Index

Symbols

--accept <accept> mlflow-sagemaker-deploy-transform-job command line option --app-name <app_name> mlflow-sagemaker-delete command line option mlflow-sagemaker-deploy command line option --archive mlflow-sagemaker-delete command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-terminate-transform-job command line option --artifact-location <artifact_location> mlflow-experiments-create command line option --artifact-path <artifact_path> mlflow-artifacts-download command line option mlflow-artifacts-list command line option mlflow-artifacts-log-artifact command line option mlflow-artifacts-log-artifacts command line option --artifact-uri <artifact_uri> mlflow-artifacts-download command line option --artifacts-destination <URI> mlflow-server command line option mlflow-ui command line option --artifacts-only mlflow-server command line option --assemble-with <assemble_with> mlflow-sagemaker-deploy-transform-job command line option --async mlflow-sagemaker-delete command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-terminate-transform-job command line option --backend <BACKEND> mlflow-run command line option --backend-config <FILE> mlflow-run command line option --backend-store-uri <PATH> mlflow-gc command line option mlflow-server command line option mlflow-ui command line option --bucket <bucket> mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option --build mlflow-sagemaker-build-and-push-container command line option --compression-type <compression_type> mlflow-sagemaker-deploy-transform-job command line option --config <NAME=VALUE> mlflow-deployments-create command line option mlflow-deployments-create-endpoint command line option mlflow-deployments-delete command line option mlflow-deployments-run-local command line option mlflow-deployments-update command line option mlflow-deployments-update-endpoint command line option --container <container> mlflow-sagemaker-build-and-push-container command line option --content-type <content_type> mlflow-models-predict command line option mlflow-sagemaker-deploy-transform-job command line option --default-artifact-root <URI> mlflow-server command line option mlflow-ui command line option --description <description> mlflow-azureml-build-image command line option --docker-args <NAME=VALUE> mlflow-run command line option --dst-path <dst_path> mlflow-artifacts-download command line option --enable-mlserver mlflow-models-build-docker command line option mlflow-models-serve command line option --endpoint <endpoint> mlflow-deployments-create command line option mlflow-deployments-create-endpoint command line option mlflow-deployments-delete command line option mlflow-deployments-delete-endpoint command line option mlflow-deployments-explain command line option mlflow-deployments-get command line option mlflow-deployments-get-endpoint command line option mlflow-deployments-list command line option mlflow-deployments-predict command line option mlflow-deployments-update command line option mlflow-deployments-update-endpoint command line option --entry-point <NAME> mlflow-run command line option --env-manager <env_manager> mlflow-models-build-docker command line option mlflow-models-predict command line option mlflow-models-prepare-env command line option mlflow-models-serve command line option mlflow-run command line option mlflow-sagemaker-build-and-push-container command line option --execution-role-arn <execution_role_arn> mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option --experiment-id <experiment_id> mlflow-experiments-csv command line option mlflow-experiments-delete command line option mlflow-experiments-rename command line option mlflow-experiments-restore command line option mlflow-run command line option mlflow-runs-list command line option --experiment-name <experiment_name> mlflow-experiments-create command line option mlflow-run command line option --expose-prometheus <expose_prometheus> mlflow-server command line option --filename <filename> mlflow-experiments-csv command line option --flavor <flavor> mlflow-deployments-create command line option mlflow-deployments-run-local command line option mlflow-deployments-update command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option mlflow-sagemaker-run-local command line option --gunicorn-opts <gunicorn_opts> mlflow-server command line option --host <HOST> mlflow-models-serve command line option mlflow-server command line option mlflow-ui command line option --image <image> mlflow-sagemaker-run-local command line option --image-name <image_name> mlflow-azureml-build-image command line option --image-url <image_url> mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option --input-data-type <input_data_type> mlflow-sagemaker-deploy-transform-job command line option --input-filter <input_filter> mlflow-sagemaker-deploy-transform-job command line option --input-path <input_path> mlflow-deployments-explain command line option mlflow-deployments-predict command line option mlflow-models-predict command line option --input-uri <input_uri> mlflow-sagemaker-deploy-transform-job command line option --install-mlflow mlflow-models-build-docker command line option mlflow-models-predict command line option mlflow-models-prepare-env command line option mlflow-models-serve command line option --instance-count <instance_count> mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option --instance-type <instance_type> mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option --job-name <job_name> mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-terminate-transform-job command line option --join-resource <join_resource> mlflow-sagemaker-deploy-transform-job command line option --json-format <json_format> mlflow-models-predict command line option --local-dir <local_dir> mlflow-artifacts-log-artifacts command line option --local-file <local_file> mlflow-artifacts-log-artifact command line option --mlflow-home <PATH> mlflow-azureml-build-image command line option mlflow-models-build-docker command line option mlflow-sagemaker-build-and-push-container command line option --mode <mode> mlflow-sagemaker-deploy command line option --model-name <model_name> mlflow-azureml-build-image command line option mlflow-sagemaker-push-model command line option --model-uri <URI> mlflow-azureml-build-image command line option mlflow-deployments-create command line option mlflow-deployments-run-local command line option mlflow-deployments-update command line option mlflow-models-build-docker command line option mlflow-models-predict command line option mlflow-models-prepare-env command line option mlflow-models-serve command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option mlflow-sagemaker-run-local command line option --name <name> mlflow-deployments-create command line option mlflow-deployments-delete command line option mlflow-deployments-explain command line option mlflow-deployments-get command line option mlflow-deployments-predict command line option mlflow-deployments-run-local command line option mlflow-deployments-update command line option mlflow-models-build-docker command line option --new-name <new_name> mlflow-experiments-rename command line option --no-build mlflow-sagemaker-build-and-push-container command line option --no-conda mlflow-models-predict command line option mlflow-models-prepare-env command line option mlflow-models-serve command line option mlflow-run command line option --no-push mlflow-sagemaker-build-and-push-container command line option --output-filter <output_filter> mlflow-sagemaker-deploy-transform-job command line option --output-path <output_path> mlflow-deployments-explain command line option mlflow-deployments-predict command line option mlflow-models-predict command line option mlflow-sagemaker-deploy-transform-job command line option --param-list <NAME=VALUE> mlflow-run command line option --port <port> mlflow-models-serve command line option mlflow-sagemaker-run-local command line option mlflow-server command line option mlflow-ui command line option --profile <profile> mlflow-pipelines-clean command line option mlflow-pipelines-inspect command line option mlflow-pipelines-run command line option --push mlflow-sagemaker-build-and-push-container command line option --region-name <region_name> mlflow-sagemaker-delete command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option mlflow-sagemaker-terminate-transform-job command line option

