def run_custom_model():
for year in ("2016", "2017"):
cfg = Configuration(random_forest.Model(), load_climbset(year),
CategoricalPreprocessor())
cfg.run()
Configuration.report_headings()
print(cfg.report())
def search():
parameter_args = ParameterSpace().product()
hyper_parameter_combinations = [
Parameters(*args) for args in parameter_args
]
print(f"Generated {len(hyper_parameter_combinations)} sets of parameters")
train_func = partial(train_model, climbset=load_climbset("2016"))
results = list(map(train_func, hyper_parameter_combinations))
pprint(results)
def generate_all_valid_configurations():
configs = []
for year in ("2016", "2017"):
# XGBoost
configs.append(
Configuration(xgboost_model.Model(), load_climbset(year),
FlandersPreprocessor()))
# Random forest flanders proprocessor
configs.append(
Configuration(random_forest.Model(), load_climbset(year),
FlandersPreprocessor()))
# Loop through categorical grade preprocessors
for preprocessor in (
CategoricalPreprocessor(),
SplitPreprocessor(4),
HalfGradePreprocessor(),
):
# LSTM
configs.append(
Configuration(
keras_lstm_grade.Model(),
load_climbset(year),
preprocessor,
HoldListPreprocessor(),
))
# MLP
configs.append(
Configuration(keras_mlp.Model(), load_climbset(year),
preprocessor))
# Random forest
configs.append(
Configuration(random_forest.Model(), load_climbset(year),
preprocessor))
print(f"Generated {len(configs)} configruations.")
return configs
def main(year):
num_climbs = 500
# Load climbset
climbset = load_climbset(year)
# Sample generators
lstm = keras_lstm_gen.Model()
sampling_parameters = params.Parameters()
sample = lstm.sample(climbset, num_climbs, sampling_parameters)
# Save to file
file_data = {"original": climbset, "lstm": sample}
print(f"Saving {len(file_data)} climbsets")
pickle.dump(file_data,
open(local_file_path(__file__, f"{year}.pickle"), "wb"))
def prep_no_grade():
output_path = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"input.txt")
with open(output_path, "w") as handle:
handle.write(load_climbset().no_grade_string())
return output_path