furiosa.server.types package

Submodules

furiosa.server.types.model_repository module

class furiosa.server.types.model_repository.RepositoryIndexErrorResponse(*, error: Optional[str] = None)

Bases: pydantic.main.BaseModel

error: Optional[str]

class furiosa.server.types.model_repository.RepositoryIndexRequest(*, ready: Optional[bool] = None)

Bases: pydantic.main.BaseModel

ready: Optional[bool]

class furiosa.server.types.model_repository.RepositoryIndexResponse(*, __root__: List[furiosa.server.types.model_repository.RepositoryIndexResponseItem]): Bases: pydantic.main.BaseModel

class furiosa.server.types.model_repository.RepositoryIndexResponseItem(*, name: str, version: Optional[str] = None, state: furiosa.server.types.model_repository.State, reason: str)

Bases: pydantic.main.BaseModel

name: str

reason: str

state: furiosa.server.types.model_repository.State

version: Optional[str]

class furiosa.server.types.model_repository.RepositoryLoadErrorResponse(*, error: Optional[str] = None)

Bases: pydantic.main.BaseModel

error: Optional[str]

class furiosa.server.types.model_repository.RepositoryUnloadErrorResponse(*, error: Optional[str] = None)

Bases: pydantic.main.BaseModel

error: Optional[str]

class furiosa.server.types.model_repository.State(value)

Bases: enum.Enum

An enumeration.

LOADING = 'LOADING'

READY = 'READY'

UNAVAILABLE = 'UNAVAILABLE'

UNKNOWN = 'UNKNOWN'

UNLOADING = 'UNLOADING'

furiosa.server.types.predict module

class furiosa.server.types.predict.InferenceErrorResponse(*, error: Optional[str] = None)

Bases: pydantic.main.BaseModel

error: Optional[str]

class furiosa.server.types.predict.InferenceRequest(*, id: Optional[str] = None, parameters: Optional[furiosa.server.types.predict.Parameters] = None, inputs: List[furiosa.server.types.predict.RequestInput], outputs: Optional[List[furiosa.server.types.predict.RequestOutput]] = None)

Bases: pydantic.main.BaseModel

id: Optional[str]

inputs: List[furiosa.server.types.predict.RequestInput]

outputs: Optional[List[furiosa.server.types.predict.RequestOutput]]

parameters: Optional[furiosa.server.types.predict.Parameters]

class furiosa.server.types.predict.InferenceResponse(*, model_name: str, model_version: Optional[str] = None, id: Optional[str] = None, parameters: Optional[furiosa.server.types.predict.Parameters] = None, outputs: List[furiosa.server.types.predict.ResponseOutput])

Bases: pydantic.main.BaseModel

id: Optional[str]

model_name: str

model_version: Optional[str]

outputs: List[furiosa.server.types.predict.ResponseOutput]

parameters: Optional[furiosa.server.types.predict.Parameters]

class furiosa.server.types.predict.MetadataModelErrorResponse(*, error: str)

Bases: pydantic.main.BaseModel

error: str

class furiosa.server.types.predict.MetadataModelResponse(*, name: str, versions: Optional[List[str]] = None, platform: str, inputs: Optional[List[furiosa.server.types.predict.MetadataTensor]] = None, outputs: Optional[List[furiosa.server.types.predict.MetadataTensor]] = None)

Bases: pydantic.main.BaseModel

inputs: Optional[List[furiosa.server.types.predict.MetadataTensor]]

name: str

outputs: Optional[List[furiosa.server.types.predict.MetadataTensor]]

platform: str

versions: Optional[List[str]]

class furiosa.server.types.predict.MetadataServerErrorResponse(*, error: str)

Bases: pydantic.main.BaseModel

error: str

class furiosa.server.types.predict.MetadataServerResponse(*, name: str, version: str, extensions: List[str])

Bases: pydantic.main.BaseModel

extensions: List[str]

name: str

version: str

class furiosa.server.types.predict.MetadataTensor(*, name: str, datatype: str, shape: List[int], tags: Optional[furiosa.server.types.predict.Tags] = None)

Bases: pydantic.main.BaseModel

datatype: str

name: str

shape: List[int]

tags: Optional[furiosa.server.types.predict.Tags]

class furiosa.server.types.predict.Parameters(*, content_type: Optional[str] = None, **extra_data: Any)

Bases: pydantic.main.BaseModel

class Config

Bases: object

extra = 'allow'

content_type: Optional[str]

class furiosa.server.types.predict.RequestInput(*, name: str, shape: List[int], datatype: str, parameters: Optional[furiosa.server.types.predict.Parameters] = None, data: furiosa.server.types.predict.TensorData)

Bases: pydantic.main.BaseModel

data: furiosa.server.types.predict.TensorData

datatype: str

name: str

parameters: Optional[furiosa.server.types.predict.Parameters]

shape: List[int]

class furiosa.server.types.predict.RequestOutput(*, name: str, parameters: Optional[furiosa.server.types.predict.Parameters] = None)

Bases: pydantic.main.BaseModel

name: str

parameters: Optional[furiosa.server.types.predict.Parameters]

class furiosa.server.types.predict.ResponseOutput(*, name: str, shape: List[int], datatype: str, parameters: Optional[furiosa.server.types.predict.Parameters] = None, data: furiosa.server.types.predict.TensorData)

Bases: pydantic.main.BaseModel

data: furiosa.server.types.predict.TensorData

datatype: str

name: str

parameters: Optional[furiosa.server.types.predict.Parameters]

shape: List[int]

class furiosa.server.types.predict.Tags(*, content_type: Optional[str] = None, **extra_data: Any)

