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be4646b4b7
* Intermediate version * Fix yaml template & Successfully run rolling * Be compatible with benchmark * Get same results with previous linear model * Black formatting * Update black * Update the placeholder mechanism * Update CI * Update CI * Upgrade Black * Fix CI and simplify code * Fix CI * Move the data processing caching mechanism into utils. * Adjusting DDG-DA * Organize import
95 lines
3.3 KiB
Python
95 lines
3.3 KiB
Python
# coding=utf-8
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# Copyright 2020 The Google Research Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Lint as: python3
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"""Default configs for TFT experiments.
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Contains the default output paths for data, serialised models and predictions
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for the main experiments used in the publication.
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"""
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import os
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import data_formatters.qlib_Alpha158
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class ExperimentConfig:
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"""Defines experiment configs and paths to outputs.
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Attributes:
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root_folder: Root folder to contain all experimental outputs.
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experiment: Name of experiment to run.
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data_folder: Folder to store data for experiment.
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model_folder: Folder to store serialised models.
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results_folder: Folder to store results.
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data_csv_path: Path to primary data csv file used in experiment.
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hyperparam_iterations: Default number of random search iterations for
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experiment.
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"""
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default_experiments = ["Alpha158"]
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def __init__(self, experiment="volatility", root_folder=None):
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"""Creates configs based on default experiment chosen.
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Args:
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experiment: Name of experiment.
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root_folder: Root folder to save all outputs of training.
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"""
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if experiment not in self.default_experiments:
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raise ValueError("Unrecognised experiment={}".format(experiment))
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# Defines all relevant paths
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if root_folder is None:
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root_folder = os.path.join(os.path.dirname(os.path.realpath(__file__)), "..", "outputs")
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print("Using root folder {}".format(root_folder))
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self.root_folder = root_folder
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self.experiment = experiment
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self.data_folder = os.path.join(root_folder, "data", experiment)
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self.model_folder = os.path.join(root_folder, "saved_models", experiment)
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self.results_folder = os.path.join(root_folder, "results", experiment)
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# Creates folders if they don't exist
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for relevant_directory in [self.root_folder, self.data_folder, self.model_folder, self.results_folder]:
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if not os.path.exists(relevant_directory):
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os.makedirs(relevant_directory)
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@property
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def data_csv_path(self):
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csv_map = {
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"Alpha158": "Alpha158.csv",
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}
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return os.path.join(self.data_folder, csv_map[self.experiment])
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@property
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def hyperparam_iterations(self):
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return 240 if self.experiment == "volatility" else 60
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def make_data_formatter(self):
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"""Gets a data formatter object for experiment.
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Returns:
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Default DataFormatter per experiment.
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"""
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data_formatter_class = {
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"Alpha158": data_formatters.qlib_Alpha158.Alpha158Formatter,
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}
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return data_formatter_class[self.experiment]()
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