TrueFoundry ML Client

Usage

from truefoundry.ml import get_client

client = get_client()

client.create_run(
    ml_repo="my-ml-repo",
    run_name="my-run",
    tags={"key": "value"},
)

get_run_by_id

Get an existing run by the run_id.

Parameters

run_id

str

required

Returns

return

MlFoundryRun

Usage

from truefoundry.ml import get_client

client = get_client()

client.get_run_by_id(
    run_id="run-id-123",
)

get_run_by_fqn

Get an existing run by fqn.

Parameters

run_fqn

str

required

Returns

return

MlFoundryRun

Usage

from truefoundry.ml import get_client

client = get_client()

client.get_run_by_fqn(
    run_fqn="value",
)

get_run_by_name

Get an existing run by run_name.

Parameters

ml_repo

str

required

run_name

str

required

Returns

return

MlFoundryRun

Usage

from truefoundry.ml import get_client

client = get_client()

client.get_run_by_name(
    ml_repo="my-ml-repo",
    run_name="my-run",
)

search_runs

The user must have READ access to the ML Repo.

Parameters

ml_repo

str

required

filter_string

str

run_view_type

ViewType

default:"value"

🔗 ViewType

order_by

Sequence[str]

default:"..."

job_run_name

Optional[str]

default:"None"

Returns

return

Iterator[MlFoundryRun]

Usage

from truefoundry.ml import get_client

client = get_client()

client.search_runs(
    ml_repo="my-ml-repo",
    filter_string="value",
    run_view_type="value",
    order_by="value",
    job_run_name="value",
)

# Iterate through results
for item in response:
    print(item.name)

get_model_version

Get the model version to download contents or load it in memory

Parameters

ml_repo

str

required

name

str

required

version

Union[str, int]

default:"constants.LATEST_ARTIFACT_OR_MODEL_VERSION"

Returns

return

Optional[ModelVersion]

Usage

from truefoundry.ml import get_client

client = get_client()

client.get_model_version(
    ml_repo="my-ml-repo",
    name="my-run",
    version="value",
)

get_model_version_by_fqn

Get the model version to download contents or load it in memory

Parameters

fqn

str

required

Returns

return

ModelVersion

Usage

from truefoundry.ml import get_client

client = get_client()

client.get_model_version_by_fqn(
    fqn="run-id-123",
)

list_model_versions

Get all the version of a model to download contents or load them in memory

Parameters

ml_repo

str

required

name

str

required

Returns

return

Iterator[ModelVersion]

Usage

from truefoundry.ml import get_client

client = get_client()

client.list_model_versions(
    ml_repo="my-ml-repo",
    name="my-run",
)

list_model_versions_by_fqn

List versions for a given model

Parameters

model_fqn

str

required

Returns

return

Iterator[ModelVersion]

Usage

from truefoundry.ml import get_client

client = get_client()

client.list_model_versions_by_fqn(
    model_fqn="value",
)

get_artifact_version

Get the model version to download contents or load it in memory

Parameters

ml_repo

str

required

name

str

required

artifact_type

Optional[ArtifactType]

default:"ArtifactType.ARTIFACT"

🔗 ArtifactType

version

Union[str, int]

default:"constants.LATEST_ARTIFACT_OR_MODEL_VERSION"

Returns

return

Optional[ArtifactVersion]

Usage

from truefoundry.ml import get_client

client = get_client()

client.get_artifact_version(
    ml_repo="my-ml-repo",
    name="my-run",
    artifact_type="value",
    version="value",
)

get_artifact_version_by_fqn

Get the artifact version to download contents

Parameters

fqn

str

required

Returns

return

ArtifactVersion

Usage

from truefoundry.ml import get_client

client = get_client()

client.get_artifact_version_by_fqn(
    fqn="run-id-123",
)

list_artifact_versions

Get all the version of na artifact to download contents or load them in memory

Parameters

ml_repo

str

required

name

str

required

artifact_type

Optional[ArtifactType]

default:"ArtifactType.ARTIFACT"

🔗 ArtifactType

Returns

return

Iterator[ArtifactVersion]

Usage

from truefoundry.ml import get_client

client = get_client()

client.list_artifact_versions(
    ml_repo="my-ml-repo",
    name="my-run",
    artifact_type="value",
)

list_artifact_versions_by_fqn

List versions for a given artifact

Parameters

artifact_fqn

str

required

Returns

return

Iterator[ArtifactVersion]

Usage

from truefoundry.ml import get_client

client = get_client()

client.list_artifact_versions_by_fqn(
    artifact_fqn="value",
)

log_artifact

Logs an artifact for the current ml_repo.

Parameters

ml_repo

str

required

name

str

required

artifact_paths

List[Union[Tuple[str], Tuple[str, Optional[str]], ArtifactPath]]

required

🔗 ArtifactPath

description

Optional[str]

default:"None"

metadata

Optional[Dict[str, Any]]

default:"None"

progress

Optional[bool]

default:"None"

Returns

return

Optional[ArtifactVersion]

🔗 ModelVersionEnvironment

Usage

from truefoundry.ml import get_client

client = get_client()

client.log_artifact(
    ml_repo="my-ml-repo",
    name="my-run",
    artifact_paths=[ArtifactPath("file.txt")],
    description="value",
    metadata="value",
    progress="value",
)

log_model

Serialize and log a versioned model under the current ml_repo. Each logged model generates a new version

Parameters

ml_repo

str

required

name

str

required

model_file_or_folder

Union[str, BlobStorageDirectory]

required

🔗 BlobStorageDirectory

description

Optional[str]

default:"None"

metadata

Optional[Dict[str, Any]]

default:"None"

progress

Optional[bool]

default:"None"

framework

Optional[Union[str, ModelFramework, Any]]

default:"None"

🔗 ModelFramework

environment

Optional[ModelVersionEnvironment]

default:"None"

Returns

return

ModelVersion

Usage

from truefoundry.ml import get_client

client = get_client()

client.log_model(
    ml_repo="my-ml-repo",
    name="my-run",
    model_file_or_folder="model.pkl",
    description="value",
    metadata="value",
    progress="value",
    framework="value",
    environment="value",
)

create_data_directory

Create DataDirectory to Upload the files

Parameters

ml_repo

str

required

name

str

required

description

Optional[str]

default:"None"

metadata

Optional[Dict[str, Any]]

default:"None"

Returns

return

DataDirectory

Usage

from truefoundry.ml import get_client

client = get_client()

client.create_data_directory(
    ml_repo="my-ml-repo",
    name="my-run",
    description="value",
    metadata="value",
)

get_data_directory_by_fqn

Get the DataDirectory by DataDirectory FQN

Parameters

fqn

str

required

Returns

return

DataDirectory

Usage

from truefoundry.ml import get_client

client = get_client()

client.get_data_directory_by_fqn(
    fqn="run-id-123",
)

get_data_directory

Get an existing data_directory by name.

Parameters

ml_repo

str

required

name

str

required

Returns

return

DataDirectory

Usage

from truefoundry.ml import get_client

client = get_client()

client.get_data_directory(
    ml_repo="my-ml-repo",
    name="my-run",
)

list_data_directories

Get the list of DataDirectory in a ml_repo

Parameters

ml_repo

str

required

Returns

return

Iterator[DataDirectory]