viam.gen.service.mlmodel.v1.mlmodel_pb2

@generated by mypy-protobuf. Do not edit manually! isort:skip_file

Attributes

`DESCRIPTOR`
`LABEL_TYPE_UNSPECIFIED`
`LABEL_TYPE_TENSOR_VALUE`	the value of the arrays/tensor is the label index
`LABEL_TYPE_TENSOR_AXIS`	the position of the tensor value in the axis is the label index
`Global___LabelType`
`Global___InferRequest`
`Global___InferResponse`
`Global___MetadataRequest`
`Global___MetadataResponse`
`Global___Metadata`
`Global___TensorInfo`
`Global___File`
`Global___FlatTensorDataInt8`
`Global___FlatTensorDataUInt8`
`Global___FlatTensorDataInt16`
`Global___FlatTensorDataUInt16`
`Global___FlatTensorDataInt32`
`Global___FlatTensorDataUInt32`
`Global___FlatTensorDataInt64`
`Global___FlatTensorDataUInt64`
`Global___FlatTensorDataFloat`
`Global___FlatTensorDataDouble`
`Global___FlatTensor`
`Global___FlatTensors`

Classes

`LabelType`
`InferRequest`	Abstract base class for protocol messages.
`InferResponse`	Abstract base class for protocol messages.
`MetadataRequest`	Abstract base class for protocol messages.
`MetadataResponse`	Abstract base class for protocol messages.
`Metadata`	Abstract base class for protocol messages.
`TensorInfo`	Abstract base class for protocol messages.
`File`	Abstract base class for protocol messages.
`FlatTensorDataInt8`	Abstract base class for protocol messages.
`FlatTensorDataUInt8`	Abstract base class for protocol messages.
`FlatTensorDataInt16`	Abstract base class for protocol messages.
`FlatTensorDataUInt16`	Abstract base class for protocol messages.
`FlatTensorDataInt32`	Abstract base class for protocol messages.
`FlatTensorDataUInt32`	Abstract base class for protocol messages.
`FlatTensorDataInt64`	Abstract base class for protocol messages.
`FlatTensorDataUInt64`	Abstract base class for protocol messages.
`FlatTensorDataFloat`	Abstract base class for protocol messages.
`FlatTensorDataDouble`	Abstract base class for protocol messages.
`FlatTensor`	Abstract base class for protocol messages.
`FlatTensors`	Abstract base class for protocol messages.

Module Contents

viam.gen.service.mlmodel.v1.mlmodel_pb2.DESCRIPTOR: google.protobuf.descriptor.FileDescriptor

class viam.gen.service.mlmodel.v1.mlmodel_pb2.LabelType: Bases: _LabelType

viam.gen.service.mlmodel.v1.mlmodel_pb2.LABEL_TYPE_UNSPECIFIED: LabelType

viam.gen.service.mlmodel.v1.mlmodel_pb2.LABEL_TYPE_TENSOR_VALUE: LabelType: the value of the arrays/tensor is the label index

viam.gen.service.mlmodel.v1.mlmodel_pb2.LABEL_TYPE_TENSOR_AXIS: LabelType: the position of the tensor value in the axis is the label index

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___LabelType = LabelType

class viam.gen.service.mlmodel.v1.mlmodel_pb2.InferRequest(*, name: str = ..., input_tensors: Global___FlatTensors | None = ..., extra: google.protobuf.struct_pb2.Struct | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

name: str: name of the model service

input_tensors() → Global___FlatTensors: the input data is provided as set of named flat tensors

extra() → google.protobuf.struct_pb2.Struct: Additional arguments to the method

HasField(field_name: _HasFieldArgType) → bool

Checks if a certain field is set for the message.

For a oneof group, checks if any field inside is set. Note that if the field_name is not defined in the message descriptor, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___InferRequest = InferRequest

class viam.gen.service.mlmodel.v1.mlmodel_pb2.InferResponse(*, output_tensors: Global___FlatTensors | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

output_tensors() → Global___FlatTensors: the output data is provided as a set of named flat tensors

HasField(field_name: _HasFieldArgType) → bool

Checks if a certain field is set for the message.

For a oneof group, checks if any field inside is set. Note that if the field_name is not defined in the message descriptor, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___InferResponse = InferResponse

class viam.gen.service.mlmodel.v1.mlmodel_pb2.MetadataRequest(*, name: str = ..., extra: google.protobuf.struct_pb2.Struct | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

name: str: name of the model service

extra() → google.protobuf.struct_pb2.Struct: Additional arguments to the method

HasField(field_name: _HasFieldArgType) → bool

Checks if a certain field is set for the message.