Bases: pydantic.main.BaseModel

class Config

Bases: object

extra = 'allow'

content_type: Optional[str]

class furiosa.server.types.predict.TensorData(*, __root__: Any): Bases: pydantic.main.BaseModel

Module contents

class furiosa.server.types.InferenceErrorResponse(*, error: Optional[str] = None)

Bases: pydantic.main.BaseModel

error: Optional[str]

class furiosa.server.types.InferenceRequest(*, id: Optional[str] = None, parameters: Optional[furiosa.server.types.predict.Parameters] = None, inputs: List[furiosa.server.types.predict.RequestInput], outputs: Optional[List[furiosa.server.types.predict.RequestOutput]] = None)

Bases: pydantic.main.BaseModel

id: Optional[str]

inputs: List[furiosa.server.types.predict.RequestInput]

outputs: Optional[List[furiosa.server.types.predict.RequestOutput]]

parameters: Optional[furiosa.server.types.predict.Parameters]

class furiosa.server.types.InferenceResponse(*, model_name: str, model_version: Optional[str] = None, id: Optional[str] = None, parameters: Optional[furiosa.server.types.predict.Parameters] = None, outputs: List[furiosa.server.types.predict.ResponseOutput])

Bases: pydantic.main.BaseModel

id: Optional[str]

model_name: str

model_version: Optional[str]

outputs: List[furiosa.server.types.predict.ResponseOutput]

parameters: Optional[furiosa.server.types.predict.Parameters]

class furiosa.server.types.MetadataModelErrorResponse(*, error: str)

Bases: pydantic.main.BaseModel

error: str

class furiosa.server.types.MetadataModelResponse(*, name: str, versions: Optional[List[str]] = None, platform: str, inputs: Optional[List[furiosa.server.types.predict.MetadataTensor]] = None, outputs: Optional[List[furiosa.server.types.predict.MetadataTensor]] = None)

Bases: pydantic.main.BaseModel

inputs: Optional[List[furiosa.server.types.predict.MetadataTensor]]

name: str

outputs: Optional[List[furiosa.server.types.predict.MetadataTensor]]

platform: str

versions: Optional[List[str]]

class furiosa.server.types.MetadataServerErrorResponse(*, error: str)

Bases: pydantic.main.BaseModel

error: str

class furiosa.server.types.MetadataServerResponse(*, name: str, version: str, extensions: List[str])

Bases: pydantic.main.BaseModel

extensions: List[str]

name: str

version: str

class furiosa.server.types.MetadataTensor(*, name: str, datatype: str, shape: List[int], tags: Optional[furiosa.server.types.predict.Tags] = None)

Bases: pydantic.main.BaseModel

datatype: str

name: str

shape: List[int]

tags: Optional[furiosa.server.types.predict.Tags]

class furiosa.server.types.Parameters(*, content_type: Optional[str] = None, **extra_data: Any)

Bases: pydantic.main.BaseModel

class Config

Bases: object

extra = 'allow'

content_type: Optional[str]

class furiosa.server.types.RepositoryIndexErrorResponse(*, error: Optional[str] = None)

Bases: pydantic.main.BaseModel

error: Optional[str]

class furiosa.server.types.RepositoryIndexRequest(*, ready: Optional[bool] = None)

Bases: pydantic.main.BaseModel

ready: Optional[bool]

class furiosa.server.types.RepositoryIndexResponse(*, __root__: List[furiosa.server.types.model_repository.RepositoryIndexResponseItem]): Bases: pydantic.main.BaseModel

class furiosa.server.types.RepositoryIndexResponseItem(*, name: str, version: Optional[str] = None, state: furiosa.server.types.model_repository.State, reason: str)

Bases: pydantic.main.BaseModel

name: str

reason: str

state: furiosa.server.types.model_repository.State

version: Optional[str]

class furiosa.server.types.RepositoryLoadErrorResponse(*, error: Optional[str] = None)

Bases: pydantic.main.BaseModel

error: Optional[str]

class furiosa.server.types.RepositoryUnloadErrorResponse(*, error: Optional[str] = None)

Bases: pydantic.main.BaseModel

error: Optional[str]

class furiosa.server.types.RequestInput(*, name: str, shape: List[int], datatype: str, parameters: Optional[furiosa.server.types.predict.Parameters] = None, data: furiosa.server.types.predict.TensorData)

Bases: pydantic.main.BaseModel

data: furiosa.server.types.predict.TensorData

datatype: str

name: str

parameters: Optional[furiosa.server.types.predict.Parameters]

shape: List[int]

class furiosa.server.types.RequestOutput(*, name: str, parameters: Optional[furiosa.server.types.predict.Parameters] = None)

Bases: pydantic.main.BaseModel

name: str

parameters: Optional[furiosa.server.types.predict.Parameters]

class furiosa.server.types.ResponseOutput(*, name: str, shape: List[int], datatype: str, parameters: Optional[furiosa.server.types.predict.Parameters] = None, data: furiosa.server.types.predict.TensorData)

Bases: pydantic.main.BaseModel

data: furiosa.server.types.predict.TensorData

datatype: str

name: str

parameters: Optional[furiosa.server.types.predict.Parameters]

shape: List[int]

class furiosa.server.types.State(value)

Bases: enum.Enum

An enumeration.

LOADING = 'LOADING'

READY = 'READY'

UNAVAILABLE = 'UNAVAILABLE'

UNKNOWN = 'UNKNOWN'

UNLOADING = 'UNLOADING'

class furiosa.server.types.Tags(*, content_type: Optional[str] = None, **extra_data: Any)

Bases: pydantic.main.BaseModel

class Config

Bases: object

extra = 'allow'

content_type: Optional[str]

class furiosa.server.types.TensorData(*, __root__: Any): Bases: pydantic.main.BaseModel