_InternalNamespace

Module: ml.internal_namespace

_ModelFramework

Module: ml.model_framework
__root__
ModelFrameworkType
required

_SerializationFormatLoaderRegistry

Module: ml.model_framework

ActiveRuns

Module: ml.session

AppName

Custom ParamType to validate application names Module: ml.utils Custom ParamType to validate application names. Union, One Of:

ArtifactIdentifier

Module: ml.truefoundry_artifact_repo
artifact_version_id
Optional[uuid.UUID]
dataset_id
Optional[str]
dataset_fqn
Optional[str]

ArtifactPath

Module: ml.artifact
src
str
required
dest
Optional[str]

ArtifactVersion

Module: ml.artifact
name
str
required
Get the name of the artifact
artifact_fqn
str
required
Get fqn of the artifact
version
int
required
Get version information of the artifact
fqn
str
required
Get fqn of the current artifact version
step
Optional[int]
required
Get the step in which artifact was created
description
str
required
Get description of the artifact
metadata
Dict[str, Any]
required
Get metadata for the current artifact
version_alias
Optional[str]
required
Get version alias for the current artifact version
created_at
Optional[datetime.datetime]
required
Get the time at which artifact was created
updated_at
Optional[datetime.datetime]
required
Get the information about when the artifact was updated

ArtifactVersionDownloadInfo

Module: ml.artifact
download_dir
str
required

ArtifactVersionInternalMetadata

Module: ml.artifact
files_dir
str
required

BlobStorageDirectory

Module: ml.artifact
uri
StrictStr
required

BoundingBox

Module: ml.types
position
Position
required
class_name
NonEmptyStr
required
caption
Optional[str]

BoundingBoxGroups

Module: ml.types
__root__
Dict[Group, List[BoundingBox]]
required

ClassGroups

Module: ml.types
__root__
Dict[Group, List[NonEmptyStr]]
required

Config

Module: ml.types

DataDirectory

Module: ml.dataset
name
str
required
Get the name of the DataDirectory
fqn
str
required
Get fqn of the DataDirectory
storage_root
str
required
Get storage_root of the DataDirectory
description
Optional[str]
required
Get description of the DataDirectory
metadata
Dict[str, Any]
required
Get metadata for the current DataDirectory
created_at
datetime.datetime
required
Get the time at which DataDirectory was created
updated_at
datetime.datetime
required
Get the information about when the DataDirectory was updated

DataDirectoryPath

Module: ml.dataset
src
str
required
dest
Optional[str]

EnumMissingMixin

Module: ml.enums

FastAIFramework

FastAI model Framework Module: ml.model_framework FastAI model Framework
type
Literal[Any]
default:"fastai"
required

FileInfo

Module: ml.entities
path
StrictStr
required
is_dir
StrictBool
required
file_size
Optional[StrictInt]
signed_url
Optional[StrictStr]

GitInfo

Module: ml.git_info
current_commit_sha
str
required
current_branch_name
str
required
remote_url
Optional[str]
required
diff_patch
str
required
is_dirty
bool
required

GluonFramework

Gluon model Framework Module: ml.model_framework Gluon model Framework
type
Literal[Any]
default:"gluon"
required

H2OFramework

H2O model Framework Module: ml.model_framework H2O model Framework
type
Literal[Any]
default:"h2o"
required

Image

Module: ml.image
image
Any
required
caption
Optional[str]
required
class_groups
Optional[ClassGroups]
required
bbox_groups
Optional[BoundingBoxGroups]
required

ImageRunLogType

Module: ml.image
value
Dict[str, Any]
required

ImageVersionInternalMetadata

Module: ml.image
image_file
str
required
image_metadata_file
str
required

InferMethodName

Name of the inference method for model serving Module: ml._autogen.client.models Inference method name

Iterator

An iterator that yields items one at a time Module: typing Iterator type for collections

KerasFramework

Keras model Framework Module: ml.model_framework Keras model Framework
type
Literal[Any]
default:"keras"
required

LibraryName

Name of a library dependency Module: ml._autogen.entities.artifacts Library name for dependencies

LightGBMFramework

LightGBM model Framework Module: ml.model_framework LightGBM model Framework
type
Literal[Any]
default:"lightgbm"
required

Metric

Module: ml.entities
key
StrictStr
required
value
Optional[Union[StrictFloat, StrictInt]]
timestamp
Optional[StrictInt]
step
Optional[StrictInt]

MlFoundry

MlFoundry Module: ml.mlfoundry_api MlFoundry.