--run-id <RUN_ID> mlflow-run command line option --run-id <run_id> mlflow-artifacts-download command line option mlflow-artifacts-list command line option mlflow-artifacts-log-artifact command line option mlflow-artifacts-log-artifacts command line option mlflow-runs-delete command line option mlflow-runs-describe command line option mlflow-runs-restore command line option --run-ids <run_ids> mlflow-gc command line option --run-name <RUN_NAME> mlflow-run command line option --serve-artifacts mlflow-server command line option mlflow-ui command line option --split-type <split_type> mlflow-sagemaker-deploy-transform-job command line option --static-prefix <static_prefix> mlflow-server command line option --step <step> mlflow-pipelines-clean command line option mlflow-pipelines-inspect command line option mlflow-pipelines-run command line option --storage-dir <storage_dir> mlflow-run command line option --subscription-id <subscription_id> mlflow-azureml-build-image command line option --tags <tags> mlflow-azureml-build-image command line option --target <target> mlflow-deployments-create command line option mlflow-deployments-create-endpoint command line option mlflow-deployments-delete command line option mlflow-deployments-delete-endpoint command line option mlflow-deployments-explain command line option mlflow-deployments-get command line option mlflow-deployments-get-endpoint command line option mlflow-deployments-help command line option mlflow-deployments-list command line option mlflow-deployments-list-endpoints command line option mlflow-deployments-predict command line option mlflow-deployments-run-local command line option mlflow-deployments-update command line option mlflow-deployments-update-endpoint command line option --timeout <timeout> mlflow-models-serve command line option mlflow-sagemaker-delete command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-terminate-transform-job command line option --version mlflow command line option --version <VERSION> mlflow-run command line option --view <view> mlflow-experiments-list command line option mlflow-runs-list command line option --vpc-config <vpc_config> mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option --waitress-opts <waitress_opts> mlflow-server command line option --workers <workers> mlflow-models-serve command line option mlflow-server command line option --workspace-name <workspace_name> mlflow-azureml-build-image command line option -A mlflow-run command line option -a mlflow-artifacts-download command line option mlflow-artifacts-list command line option mlflow-artifacts-log-artifact command line option mlflow-artifacts-log-artifacts command line option mlflow-sagemaker-delete command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option -ar mlflow-sagemaker-delete command line option mlflow-sagemaker-deploy command line option -b mlflow-run command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option -C mlflow-deployments-create command line option mlflow-deployments-create-endpoint command line option mlflow-deployments-delete command line option mlflow-deployments-run-local command line option mlflow-deployments-update command line option mlflow-deployments-update-endpoint command line option -c mlflow-run command line option mlflow-sagemaker-build-and-push-container command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option -d mlflow-artifacts-download command line option mlflow-azureml-build-image command line option -e mlflow-run command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option -f mlflow-deployments-create command line option mlflow-deployments-run-local command line option mlflow-deployments-update command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option mlflow-sagemaker-run-local command line option -h mlflow-models-serve command line option mlflow-server command line option mlflow-ui command line option -I mlflow-deployments-explain command line option mlflow-deployments-predict command line option -i mlflow-azureml-build-image command line option mlflow-models-predict command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option mlflow-sagemaker-run-local command line option -j mlflow-models-predict command line option mlflow-sagemaker-deploy-transform-job command line option -l mlflow-artifacts-log-artifact command line option mlflow-artifacts-log-artifacts command line option mlflow-experiments-create command line option -m mlflow-azureml-build-image command line option mlflow-deployments-create command line option mlflow-deployments-run-local command line option mlflow-deployments-update command line option mlflow-models-build-docker command line option mlflow-models-predict command line option mlflow-models-prepare-env command line option mlflow-models-serve command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option mlflow-sagemaker-run-local command line option -n mlflow-azureml-build-image command line option mlflow-experiments-create command line option mlflow-models-build-docker command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option mlflow-sagemaker-terminate-transform-job command line option -O mlflow-deployments-explain command line option mlflow-deployments-predict command line option -o mlflow-experiments-csv command line option mlflow-models-predict command line option mlflow-sagemaker-deploy-transform-job command line option -P mlflow-run command line option -p mlflow-models-serve command line option mlflow-pipelines-clean command line option mlflow-pipelines-inspect command line option mlflow-pipelines-run command line option mlflow-sagemaker-run-local command line option mlflow-server command line option mlflow-ui command line option -r mlflow-artifacts-download command line option mlflow-artifacts-list command line option mlflow-artifacts-log-artifact command line option mlflow-artifacts-log-artifacts command line option mlflow-sagemaker-delete command line option mlflow-sagemaker-terminate-transform-job command line option -s mlflow-azureml-build-image command line option mlflow-pipelines-clean command line option mlflow-pipelines-inspect command line option mlflow-pipelines-run command line option mlflow-sagemaker-deploy-transform-job command line option -t mlflow-azureml-build-image command line option mlflow-deployments-create command line option mlflow-deployments-create-endpoint command line option mlflow-deployments-delete command line option mlflow-deployments-delete-endpoint command line option mlflow-deployments-explain command line option mlflow-deployments-get command line option mlflow-deployments-get-endpoint command line option mlflow-deployments-help command line option mlflow-deployments-list command line option mlflow-deployments-list-endpoints command line option mlflow-deployments-predict command line option mlflow-deployments-run-local command line option mlflow-deployments-update command line option mlflow-deployments-update-endpoint command line option mlflow-models-predict command line option mlflow-models-serve command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option -u mlflow-artifacts-download command line option mlflow-sagemaker-deploy-transform-job command line option -v mlflow-experiments-list command line option mlflow-run command line option mlflow-runs-list command line option mlflow-sagemaker-deploy command line option mlflow-sagemaker-deploy-transform-job command line option mlflow-sagemaker-push-model command line option -w mlflow-azureml-build-image command line option mlflow-models-serve command line option mlflow-server command line option -x mlflow-experiments-csv command line option mlflow-experiments-delete command line option mlflow-experiments-rename command line option mlflow-experiments-restore command line option

