Add Recorder and ExpManager

qlib/workflow/__init__.py

@@ -0,0 +1,157 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+
+from contextlib import contextmanager
+from .record import MLflowRecorder
+from .exp import MLflowExpManager
+
+class Record:
+    def __init__(self):
+        pass
+
+    @contextmanager
+    def start_exp(self, experiment_name=None, uri=None, project_path=None, artifact_location=None, nested=False):
+        raise NotImplementedError(f"Please implement the `start_exp` method.")
+    
+    def search_runs(self, experiment_ids=None, filter_string='', run_view_type=1, max_results=100000, order_by=None):
+        raise NotImplementedError(f"Please implement the `search_runs` method.")
+    
+    def get_exp(self, experiment_id):
+        raise NotImplementedError(f"Please implement the `get_exp` method.")
+
+    def get_exp_by_name(self, experiment_name):
+        raise NotImplementedError(f"Please implement the `get_exp_by_name` method.")
+    
+    def create_exp(self, experiment_name, artifact_location=None):
+        raise NotImplementedError(f"Please implement the `create_exp` method.")
+    
+    def set_exp(self, experiment_name):
+        raise NotImplementedError(f"Please implement the `set_exp` method.")
+
+    def delete_exp(self, experiment_id):
+        raise NotImplementedError(f"Please implement the `create_exp` method.")
+
+    def set_tracking_uri(self, uri):
+        raise NotImplementedError(f"Please implement the `set_tracking_uri` method.")
+    
+    def get_tracking_uri(self):
+        raise NotImplementedError(f"Please implement the `get_tracking_uri` method.")
+    
+    def get_recorder(self):
+        raise NotImplementedError(f"Please implement the `get_recorder` method.")
+
+    def save_object(self, name, data):
+        raise NotImplementedError(f"Please implement the `save_object` method.")
+
+    def save_objects(self, name_data_list):
+        raise NotImplementedError(f"Please implement the `save_objects` method.")
+
+    def load_object(self, name):
+        raise NotImplementedError(f"Please implement the `load_object` method.")
+    
+    def log_param(self, key, value):
+        raise NotImplementedError(f"Please implement the `log_param` method.")
+
+    def log_params(self, params):
+        raise NotImplementedError(f"Please implement the `log_params` method.")
+
+    def log_metric(self, key, value, step=None):
+        raise NotImplementedError(f"Please implement the `log_metric` method.")
+
+    def log_metrics(self, metrics, step=None):
+        raise NotImplementedError(f"Please implement the `log_metrics` method.")
+    
+    def set_tag(self, key, value):
+        raise NotImplementedError(f"Please implement the `set_tag` method.")
+
+    def set_tags(self, tags):
+        raise NotImplementedError(f"Please implement the `log_tags` method.")
+
+    def delete_tag(self, key):
+        raise NotImplementedError(f"Please implement the `delete_tag` method.")
+    
+    def log_artifact(self, local_path, artifact_path=None):
+        raise NotImplementedError(f"Please implement the `log_artifact` method.")
+
+    def log_artifacts(self, local_dir, artifact_path=None):
+        raise NotImplementedError(f"Please implement the `log_artifacts` method.")
+
+    def get_artifact_uri(self, artifact_path=None):
+        raise NotImplementedError(f"Please implement the `get_artifact_uri` method.")
+
+class MLflowRecord(Record):
+    def __init__(self):
+        self.exp_manager = MLflowExpManager()
+
+    @contextmanager
+    def start_exp(self, experiment_name=None, uri=None, project_path=None, artifact_location=None, nested=False):
+        yield self.exp_manager.start_exp(experiment_name, uri, project_path, artifact_location, nested)
+    
+    def search_runs(self, experiment_ids=None, filter_string='', run_view_type=1, max_results=100000, order_by=None):
+        return self.exp_manager.search_runs(experiment_ids, filter_string, run_view_type, max_results, order_by)
+    
+    def get_exp(self, experiment_id):
+        return self.exp_manager.get_exp(experiment_id)
+
+    def get_exp_by_name(self, experiment_name):
+        return self.exp_manager.get_exp_by_name(experiment_name)
+    
+    def create_exp(self, experiment_name, artifact_location=None):
+        self.exp_manager.create_exp(experiment_name, artifact_location)
+    
+    def set_exp(self, experiment_name):
+        self.exp_manager.set_exp(experiment_name)
+
+    def delete_exp(self, experiment_id):
+        self.exp_manager.delete_exp(experiment_id)
+
+    def set_tracking_uri(self, uri):
+        self.exp_manager.set_tracking_uri(uri)
+    
+    def get_tracking_uri(self):
+        return self.exp_manager.get_tracking_uri()
+    
+    def get_recorder(self):
+        return self.exp_manager.get_recorder()
+
+    def save_object(self, name, data):
+        self.exp_manager.active_recorder.save_object(name, data)
+
+    def save_objects(self, name_data_list):
+        self.exp_manager.active_recorder.save_objects(name_data_list)
+
+    def load_object(self, name):
+        return self.exp_manager.active_recorder.load_object(name)
+    
+    def log_param(self, key, value):
+        self.exp_manager.active_recorder.log_param(key, value)
+
+    def log_params(self, params):
+        self.exp_manager.active_recorder.log_params(params)
+
+    def log_metric(self, key, value, step=None):
+        self.exp_manager.active_recorder.log_metric(key, value, step)
+
+    def log_metrics(self, metrics, step=None):
+        self.exp_manager.active_recorder.log_metrics(metrics, step)
+    
+    def set_tag(self, key, value):
+        self.exp_manager.active_recorder.set_tag(key, value)
+
+    def set_tags(self, tags):
+        self.exp_manager.active_recorder.set_tags(tags)
+
+    def delete_tag(self, key):
+        self.exp_manager.active_recorder.delete_tag(key)
+    
+    def log_artifact(self, local_path, artifact_path=None):
+        self.exp_manager.active_recorder.log_artifact(local_path, artifact_path)
+
+    def log_artifacts(self, local_dir, artifact_path=None):
+        self.exp_manager.active_recorder.log_artifacts(local_dir, artifact_path)
+
+    def get_artifact_uri(self, artifact_path=None):
+        return self.exp_manager.active_recorder.get_artifact_uri(artifact_path)
+
+# global record
+R = MLflowRecord()