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Update R related codes

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This commit is contained in:
Jactus
2020-11-13 21:34:13 +08:00
parent 138ab10c1a
commit ea5f14ce12
9 changed files with 704 additions and 131 deletions
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143
qlib/workflow/expm.py
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@@ -18,8 +18,9 @@ class ExpManager:
(The link: https://mlflow.org/docs/latest/python_api/mlflow.html)
"""
def __init__(self):
self.uri = None
def __init__(self, uri, default_exp_name):
self.uri = uri
self.default_exp_name = default_exp_name
self.active_experiment = None # only one experiment can running each time
self.experiments = dict() # store the experiment name --> Experiment object
@@ -39,6 +40,7 @@ class ExpManager:
controls whether run is nested in parent run.
Returns
-------
An active recorder.
"""
raise NotImplementedError(f"Please implement the `start_exp` method.")
@@ -112,7 +114,7 @@ class ExpManager:
"""
raise NotImplementedError(f"Please implement the `get_exp` method.")
def delete_exp(self, experiment_id):
def delete_exp(self, experiment_id=None, experiment_name=None):
"""
Delete an experiment.
@@ -120,41 +122,51 @@ class ExpManager:
----------
experiment_id : str
the experiment id.
experiment_name : str
the experiment name.
"""
raise NotImplementedError(f"Please implement the `create_exp` method.")
raise NotImplementedError(f"Please implement the `delete_exp` method.")
def get_uri(self):
"""
Get the default tracking URI or current URI.
Parameters
----------
Returns
-------
The tracking URI string.
"""
return self.uri
def list_experiments(self):
"""
List all the existing experiments.
Returns
-------
A dictionary (name -> experiment) of experiments information that being stored.
"""
raise NotImplementedError(f"Please implement the `list_experiments` method.")
class MLflowExpManager(ExpManager):
"""
Use mlflow to implement ExpManager.
"""
def __init__(self):
super(MLflowExpManager, self).__init__()
self.uri = None
def __init__(self, uri, default_exp_name):
super(MLflowExpManager, self).__init__(uri, default_exp_name)
self._total_exps = 0
# get all the exps
self.experiments = self.list_experiments()
def start_exp(self, experiment_name=None, uri=None):
# create experiment
experiment = self.create_exp(experiment_name, uri)
# set up active experiment
self.active_experiment = experiment
# store the experiment
self.experiments[experiment_name] = experiment
# start the experiment
self.active_experiment.start()
self._total_exps += 1 # update exp num
return self.active_experiment
@@ -162,10 +174,9 @@ class MLflowExpManager(ExpManager):
if self.active_experiment is not None:
self.active_experiment.end(status)
self.active_experiment = None
self._total_exps -= 1
def create_exp(self, experiment_name=None, uri=None):
# init experiment
experiment = MLflowExperiment()
# set the tracking uri
if uri is None:
logger.info(
@@ -176,15 +187,19 @@ class MLflowExpManager(ExpManager):
mlflow.set_tracking_uri(self.uri)
# start the experiment
if experiment_name is None:
logger.info("No experiment name provided. The default experiment name is set as `experiment`.")
experiment_id = mlflow.create_experiment("experiment")
logger.info(
f"No experiment name provided. The default experiment name is set as `{self.default_exp_name}`."
)
experiment_id = mlflow.create_experiment(self.default_exp_name)
# set the active experiment
mlflow.set_experiment("experiment")
experiment_name = "experiment"
mlflow.set_experiment(self.default_exp_name)
experiment_name = self.default_exp_name
else:
if experiment_name not in self.experiments:
if mlflow.get_experiment_by_name(experiment_name) is not None:
logger.info("The experiment has already been created before. Try to resume the experiment...")
logger.info(
"The experiment has already been created before. Try to resume the experiment with a new recorder..."
)
experiment_id = mlflow.get_experiment_by_name(experiment_name).experiment_id
else:
experiment_id = mlflow.create_experiment(experiment_name)
@@ -193,9 +208,11 @@ class MLflowExpManager(ExpManager):
experiment = self.experiments[experiment_name]
# set the active experiment
mlflow.set_experiment(experiment_name)
# set up experiment
experiment.id = experiment_id
experiment.name = experiment_name
# init experiment
experiment = MLflowExperiment(experiment_id, experiment_name, self.uri)
experiment._default_name = self.default_exp_name
# store the experiment
self.experiments[experiment_name] = experiment
return experiment
@@ -206,19 +223,73 @@ class MLflowExpManager(ExpManager):
order_by = kwargs.get("order_by")
return mlflow.search_runs(experiment_ids, filter_string, run_view_type, max_results, order_by)
def get_exp(self, experiment_id=None, experiment_name=None):
if experiment_name is not None:
return self.experiments[experiment_name]
elif experiment_id is not None:
for name in self.experiments:
if self.experiments[name].id == experiment_id:
return self.experiments[name]
elif self.active_experiment is None:
raise Exception("No valid active experiment exists. Please make sure experiment manager is running.")
def get_exp(self, experiment_id=None, experiment_name=None, create=True):
if experiment_id is None and experiment_name is None:
if self.active_experiment:
return self.active_experiment
else:
if create:
logger.warning("QlibRecorder is not running. Use the Default experiment for further process.")
return self.start_exp()
else:
raise Exception(
"Something went wrong when retrieving experiments. Please check if QlibRecorder is running or the name/id of the experiment is correct."
)
else:
logger.info("No experiment id or name is given. Return the current active experiment.")
return self.active_experiment
if experiment_name is not None:
if experiment_name in self.experiments:
return self.experiments[experiment_name]
else:
if create:
logger.warning(
f"No valid experiment found. Create experiment with name {experiment_name} for further process."
)
return self.start_exp(experiment_name)
else:
raise Exception(
"Something went wrong when retrieving experiments. Please check if QlibRecorder is running or the name/id of the experiment is correct."
)
else:
for name in self.experiments:
if self.experiments[name].id == experiment_id:
return self.experiments[name]
if create:
logger.warning(f"No valid experiment found. Use the Default experiment for further process.")
return self.start_exp()
else:
raise Exception(
"Something went wrong when retrieving experiments. Please check if QlibRecorder is running or the name/id of the experiment is correct."
)
def delete_exp(self, experiment_id):
mlflow.delete_experiment(experiment_id)
self.experiments = {key: val for key, val in self.experiments.items() if val.id != experiment_id}
def delete_exp(self, experiment_id=None, experiment_name=None):
assert (
experiment_id is not None or experiment_name is not None
), "Please input a valid experiment id or name before deleting."
try:
if experiment_id is not None:
mlflow.delete_experiment(experiment_id)
self.experiments = {key: val for key, val in self.experiments.items() if val.id != experiment_id}
else:
experiment_id = self.experiments[experiment_name].id
mlflow.delete_experiment(experiment_id)
except:
raise Exception(
"Something went wrong when deleting experiment. Please check if the name/id of the experiment is correct."
)
def list_experiments(self):
# retrieve all the existing experiments
client = mlflow.tracking.MlflowClient(tracking_uri=self.uri)
exps = client.list_experiments()
experiments = dict()
self._total_exps = len(exps)
for i in range(len(exps)):
eid = exps[i].experiment_id
ename = exps[i].name
experiment = MLflowExperiment(eid, ename, self.uri)
experiment.id = eid
experiment.name = ename
experiment._uri = self.uri
experiments[ename] = experiment
return experiments