_

__new__() (mlflow.pipelines.Pipeline static method)

A

ACTIVE (mlflow.entities.LifecycleStage attribute) ACTIVE_ONLY (mlflow.entities.ViewType attribute) active_run() (in module mlflow) ActiveRun (class in mlflow) add_flavor() (mlflow.models.Model method) add_to_model() (in module mlflow.mleap) (in module mlflow.pyfunc) ALL (mlflow.entities.ViewType attribute) all_status() (mlflow.entities.RunStatus static method) artifact_location() (mlflow.entities.Experiment property) artifact_path() (mlflow.models.model.ModelInfo property) artifact_uri() (mlflow.entities.RunInfo property) artifacts() (mlflow.models.EvaluationResult property) (mlflow.pyfunc.PythonModelContext property)

as_spark_schema() (mlflow.types.Schema method) autolog() (in module mlflow) (in module mlflow.fastai) (in module mlflow.gluon) (in module mlflow.keras) (in module mlflow.lightgbm) (in module mlflow.paddle) (in module mlflow.pyspark.ml) (in module mlflow.pytorch) (in module mlflow.sklearn) (in module mlflow.spark) (in module mlflow.statsmodels) (in module mlflow.tensorflow) (in module mlflow.xgboost) AutologHelpers (class in mlflow.statsmodels)

B

BaseDeploymentClient (class in mlflow.deployments) binary (mlflow.types.DataType attribute)

boolean (mlflow.types.DataType attribute) build_image() (in module mlflow.azureml)

C

can_build_image() (mlflow.models.FlavorBackend method) can_score_model() (mlflow.models.FlavorBackend method) cancel() (mlflow.projects.SubmittedRun method) clean() (mlflow.pipelines.regression.v1.pipeline.RegressionPipeline method) ColSpec (class in mlflow.types) content() (mlflow.models.EvaluationArtifact property) create_deployment() (mlflow.deployments.BaseDeploymentClient method) (mlflow.sagemaker.SageMakerDeploymentClient method) create_endpoint() (mlflow.deployments.BaseDeploymentClient method) (mlflow.sagemaker.SageMakerDeploymentClient method)

create_experiment() (in module mlflow) (mlflow.tracking.MlflowClient method) create_model_version() (mlflow.tracking.MlflowClient method) create_registered_model() (mlflow.tracking.MlflowClient method) create_run() (mlflow.tracking.MlflowClient method) creation_timestamp() (mlflow.entities.model_registry.ModelVersion property) (mlflow.entities.model_registry.RegisteredModel property) current_stage() (mlflow.entities.model_registry.ModelVersion property)

D

data() (mlflow.entities.Run property) DataType (class in mlflow.types) datetime (mlflow.types.DataType attribute) DEFAULT_EXPERIMENT_NAME (mlflow.entities.Experiment attribute) delete() (in module mlflow.sagemaker) delete_deployment() (mlflow.deployments.BaseDeploymentClient method) (mlflow.sagemaker.SageMakerDeploymentClient method) delete_endpoint() (mlflow.deployments.BaseDeploymentClient method) (mlflow.sagemaker.SageMakerDeploymentClient method) delete_experiment() (in module mlflow) (mlflow.tracking.MlflowClient method) delete_model_version() (mlflow.tracking.MlflowClient method) delete_model_version_tag() (mlflow.tracking.MlflowClient method) delete_registered_model() (mlflow.tracking.MlflowClient method)

delete_registered_model_tag() (mlflow.tracking.MlflowClient method) delete_run() (in module mlflow) (mlflow.tracking.MlflowClient method) delete_tag() (in module mlflow) (mlflow.tracking.MlflowClient method) DELETED (mlflow.entities.LifecycleStage attribute) DELETED_ONLY (mlflow.entities.ViewType attribute) deploy() (in module mlflow.azureml) (in module mlflow.sagemaker) deploy_transform_job() (in module mlflow.sagemaker) description() (mlflow.entities.model_registry.ModelVersion property) (mlflow.entities.model_registry.RegisteredModel property) double (mlflow.types.DataType attribute) download_artifacts() (in module mlflow.artifacts) (mlflow.tracking.MlflowClient method)