MlFoundryArtifactsRepository

Module: ml.truefoundry_artifact_repo

MlFoundryException

Module: ml.exceptions Union, One Of:

MlFoundryRun

MlFoundryRun Module: ml.mlfoundry_run MlFoundryRun.
run_id
str
required
Get run_id for the current run
run_name
str
required
Get run_name for the current run
fqn
str
required
Get fqn for the current run
status
RunStatus
required
🔗 RunStatusGet status for the current run
ml_repo
str
required
Get ml_repo name of which the current run is part of
auto_end
bool
required
Tells whether automatic end for run is True or False
Get Mlfoundry dashboard link for a run

MLFoundryServerApiClient

Module: ml.session
tfy_host
str
required
access_token
str
required

MLFoundrySession

Module: ml.session Union, One Of:

MLRepo

A repository for ML training runs and versioned entities Module: ml._autogen.entities.artifacts MLRepo is a repository ML training runs that log params, metrics, plots, images and versioned entities like artifacts, models, prompts, tools, agents

ModelFrameworkType

Base class for all model framework implementations Module: ml.model_framework Base class for model framework types

ModelVersion

Module: ml.model
name
str
required
Get the name of the model
model_fqn
str
required
Get fqn of the model
version
int
required
Get version information of the model
fqn
str
required
Get fqn of the current model version
step
Optional[int]
required
Get the step in which model was created
description
str
required
Get description of the model
metadata
Dict[str, Any]
required
Get metadata for the current model
version_alias
Optional[str]
required
Get version alias for the current model version
environment
Optional[ModelVersionEnvironment]
required
🔗 ModelVersionEnvironmentGet the environment details for the model
framework
Optional[Any]
required
Get the framework of the model
created_at
Optional[datetime.datetime]
required
Get the time at which model version was created
updated_at
Optional[datetime.datetime]
required
Get the information about when the model version was updated

ModelVersionDownloadInfo

Module: ml.model
download_dir
str
required
model_dir
str
required
model_framework
ModelFramework
default:"ModelFramework.UNKNOWN"
required
model_filename
Optional[str]

ModelVersionEnvironment

Environment configuration for model deployment Module: ml._autogen.client.models Environment for model version

ModelVersionInternalMetadata

Module: ml.model
files_dir
str
required
model_dir
str
required
model_is_null
bool
required
framework
ModelFramework
default:"ModelFramework.UNKNOWN"
required
transformers_pipeline_task
Optional[str]
model_filename
Optional[str]
mlfoundry_version
Optional[str]
truefoundry_version
Optional[str]

NonEmptyString

Module: ml.utils Union, One Of:

NumpyEncoder

Special json encoder for numpy types Module: ml.run_utils Special json encoder for numpy types Union, One Of:

ONNXFramework

ONNX model Framework Module: ml.model_framework ONNX model Framework
type
Literal[Any]
default:"onnx"
required

PaddleFramework

Paddle model Framework Module: ml.model_framework Paddle model Framework
type
Literal[Any]
default:"paddle"
required

Plot

Module: ml.plot

PlotArtifact

Module: ml.plot
artifact_file
str
required
format
Format
required

PlotRunLogType

Module: ml.plot
value
PlotArtifact
required

PlotVersionInternalMetadata

Module: ml.plot
plot_file
str
required

Position

Module: ml.types
min_x
float
required
min_y
float
required
max_x
float
required
max_y
float
required

PydanticBase

Module: ml.pydantic_base Union, One Of:

PyTorchFramework

PyTorch model Framework Module: ml.model_framework PyTorch model Framework
type
Literal[Any]
default:"pytorch"
required

SklearnFramework

Sklearn model Framework Module: ml.model_framework Sklearn model Framework
type
Literal[Any]
default:"sklearn"
required

SklearnModelSchema

Schema definition for scikit-learn model serialization Module: ml._autogen.client.models Schema for scikit-learn models

SpaCyFramework

SpaCy model Framework Module: ml.model_framework SpaCy model Framework
type
Literal[Any]
default:"spacy"
required

StatsModelsFramework

StatsModels model Framework Module: ml.model_framework StatsModels model Framework
type
Literal[Any]
default:"statsmodels"
required

TensorFlowFramework

TensorFlow model Framework Module: ml.model_framework TensorFlow model Framework
type
Literal[Any]
default:"tensorflow"
required

TransformersFramework

Transformers model Framework Module: ml.model_framework Transformers model Framework
type
Literal[Any]
default:"transformers"
required

XGBoostFramework

XGBoost model Framework Module: ml.model_framework XGBoost model Framework
type
Literal[Any]
default:"xgboost"
required

XGBoostModelSchema

Schema definition for XGBoost model serialization Module: ml._autogen.client.models Schema for XGBoost models