1.27.0
MLflow
Quickstart
Tutorials and Examples
Concepts
MLflow Tracking
MLflow Projects
MLflow Models
MLflow Model Registry
MLflow Pipelines (experimental)
MLflow Plugins
Command-Line Interface
Search
Python API
R API
Java API
REST API
Contribute
Documentation
Index
Edit on GitHub
Index
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F
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J
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K
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L
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M
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N
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P
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R
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U
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V
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W
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)