E

end_run() (in module mlflow) end_time() (mlflow.entities.RunInfo property) eval_and_log_metrics() (in module mlflow.sklearn) evaluate() (in module mlflow) (in module mlflow.models) EvaluationArtifact (class in mlflow.models) EvaluationResult (class in mlflow.models)

ExecutionException Experiment (class in mlflow.entities) experiment_id() (mlflow.entities.Experiment property) (mlflow.entities.RunInfo property) ExperimentTag (class in mlflow.entities) explain() (mlflow.deployments.BaseDeploymentClient method) (mlflow.sagemaker.SageMakerDeploymentClient method)

F

FAILED (mlflow.entities.RunStatus attribute) file_size() (mlflow.entities.FileInfo property) FileInfo (class in mlflow.entities) FINISHED (mlflow.entities.RunStatus attribute) FlavorBackend (class in mlflow.models) flavors() (mlflow.models.model.ModelInfo property) float (mlflow.types.DataType attribute) from_dict() (mlflow.models.Model class method) (mlflow.models.ModelSignature class method) from_json() (mlflow.types.Schema class method) from_json_dict() (mlflow.types.TensorSpec class method) from_proto() (mlflow.entities.Experiment class method) (mlflow.entities.ExperimentTag class method) (mlflow.entities.FileInfo class method) (mlflow.entities.Metric class method) (mlflow.entities.model_registry.ModelVersion class method) (mlflow.entities.model_registry.ModelVersionTag class method) (mlflow.entities.model_registry.RegisteredModel class method) (mlflow.entities.model_registry.RegisteredModelTag class method) (mlflow.entities.Param class method) (mlflow.entities.Run class method) (mlflow.entities.RunData class method) (mlflow.entities.RunInfo class method) (mlflow.entities.RunTag class method) (mlflow.entities.ViewType class method)

from_string() (mlflow.entities.RunStatus static method) (mlflow.entities.SourceType static method) (mlflow.entities.ViewType class method)

G

get_artifact() (mlflow.pipelines.regression.v1.pipeline.RegressionPipeline method) get_artifact_uri() (in module mlflow) get_default_conda_env() (in module mlflow.catboost) (in module mlflow.diviner) (in module mlflow.fastai) (in module mlflow.gluon) (in module mlflow.h2o) (in module mlflow.keras) (in module mlflow.lightgbm) (in module mlflow.onnx) (in module mlflow.paddle) (in module mlflow.pmdarima) (in module mlflow.prophet) (in module mlflow.pyfunc) (in module mlflow.pytorch) (in module mlflow.shap) (in module mlflow.sklearn) (in module mlflow.spacy) (in module mlflow.spark) (in module mlflow.statsmodels) (in module mlflow.tensorflow) (in module mlflow.xgboost) get_default_pip_requirements() (in module mlflow.catboost) (in module mlflow.diviner) (in module mlflow.fastai) (in module mlflow.gluon) (in module mlflow.h2o) (in module mlflow.keras) (in module mlflow.lightgbm) (in module mlflow.onnx) (in module mlflow.paddle) (in module mlflow.pmdarima) (in module mlflow.prophet) (in module mlflow.pyfunc) (in module mlflow.pytorch) (in module mlflow.shap) (in module mlflow.sklearn) (in module mlflow.spacy) (in module mlflow.spark) (in module mlflow.statsmodels) (in module mlflow.tensorflow) (in module mlflow.xgboost)

get_deploy_client() (in module mlflow.deployments) get_deployment() (mlflow.deployments.BaseDeploymentClient method) (mlflow.sagemaker.SageMakerDeploymentClient method) get_endpoint() (mlflow.deployments.BaseDeploymentClient method) (mlflow.sagemaker.SageMakerDeploymentClient method) get_experiment() (in module mlflow) (mlflow.tracking.MlflowClient method) get_experiment_by_name() (in module mlflow) (mlflow.tracking.MlflowClient method) get_input_schema() (mlflow.models.Model method) get_latest_versions() (mlflow.tracking.MlflowClient method) get_metric_history() (mlflow.tracking.MlflowClient method) get_model_dependencies() (in module mlflow.pyfunc) get_model_info() (mlflow.models.Model method) get_model_version() (mlflow.tracking.MlflowClient method) get_model_version_download_uri() (mlflow.tracking.MlflowClient method) get_model_version_stages() (mlflow.tracking.MlflowClient method) get_orderable_attributes() (mlflow.entities.RunInfo class method) get_output_schema() (mlflow.models.Model method) get_registered_model() (mlflow.tracking.MlflowClient method) get_registry_uri() (in module mlflow) (in module mlflow.tracking) get_run() (in module mlflow) (mlflow.tracking.MlflowClient method) get_searchable_attributes() (mlflow.entities.RunInfo class method) get_status() (mlflow.projects.SubmittedRun method) get_tracking_uri() (in module mlflow) (in module mlflow.tracking) get_underlying_model_flavor() (in module mlflow.shap)

H

has_input_names() (mlflow.types.Schema method)

I

infer_pip_requirements() (in module mlflow.models) infer_signature() (in module mlflow.models) info() (mlflow.entities.Run property) input_names() (mlflow.types.Schema method) input_types() (mlflow.types.Schema method) inputs() (mlflow.types.Schema property)

inspect() (mlflow.pipelines.regression.v1.pipeline.RegressionPipeline method) integer (mlflow.types.DataType attribute) is_dir() (mlflow.entities.FileInfo property) is_tensor_spec() (mlflow.types.Schema method) is_terminated() (mlflow.entities.RunStatus static method) is_tracking_uri_set() (in module mlflow.tracking) is_valid() (mlflow.entities.LifecycleStage class method)

