argument('--results_dir', nargs='?', type=str, default=default_results_dir, help='The output directory of the results.')
+ parser.add_argument('--models_dir', nargs='?', type=str, default=default_models_dir, help='The output directory of the trained models.')
+ parser.add_argument('--experiment_id', nargs='?', type=int, default=default_experiment_id, help='Compute the results of a single experiment id')
+ args = parser.parse_args()
+
+ pathlib.Path(args.results_dir).mkdir(parents=True, exist_ok=True)
+
+ if args.experiment_id == -1:
+ pass
+ else:
+ pass
diff --git a/train.py b/train.py
index cd6f228..0e6896c 100644
--- a/train.py
+++ b/train.py
@@ -1,11 +1,15 @@
from bolsonaro.data.dataset_parameters import DatasetParameters
from bolsonaro.data.dataset_loader import DatasetLoader
from bolsonaro.models.model_factory import ModelFactory
+from bolsonaro.models.model_parameters import ModelParameters
from bolsonaro.trainer import Trainer
+from bolsonaro.utils import resolve_experiment_id
import argparse
import pathlib
import random
+import os
+import errno
if __name__ == "__main__":
@@ -13,7 +17,6 @@ if __name__ == "__main__":
default_normalize = False
default_forest_size = 100
default_extracted_forest_size = 10
- default_results_dir = 'results'
default_models_dir = 'models'
default_dev_size = 0.2
default_test_size = 0.2
@@ -27,7 +30,6 @@ if __name__ == "__main__":
parser.add_argument('--normalize', action='store_true', default=default_normalize, help='Normalize the data by doing the L2 division of the pred vectors.')
parser.add_argument('--forest_size', nargs='?', type=int, default=default_forest_size, help='The number of trees of the random forest.')
parser.add_argument('--extracted_forest_size', nargs='+', type=int, default=default_extracted_forest_size, help='The number of trees selected by OMP.')
- parser.add_argument('--results_dir', nargs='?', type=str, default=default_results_dir, help='The output directory of the results.')
parser.add_argument('--models_dir', nargs='?', type=str, default=default_models_dir, help='The output directory of the trained models.')
parser.add_argument('--dev_size', nargs='?', type=float, default=default_dev_size, help='Dev subset ratio')
parser.add_argument('--test_size', nargs='?', type=float, default=default_test_size, help='Test subset ratio')
@@ -35,35 +37,57 @@ if __name__ == "__main__":
parser.add_argument('--random_seed_number', nargs='?', type=int, default=default_random_seed_number, help='Number of random seeds used')
args = parser.parse_args()
- pathlib.Path(args.results_dir).mkdir(parents=True, exist_ok=True)
pathlib.Path(args.models_dir).mkdir(parents=True, exist_ok=True)
- random_seeds = [random.randint(begin_random_seed_range, end_random_seed_range) for i in range(args.random_seed_number)] \
+ args.extracted_forest_size = args.extracted_forest_size \
+ if type(args.extracted_forest_size) == list \
+ else [args.extracted_forest_size]
+
+ random_seeds = [random.randint(begin_random_seed_range, end_random_seed_range) \
+ for i in range(args.random_seed_number)] \
if args.use_random_seed else None
+ experiment_id = resolve_experiment_id(args.models_dir)
+ experiment_id_str = str(experiment_id)
+
for random_seed in random_seeds:
- dataset = DatasetLoader.load_from_name(
- DatasetParameters(
- name=args.dataset_name,
- test_size=args.test_size,
- dev_size=args.dev_size,
- random_state=random_seed,
- normalize=args.normalize
- )
+ random_seed_str = str(random_seed)
+ models_dir = args.models_dir + os.sep + experiment_id_str + os.sep + 'seeds' + \
+ os.sep + random_seed_str
+ try:
+ os.makedirs(models_dir)
+ except OSError as e:
+ if e.errno != errno.EEXIST:
+ raise
+
+ dataset_parameters = DatasetParameters(
+ name=args.dataset_name,
+ test_size=args.test_size,
+ dev_size=args.dev_size,
+ random_state=random_seed,
+ normalize=args.normalize
)
+ dataset_parameters.save(models_dir, experiment_id_str)
+
+ dataset = DatasetLoader.load_from_name(dataset_parameters)
+
+ trainer = Trainer(dataset)
for extracted_forest_size in args.extracted_forest_size:
- model = ModelFactory(
- task=dataset.task,
+ sub_models_dir = models_dir + os.sep + 'extracted_forest_size' + os.sep + str(extracted_forest_size)
+ try:
+ os.makedirs(sub_models_dir)
+ except OSError as e:
+ if e.errno != errno.EEXIST:
+ raise
+
+ model_parameters = ModelParameters(
forest_size=args.forest_size,
extracted_forest_size=extracted_forest_size,
seed=random_seed
)
+ model_parameters.save(sub_models_dir, experiment_id)
- trainer = Trainer(
- dataset=dataset,
- model=model,
- results_dir=args.results_dir,
- models_dir=args.models_dir
- )
- trainer.process()
+ model = ModelFactory.build(dataset.task, model_parameters)
+
+ trainer.iterate(model, sub_models_dir)
diff --git a/visualize.py b/visualize.py
index e69de29..6ae9da1 100644
--- a/visualize.py
+++ b/visualize.py
@@ -0,0 +1,8 @@
+import argparse
+
+
+if __name__ == "__main__":
+ parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+ parser.add_argument('--weight_density', action='store_true', default=default_use_weright_density, help='')
+ args = parser.parse_args()
+
--
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