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Refine TT workflow

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This commit is contained in:
D-X-Y
2021-03-06 06:38:34 -08:00
parent 511e2443d0
commit 349d9fcc9f
3 changed files with 135 additions and 88 deletions
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47
exps/trading/workflow_tt.py
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@@ -4,7 +4,7 @@
# Refer to:
# - https://github.com/microsoft/qlib/blob/main/examples/workflow_by_code.ipynb
# - https://github.com/microsoft/qlib/blob/main/examples/workflow_by_code.py
# python exps/trading/workflow_tt.py --market all
# python exps/trading/workflow_tt.py --market all --gpu 1
#####################################################
import sys, argparse
from pathlib import Path
@@ -13,6 +13,10 @@ lib_dir = (Path(__file__).parent / ".." / ".." / "lib").resolve()
if str(lib_dir) not in sys.path:
sys.path.insert(0, str(lib_dir))
from procedures.q_exps import update_gpu
from procedures.q_exps import update_market
from procedures.q_exps import run_exp
import qlib
from qlib.config import C
from qlib.config import REG_CN
@@ -100,44 +104,23 @@ def main(xargs):
},
]
task = dict(model=model_config, dataset=dataset_config, record=record_config)
provider_uri = "~/.qlib/qlib_data/cn_data"
qlib.init(provider_uri=provider_uri, region=REG_CN)
# start exp to train model
with R.start(experiment_name="tt_model", uri=xargs.save_dir + "-" + xargs.market):
set_log_basic_config(R.get_recorder().root_uri / "log.log")
model = init_instance_by_config(model_config)
dataset = init_instance_by_config(dataset_config)
R.log_params(**flatten_dict(task))
model.fit(dataset)
R.save_objects(trained_model=model)
# prediction
recorder = R.get_recorder()
print(recorder)
for record in task["record"]:
record = record.copy()
if record["class"] == "SignalRecord":
srconf = {"model": model, "dataset": dataset, "recorder": recorder}
record["kwargs"].update(srconf)
sr = init_instance_by_config(record)
sr.generate()
else:
rconf = {"recorder": recorder}
record["kwargs"].update(rconf)
ar = init_instance_by_config(record)
ar.generate()
dataset = init_instance_by_config(dataset_config)
for irun in range(xargs.times):
xmodel_config = model_config.copy()
xmodel_config = update_gpu(xmodel_config, xags.gpu)
task = dict(model=xmodel_config, dataset=dataset_config, record=record_config)
run_exp(task_config, dataset, "Transformer", "recorder-{:02d}-{:02d}".format(irun, xargs.times), xargs.save_dir)
if __name__ == "__main__":
parser = argparse.ArgumentParser("Vanilla Transformable Transformer")
parser.add_argument("--save_dir", type=str, default="./outputs/tt-ml-runs", help="The checkpoint directory.")
parser.add_argument("--times", type=int, default=10, help="The repeated run times.")
parser.add_argument("--gpu", type=int, default=0, help="The GPU ID used for train / test.")
parser.add_argument("--market", type=str, default="csi300", help="The market indicator.")
args = parser.parse_args()
provider_uri = "~/.qlib/qlib_data/cn_data"
qlib.init(provider_uri=provider_uri, region=REG_CN)
main(args)