J

JOB (mlflow.entities.SourceType attribute)

K

key() (mlflow.entities.ExperimentTag property) (mlflow.entities.Metric property) (mlflow.entities.model_registry.ModelVersionTag property) (mlflow.entities.model_registry.RegisteredModelTag property) (mlflow.entities.Param property) (mlflow.entities.RunTag property)

KILLED (mlflow.entities.RunStatus attribute)

L

last_active_run() (in module mlflow) last_updated_timestamp() (mlflow.entities.model_registry.ModelVersion property) (mlflow.entities.model_registry.RegisteredModel property) latest_versions() (mlflow.entities.model_registry.RegisteredModel property) lifecycle_stage() (mlflow.entities.Experiment property) (mlflow.entities.RunInfo property) LifecycleStage (class in mlflow.entities) list_artifacts() (mlflow.tracking.MlflowClient method) list_deployments() (mlflow.deployments.BaseDeploymentClient method) (mlflow.sagemaker.SageMakerDeploymentClient method) list_endpoints() (mlflow.deployments.BaseDeploymentClient method) (mlflow.sagemaker.SageMakerDeploymentClient method) list_evaluators() (in module mlflow.models) list_experiments() (in module mlflow) (mlflow.tracking.MlflowClient method) list_registered_models() (mlflow.tracking.MlflowClient method) list_run_infos() (in module mlflow) (mlflow.tracking.MlflowClient method) load() (mlflow.models.EvaluationResult class method) (mlflow.models.Model class method) load_context() (mlflow.pyfunc.PythonModel method) load_explainer() (in module mlflow.shap) load_input_example() (mlflow.models.Model method) load_model() (in module mlflow.catboost) (in module mlflow.diviner) (in module mlflow.fastai) (in module mlflow.gluon) (in module mlflow.h2o) (in module mlflow.keras) (in module mlflow.lightgbm) (in module mlflow.onnx) (in module mlflow.paddle) (in module mlflow.pmdarima) (in module mlflow.prophet) (in module mlflow.pyfunc) (in module mlflow.pytorch) (in module mlflow.sklearn) (in module mlflow.spacy) (in module mlflow.spark) (in module mlflow.statsmodels) (in module mlflow.tensorflow) (in module mlflow.xgboost) load_pyfunc() (in module mlflow.pyfunc) load_state_dict() (in module mlflow.pytorch)

LOCAL (mlflow.entities.SourceType attribute) log() (mlflow.models.Model class method) log_artifact() (in module mlflow) (mlflow.tracking.MlflowClient method) log_artifacts() (in module mlflow) (mlflow.tracking.MlflowClient method) log_batch() (mlflow.tracking.MlflowClient method) log_dict() (in module mlflow) (mlflow.tracking.MlflowClient method) log_explainer() (in module mlflow.shap) log_explanation() (in module mlflow.shap) log_figure() (in module mlflow) (mlflow.tracking.MlflowClient method) log_image() (in module mlflow) (mlflow.tracking.MlflowClient method) log_metric() (in module mlflow) (mlflow.tracking.MlflowClient method) log_metrics() (in module mlflow) log_model() (in module mlflow.catboost) (in module mlflow.diviner) (in module mlflow.fastai) (in module mlflow.gluon) (in module mlflow.h2o) (in module mlflow.keras) (in module mlflow.lightgbm) (in module mlflow.mleap) (in module mlflow.onnx) (in module mlflow.paddle) (in module mlflow.pmdarima) (in module mlflow.prophet) (in module mlflow.pyfunc) (in module mlflow.pytorch) (in module mlflow.sklearn) (in module mlflow.spacy) (in module mlflow.spark) (in module mlflow.statsmodels) (in module mlflow.tensorflow) (in module mlflow.xgboost) log_param() (in module mlflow) (mlflow.tracking.MlflowClient method) log_params() (in module mlflow) log_state_dict() (in module mlflow.pytorch) log_text() (in module mlflow) (mlflow.tracking.MlflowClient method) long (mlflow.types.DataType attribute)