For a oneof group, checks if any field inside is set. Note that if the field_name is not defined in the message descriptor, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___MetadataRequest = MetadataRequest

class viam.gen.service.mlmodel.v1.mlmodel_pb2.MetadataResponse(*, metadata: Global___Metadata | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

metadata() → Global___Metadata: this is the metadata associated with the ML model

HasField(field_name: _HasFieldArgType) → bool

Checks if a certain field is set for the message.

For a oneof group, checks if any field inside is set. Note that if the field_name is not defined in the message descriptor, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___MetadataResponse = MetadataResponse

class viam.gen.service.mlmodel.v1.mlmodel_pb2.Metadata(*, name: str = ..., type: str = ..., description: str = ..., input_info: collections.abc.Iterable[Global___TensorInfo] | None = ..., output_info: collections.abc.Iterable[Global___TensorInfo] | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

name: str: name of the model

type: str: type of model e.g. object_detector, text_classifier

description: str: description of the model

input_info() → google.protobuf.internal.containers.RepeatedCompositeFieldContainer[Global___TensorInfo]: the necessary input arrays/tensors for an inference, order matters

output_info() → google.protobuf.internal.containers.RepeatedCompositeFieldContainer[Global___TensorInfo]: the output arrays/tensors of the model, order matters

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___Metadata = Metadata

class viam.gen.service.mlmodel.v1.mlmodel_pb2.TensorInfo(*, name: str = ..., description: str = ..., data_type: str = ..., shape: collections.abc.Iterable[int] | None = ..., associated_files: collections.abc.Iterable[Global___File] | None = ..., extra: google.protobuf.struct_pb2.Struct | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

name: str: name of the data in the array/tensor

description: str: description of the data in the array/tensor

data_type: str: data type of the array/tensor, e.g. float32, float64, uint8

shape() → google.protobuf.internal.containers.RepeatedScalarFieldContainer[int]: shape of the array/tensor (-1 for unknown)

associated_files() → google.protobuf.internal.containers.RepeatedCompositeFieldContainer[Global___File]: files associated with the array/tensor, like for category labels

extra() → google.protobuf.struct_pb2.Struct: anything else you want to say

HasField(field_name: _HasFieldArgType) → bool

Checks if a certain field is set for the message.

For a oneof group, checks if any field inside is set. Note that if the field_name is not defined in the message descriptor, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___TensorInfo = TensorInfo

class viam.gen.service.mlmodel.v1.mlmodel_pb2.File(*, name: str = ..., description: str = ..., label_type: Global___LabelType = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

name: str: name of the file, with file extension

description: str: description of what the file contains

label_type: Global___LabelType: How to associate the arrays/tensors to the labels in the file

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___File = File

class viam.gen.service.mlmodel.v1.mlmodel_pb2.FlatTensorDataInt8(*, data: bytes = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

data: bytes

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___FlatTensorDataInt8 = FlatTensorDataInt8

class viam.gen.service.mlmodel.v1.mlmodel_pb2.FlatTensorDataUInt8(*, data: bytes = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

data: bytes

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___FlatTensorDataUInt8 = FlatTensorDataUInt8

class viam.gen.service.mlmodel.v1.mlmodel_pb2.FlatTensorDataInt16(*, data: collections.abc.Iterable[int] | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

data() → google.protobuf.internal.containers.RepeatedScalarFieldContainer[int]: packs two 16-bit numbers per entry - explicitly little-endian so big-endian producers/consumers must compensate

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___FlatTensorDataInt16 = FlatTensorDataInt16

class viam.gen.service.mlmodel.v1.mlmodel_pb2.FlatTensorDataUInt16(*, data: collections.abc.Iterable[int] | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

data() → google.protobuf.internal.containers.RepeatedScalarFieldContainer[int]: packs two 16-bit numbers per entry - explicitly little-endian so big-endian producers/consumers must compensate

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___FlatTensorDataUInt16 = FlatTensorDataUInt16

class viam.gen.service.mlmodel.v1.mlmodel_pb2.FlatTensorDataInt32(*, data: collections.abc.Iterable[int] | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

data() → google.protobuf.internal.containers.RepeatedScalarFieldContainer[int]