M

matches_view_type() (mlflow.entities.LifecycleStage class method) metadata() (mlflow.pyfunc.PyFuncModel property) Metric (class in mlflow.entities) metrics() (mlflow.entities.RunData property) (mlflow.models.EvaluationResult property) MissingConfigException MLeapSerializationException mlflow module mlflow command line option --version mlflow-artifacts-download command line option --artifact-path <artifact_path> --artifact-uri <artifact_uri> --dst-path <dst_path> --run-id <run_id> -a -d -r -u mlflow-artifacts-list command line option --artifact-path <artifact_path> --run-id <run_id> -a -r mlflow-artifacts-log-artifact command line option --artifact-path <artifact_path> --local-file <local_file> --run-id <run_id> -a -l -r mlflow-artifacts-log-artifacts command line option --artifact-path <artifact_path> --local-dir <local_dir> --run-id <run_id> -a -l -r mlflow-azureml-build-image command line option --description <description> --image-name <image_name> --mlflow-home <PATH> --model-name <model_name> --model-uri <URI> --subscription-id <subscription_id> --tags <tags> --workspace-name <workspace_name> -d -i -m -n -s -t -w mlflow-db-upgrade command line option URL mlflow-deployments-create command line option --config <NAME=VALUE> --endpoint <endpoint> --flavor <flavor> --model-uri <URI> --name <name> --target <target> -C -f -m -t mlflow-deployments-create-endpoint command line option --config <NAME=VALUE> --endpoint <endpoint> --target <target> -C -t mlflow-deployments-delete command line option --config <NAME=VALUE> --endpoint <endpoint> --name <name> --target <target> -C -t mlflow-deployments-delete-endpoint command line option --endpoint <endpoint> --target <target> -t mlflow-deployments-explain command line option --endpoint <endpoint> --input-path <input_path> --name <name> --output-path <output_path> --target <target> -I -O -t mlflow-deployments-get command line option --endpoint <endpoint> --name <name> --target <target> -t mlflow-deployments-get-endpoint command line option --endpoint <endpoint> --target <target> -t mlflow-deployments-help command line option --target <target> -t mlflow-deployments-list command line option --endpoint <endpoint> --target <target> -t mlflow-deployments-list-endpoints command line option --target <target> -t mlflow-deployments-predict command line option --endpoint <endpoint> --input-path <input_path> --name <name> --output-path <output_path> --target <target> -I -O -t mlflow-deployments-run-local command line option --config <NAME=VALUE> --flavor <flavor> --model-uri <URI> --name <name> --target <target> -C -f -m -t mlflow-deployments-update command line option --config <NAME=VALUE> --endpoint <endpoint> --flavor <flavor> --model-uri <URI> --name <name> --target <target> -C -f -m -t mlflow-deployments-update-endpoint command line option --config <NAME=VALUE> --endpoint <endpoint> --target <target> -C -t mlflow-experiments-create command line option --artifact-location <artifact_location> --experiment-name <experiment_name> -l -n mlflow-experiments-csv command line option --experiment-id <experiment_id> --filename <filename> -o -x mlflow-experiments-delete command line option --experiment-id <experiment_id> -x mlflow-experiments-list command line option --view <view> -v mlflow-experiments-rename command line option --experiment-id <experiment_id> --new-name <new_name> -x mlflow-experiments-restore command line option --experiment-id <experiment_id> -x mlflow-gc command line option --backend-store-uri <PATH> --run-ids <run_ids> mlflow-models-build-docker command line option --enable-mlserver --env-manager <env_manager> --install-mlflow --mlflow-home <PATH> --model-uri <URI> --name <name> -m -n mlflow-models-predict command line option --content-type <content_type> --env-manager <env_manager> --input-path <input_path> --install-mlflow --json-format <json_format> --model-uri <URI> --no-conda --output-path <output_path> -i -j -m -o -t mlflow-models-prepare-env command line option --env-manager <env_manager> --install-mlflow --model-uri <URI> --no-conda -m mlflow-models-serve command line option --enable-mlserver --env-manager <env_manager> --host <HOST> --install-mlflow --model-uri <URI> --no-conda --port <port> --timeout <timeout> --workers <workers> -h -m -p -t -w mlflow-pipelines-clean command line option --profile <profile> --step <step> -p -s mlflow-pipelines-inspect command line option --profile <profile> --step <step> -p -s mlflow-pipelines-run command line option --profile <profile> --step <step> -p -s mlflow-run command line option --backend <BACKEND> --backend-config <FILE> --docker-args <NAME=VALUE> --entry-point <NAME> --env-manager <env_manager> --experiment-id <experiment_id> --experiment-name <experiment_name> --no-conda --param-list <NAME=VALUE> --run-id <RUN_ID> --run-name <RUN_NAME> --storage-dir <storage_dir> --version <VERSION> -A -b -c -e -P -v URI mlflow-runs-delete command line option --run-id <run_id> mlflow-runs-describe command line option --run-id <run_id> mlflow-runs-list command line option --experiment-id <experiment_id> --view <view> -v

mlflow-runs-restore command line option --run-id <run_id> mlflow-sagemaker-build-and-push-container command line option --build --container <container> --env-manager <env_manager> --mlflow-home <PATH> --no-build --no-push --push -c mlflow-sagemaker-delete command line option --app-name <app_name> --archive --async --region-name <region_name> --timeout <timeout> -a -ar -r mlflow-sagemaker-deploy command line option --app-name <app_name> --archive --async --bucket <bucket> --execution-role-arn <execution_role_arn> --flavor <flavor> --image-url <image_url> --instance-count <instance_count> --instance-type <instance_type> --mode <mode> --model-uri <URI> --region-name <region_name> --timeout <timeout> --vpc-config <vpc_config> -a -ar -b -c -e -f -i -m -t -v mlflow-sagemaker-deploy-transform-job command line option --accept <accept> --archive --assemble-with <assemble_with> --async --bucket <bucket> --compression-type <compression_type> --content-type <content_type> --execution-role-arn <execution_role_arn> --flavor <flavor> --image-url <image_url> --input-data-type <input_data_type> --input-filter <input_filter> --input-uri <input_uri> --instance-count <instance_count> --instance-type <instance_type> --job-name <job_name> --join-resource <join_resource> --model-uri <URI> --output-filter <output_filter> --output-path <output_path> --region-name <region_name> --split-type <split_type> --timeout <timeout> --vpc-config <vpc_config> -a -b -c -e -f -i -j -m -n -o -s -t -u -v mlflow-sagemaker-push-model command line option --bucket <bucket> --execution-role-arn <execution_role_arn> --flavor <flavor> --image-url <image_url> --model-name <model_name> --model-uri <URI> --region-name <region_name> --vpc-config <vpc_config> -b -e -f -i -m -n -v mlflow-sagemaker-run-local command line option --flavor <flavor> --image <image> --model-uri <URI> --port <port> -f -i -m -p mlflow-sagemaker-terminate-transform-job command line option --archive --async --job-name <job_name> --region-name <region_name> --timeout <timeout> -n -r mlflow-server command line option --artifacts-destination <URI> --artifacts-only --backend-store-uri <PATH> --default-artifact-root <URI> --expose-prometheus <expose_prometheus> --gunicorn-opts <gunicorn_opts> --host <HOST> --port <port> --serve-artifacts --static-prefix <static_prefix> --waitress-opts <waitress_opts> --workers <workers> -h -p -w mlflow-ui command line option --artifacts-destination <URI> --backend-store-uri <PATH> --default-artifact-root <URI> --host <HOST> --port <port> --serve-artifacts -h -p mlflow.artifacts module mlflow.azureml module mlflow.catboost module mlflow.deployments module mlflow.diviner module mlflow.entities module mlflow.entities.model_registry module mlflow.exceptions module mlflow.exceptions.MlflowException mlflow.fastai module mlflow.gluon module mlflow.h2o module mlflow.keras module mlflow.lightgbm module mlflow.mleap module mlflow.models module mlflow.onnx module mlflow.paddle module mlflow.pipelines module mlflow.pipelines.regression.v1.pipeline module mlflow.pmdarima module mlflow.projects module mlflow.prophet module mlflow.pyfunc module mlflow.pyspark.ml module mlflow.pytorch module mlflow.sagemaker module mlflow.shap module mlflow.sklearn module mlflow.spacy module mlflow.spark module mlflow.statsmodels module mlflow.store.entities module mlflow.tensorflow module mlflow.tracking module mlflow.types module mlflow.xgboost module mlflow_version() (mlflow.models.model.ModelInfo property) MlflowClient (class in mlflow.tracking) Model (class in mlflow.models) model_uri() (mlflow.models.model.ModelInfo property) model_uuid() (mlflow.models.model.ModelInfo property) ModelInfo (class in mlflow.models.model) ModelSignature (class in mlflow.models) ModelVersion (class in mlflow.entities.model_registry) ModelVersionTag (class in mlflow.entities.model_registry) module mlflow mlflow.artifacts mlflow.azureml mlflow.catboost mlflow.deployments mlflow.diviner mlflow.entities mlflow.entities.model_registry mlflow.exceptions mlflow.fastai mlflow.gluon mlflow.h2o mlflow.keras mlflow.lightgbm mlflow.mleap mlflow.models mlflow.onnx mlflow.paddle mlflow.pipelines mlflow.pipelines.regression.v1.pipeline mlflow.pmdarima mlflow.projects mlflow.prophet mlflow.pyfunc mlflow.pyspark.ml mlflow.pytorch mlflow.sagemaker mlflow.shap mlflow.sklearn mlflow.spacy mlflow.spark mlflow.statsmodels mlflow.store.entities mlflow.tensorflow mlflow.tracking mlflow.types mlflow.xgboost

N

name() (mlflow.entities.Experiment property) (mlflow.entities.model_registry.ModelVersion property) (mlflow.entities.model_registry.RegisteredModel property) (mlflow.types.ColSpec property) (mlflow.types.TensorSpec property)

NOTEBOOK (mlflow.entities.SourceType attribute) numpy_types() (mlflow.types.Schema method)

P

PagedList (class in mlflow.store.entities) pandas_types() (mlflow.types.Schema method) Param (class in mlflow.entities) params() (mlflow.entities.RunData property) path() (mlflow.entities.FileInfo property) Pipeline (class in mlflow.pipelines) predict() (mlflow.deployments.BaseDeploymentClient method) (mlflow.models.FlavorBackend method) (mlflow.pyfunc.PyFuncModel method) (mlflow.pyfunc.PythonModel method) (mlflow.sagemaker.SageMakerDeploymentClient method)

prepare_env() (mlflow.models.FlavorBackend method) PROJECT (mlflow.entities.SourceType attribute) push_image_to_ecr() (in module mlflow.sagemaker) push_model_to_sagemaker() (in module mlflow.sagemaker) PyFuncModel (class in mlflow.pyfunc) PythonModel (class in mlflow.pyfunc) PythonModelContext (class in mlflow.pyfunc)

R

register_model() (in module mlflow) RegisteredModel (class in mlflow.entities.model_registry) RegisteredModelTag (class in mlflow.entities.model_registry) RegressionPipeline (class in mlflow.pipelines.regression.v1.pipeline) rename_experiment() (mlflow.tracking.MlflowClient method) rename_registered_model() (mlflow.tracking.MlflowClient method) RestException restore_experiment() (mlflow.tracking.MlflowClient method) restore_run() (mlflow.tracking.MlflowClient method) Run (class in mlflow.entities) run() (in module mlflow) (in module mlflow.projects) (mlflow.pipelines.regression.v1.pipeline.RegressionPipeline method)

run_id() (mlflow.entities.model_registry.ModelVersion property) (mlflow.entities.RunInfo property) (mlflow.models.model.ModelInfo property) (mlflow.projects.SubmittedRun property) run_link() (mlflow.entities.model_registry.ModelVersion property) run_local() (in module mlflow.deployments) (in module mlflow.sagemaker) run_uuid() (mlflow.entities.RunInfo property) RunData (class in mlflow.entities) RunInfo (class in mlflow.entities) RUNNING (mlflow.entities.RunStatus attribute) RunStatus (class in mlflow.entities) RunTag (class in mlflow.entities)