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___FlatTensorDataInt32 = FlatTensorDataInt32

class viam.gen.service.mlmodel.v1.mlmodel_pb2.FlatTensorDataUInt32(*, data: collections.abc.Iterable[int] | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

data() → google.protobuf.internal.containers.RepeatedScalarFieldContainer[int]

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___FlatTensorDataUInt32 = FlatTensorDataUInt32

class viam.gen.service.mlmodel.v1.mlmodel_pb2.FlatTensorDataInt64(*, data: collections.abc.Iterable[int] | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

data() → google.protobuf.internal.containers.RepeatedScalarFieldContainer[int]

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___FlatTensorDataInt64 = FlatTensorDataInt64

class viam.gen.service.mlmodel.v1.mlmodel_pb2.FlatTensorDataUInt64(*, data: collections.abc.Iterable[int] | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

data() → google.protobuf.internal.containers.RepeatedScalarFieldContainer[int]

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___FlatTensorDataUInt64 = FlatTensorDataUInt64

class viam.gen.service.mlmodel.v1.mlmodel_pb2.FlatTensorDataFloat(*, data: collections.abc.Iterable[float] | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

data() → google.protobuf.internal.containers.RepeatedScalarFieldContainer[float]

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___FlatTensorDataFloat = FlatTensorDataFloat

class viam.gen.service.mlmodel.v1.mlmodel_pb2.FlatTensorDataDouble(*, data: collections.abc.Iterable[float] | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

data() → google.protobuf.internal.containers.RepeatedScalarFieldContainer[float]

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___FlatTensorDataDouble = FlatTensorDataDouble

class viam.gen.service.mlmodel.v1.mlmodel_pb2.FlatTensor(*, shape: collections.abc.Iterable[int] | None = ..., int8_tensor: Global___FlatTensorDataInt8 | None = ..., uint8_tensor: Global___FlatTensorDataUInt8 | None = ..., int16_tensor: Global___FlatTensorDataInt16 | None = ..., uint16_tensor: Global___FlatTensorDataUInt16 | None = ..., int32_tensor: Global___FlatTensorDataInt32 | None = ..., uint32_tensor: Global___FlatTensorDataUInt32 | None = ..., int64_tensor: Global___FlatTensorDataInt64 | None = ..., uint64_tensor: Global___FlatTensorDataUInt64 | None = ..., float_tensor: Global___FlatTensorDataFloat | None = ..., double_tensor: Global___FlatTensorDataDouble | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

shape() → google.protobuf.internal.containers.RepeatedScalarFieldContainer[int]: the shape of the provided tensor as a list of integer extents

int8_tensor() → Global___FlatTensorDataInt8

uint8_tensor() → Global___FlatTensorDataUInt8

int16_tensor() → Global___FlatTensorDataInt16

uint16_tensor() → Global___FlatTensorDataUInt16

int32_tensor() → Global___FlatTensorDataInt32

uint32_tensor() → Global___FlatTensorDataUInt32

int64_tensor() → Global___FlatTensorDataInt64

uint64_tensor() → Global___FlatTensorDataUInt64

float_tensor() → Global___FlatTensorDataFloat

double_tensor() → Global___FlatTensorDataDouble

HasField(field_name: _HasFieldArgType) → bool

Checks if a certain field is set for the message.

For a oneof group, checks if any field inside is set. Note that if the field_name is not defined in the message descriptor, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

WhichOneof(oneof_group: _WhichOneofArgType_tensor) → _WhichOneofReturnType_tensor | None

Returns the name of the field that is set inside a oneof group.

If no field is set, returns None.

Parameters:: oneof_group (str) – the name of the oneof group to check.
Returns:: The name of the group that is set, or None.
Return type:: str or None
Raises:: ValueError – no group with the given name exists

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___FlatTensor = FlatTensor

class viam.gen.service.mlmodel.v1.mlmodel_pb2.FlatTensors(*, tensors: collections.abc.Mapping[str, Global___FlatTensor] | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

class TensorsEntry(*, key: str = ..., value: Global___FlatTensor | None = ...)

Bases: google.protobuf.message.Message

Abstract base class for protocol messages.

Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below.

key: str

value() → Global___FlatTensor

HasField(field_name: _HasFieldArgType) → bool

Checks if a certain field is set for the message.

For a oneof group, checks if any field inside is set. Note that if the field_name is not defined in the message descriptor, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

tensors() → google.protobuf.internal.containers.MessageMap[str, Global___FlatTensor]: A name-indexed collection of flat tensor objects

type viam.gen.service.mlmodel.v1.mlmodel_pb2.Global___FlatTensors = FlatTensors