S

SageMakerDeploymentClient (class in mlflow.sagemaker) save() (mlflow.models.EvaluationResult method) (mlflow.models.Model method) save_explainer() (in module mlflow.shap) save_model() (in module mlflow.catboost) (in module mlflow.diviner) (in module mlflow.fastai) (in module mlflow.gluon) (in module mlflow.h2o) (in module mlflow.keras) (in module mlflow.lightgbm) (in module mlflow.mleap) (in module mlflow.onnx) (in module mlflow.paddle) (in module mlflow.pmdarima) (in module mlflow.prophet) (in module mlflow.pyfunc) (in module mlflow.pytorch) (in module mlflow.sklearn) (in module mlflow.spacy) (in module mlflow.spark) (in module mlflow.statsmodels) (in module mlflow.tensorflow) (in module mlflow.xgboost) save_state_dict() (in module mlflow.pytorch) saved_input_example_info() (mlflow.models.Model property) (mlflow.models.model.ModelInfo property) SCHEDULED (mlflow.entities.RunStatus attribute) Schema (class in mlflow.types) search_model_versions() (mlflow.tracking.MlflowClient method) search_registered_models() (mlflow.tracking.MlflowClient method) search_runs() (in module mlflow) (mlflow.tracking.MlflowClient method)

serve() (mlflow.models.FlavorBackend method) set_experiment() (in module mlflow) set_experiment_tag() (in module mlflow) (mlflow.tracking.MlflowClient method) set_experiment_tags() (in module mlflow) set_model_version_tag() (mlflow.tracking.MlflowClient method) set_registered_model_tag() (mlflow.tracking.MlflowClient method) set_registry_uri() (in module mlflow) (in module mlflow.tracking) set_tag() (in module mlflow) (mlflow.tracking.MlflowClient method) set_tags() (in module mlflow) set_terminated() (mlflow.tracking.MlflowClient method) set_tracking_uri() (in module mlflow) (in module mlflow.tracking) shape() (mlflow.types.TensorSpec property) should_autolog (mlflow.statsmodels.AutologHelpers attribute) signature() (mlflow.models.Model property) signature_dict() (mlflow.models.model.ModelInfo property) source() (mlflow.entities.model_registry.ModelVersion property) SourceType (class in mlflow.entities) SOURCETYPE_TO_STRING (mlflow.entities.SourceType attribute) spark_udf() (in module mlflow.pyfunc) start_run() (in module mlflow) start_time() (mlflow.entities.RunInfo property) status() (mlflow.entities.model_registry.ModelVersion property) (mlflow.entities.RunInfo property) status_message() (mlflow.entities.model_registry.ModelVersion property) step() (mlflow.entities.Metric property) string (mlflow.types.DataType attribute) SubmittedRun (class in mlflow.projects)

T

tags() (mlflow.entities.Experiment property) (mlflow.entities.model_registry.ModelVersion property) (mlflow.entities.model_registry.RegisteredModel property) (mlflow.entities.RunData property) target_help() (in module mlflow.sagemaker) TensorSpec (class in mlflow.types) terminate_transform_job() (in module mlflow.sagemaker) timestamp() (mlflow.entities.Metric property) to_dict() (mlflow.models.Model method) (mlflow.models.ModelSignature method) (mlflow.types.Schema method) to_dictionary() (mlflow.entities.Run method) (mlflow.entities.RunData method) to_json() (mlflow.models.Model method) (mlflow.types.Schema method) to_numpy() (mlflow.types.DataType method) to_pandas() (mlflow.types.DataType method) to_proto() (mlflow.entities.Experiment method) (mlflow.entities.ExperimentTag method) (mlflow.entities.FileInfo method) (mlflow.entities.Metric method) (mlflow.entities.model_registry.ModelVersion method) (mlflow.entities.model_registry.ModelVersionTag method) (mlflow.entities.model_registry.RegisteredModel method) (mlflow.entities.model_registry.RegisteredModelTag method) (mlflow.entities.Param method) (mlflow.entities.Run method) (mlflow.entities.RunData method) (mlflow.entities.RunInfo method) (mlflow.entities.RunTag method) (mlflow.entities.ViewType class method)

to_string() (mlflow.entities.RunStatus static method) (mlflow.entities.SourceType static method) (mlflow.entities.ViewType class method) to_yaml() (mlflow.models.Model method) transition_model_version_stage() (mlflow.tracking.MlflowClient method) type() (mlflow.types.ColSpec property) (mlflow.types.TensorSpec property)

U

UNKNOWN (mlflow.entities.SourceType attribute) update_deployment() (mlflow.deployments.BaseDeploymentClient method) (mlflow.sagemaker.SageMakerDeploymentClient method) update_endpoint() (mlflow.deployments.BaseDeploymentClient method) (mlflow.sagemaker.SageMakerDeploymentClient method) update_model_version() (mlflow.tracking.MlflowClient method) update_registered_model() (mlflow.tracking.MlflowClient method)

URI mlflow-run command line option uri() (mlflow.models.EvaluationArtifact property) URL mlflow-db-upgrade command line option user_id() (mlflow.entities.model_registry.ModelVersion property) (mlflow.entities.RunInfo property) utc_time_created() (mlflow.models.model.ModelInfo property)

V

value() (mlflow.entities.ExperimentTag property) (mlflow.entities.Metric property) (mlflow.entities.model_registry.ModelVersionTag property) (mlflow.entities.model_registry.RegisteredModelTag property) (mlflow.entities.Param property) (mlflow.entities.RunTag property)

version() (mlflow.entities.model_registry.ModelVersion property) view_type_to_stages() (mlflow.entities.LifecycleStage class method) ViewType (class in mlflow.entities)

W

wait() (mlflow.projects.SubmittedRun method)