flytekit.core.resources

Class	Description
`ResourceSpec`
`Resources`	This class is used to specify both resource requests and resource limits.

Method	Description
`construct_extended_resources()`	Convert public extended resources to idl.
`convert_resources_to_resource_model()`	Convert flytekit `Resources` objects to a Resources model.
`pod_spec_from_resources()`

Property	Type	Description
`SHARED_MEMORY_MOUNT_NAME`	`str`
`SHARED_MEMORY_MOUNT_PATH`	`str`
`TYPE_CHECKING`	`bool`

Methods

construct_extended_resources()

        
    
def construct_extended_resources(
    accelerator: typing.Optional[flytekit.extras.accelerators.BaseAccelerator] = None,
    shared_memory: typing.Union[typing.Literal[True], str, NoneType] = None,
) -> typing.Optional[flyteidl.core.tasks_pb2.ExtendedResources]

Convert public extended resources to idl.

Parameter	Type	Description
`accelerator`	`typing.Optional[flytekit.extras.accelerators.BaseAccelerator]`	The accelerator to use for this task.
`shared_memory`	`typing.Union[typing.Literal[True], str, NoneType]`	If True, then shared memory will be attached to the container where the size is equal to the allocated memory. If str, then the shared memory is set to that size.

convert_resources_to_resource_model()

        
    
def convert_resources_to_resource_model(
    requests: typing.Optional[flytekit.core.resources.Resources] = None,
    limits: typing.Optional[flytekit.core.resources.Resources] = None,
) -> flytekit.models.task.Resources

Convert flytekit Resources objects to a Resources model

Parameter	Type	Description
`requests`	`typing.Optional[flytekit.core.resources.Resources]`	Resource requests. Optional, defaults to `None`
`limits`	`typing.Optional[flytekit.core.resources.Resources]`	Resource limits. Optional, defaults to `None`

Returns: The given resources as requests and limits

pod_spec_from_resources()

        
    
def pod_spec_from_resources(
    primary_container_name: typing.Optional[str] = None,
    requests: typing.Optional[flytekit.core.resources.Resources] = None,
    limits: typing.Optional[flytekit.core.resources.Resources] = None,
    k8s_gpu_resource_key: str = 'nvidia.com/gpu',
) -> V1PodSpec

Parameter	Type	Description
`primary_container_name`	`typing.Optional[str]`
`requests`	`typing.Optional[flytekit.core.resources.Resources]`
`limits`	`typing.Optional[flytekit.core.resources.Resources]`
`k8s_gpu_resource_key`	`str`

flytekit.core.resources.ResourceSpec

Parameters

        
    
class ResourceSpec(
    requests: flytekit.core.resources.Resources,
    limits: flytekit.core.resources.Resources,
)

Parameter	Type	Description
`requests`	`flytekit.core.resources.Resources`
`limits`	`flytekit.core.resources.Resources`

Methods

Method	Description
`from_dict()`
`from_multiple_resource()`	Convert Resources that represent both a requests and limits into a ResourceSpec.
`to_dict()`

from_dict()

        
    
def from_dict(
    d,
    dialect = None,
)

Parameter	Type	Description
`d`
`dialect`

from_multiple_resource()

        
    
def from_multiple_resource(
    resource: flytekit.core.resources.Resources,
) -> ResourceSpec

Convert Resources that represent both a requests and limits into a ResourceSpec.

Parameter	Type	Description
`resource`	`flytekit.core.resources.Resources`

to_dict()

        
    
def to_dict()

flytekit.core.resources.Resources

This class is used to specify both resource requests and resource limits.

        
    
Resources(cpu="1", mem="2048")  # This is 1 CPU and 2 KB of memory
Resources(cpu="100m", mem="2Gi")  # This is 1/10th of a CPU and 2 gigabytes of memory
Resources(cpu=0.5, mem=1024) # This is 500m CPU and 1 KB of memory

# For Kubernetes-based tasks, pods use ephemeral local storage for scratch space, caching, and for logs.
# This allocates 1Gi of such local storage.
Resources(ephemeral_storage="1Gi")

When used together with @task(resources=), you a specific the request and limits with one object. When the value is set to a tuple or list, the first value is the request and the second value is the limit. If the value is a single value, then both the requests and limit is set to that value. For example, the Resource(cpu=("1", "2"), mem=1024) will set the cpu request to 1, cpu limit to 2, mem limit and request to 1024.

Persistent storage is not currently supported on the Flyte backend.

Please see the User Guide for detailed examples. Also refer to the K8s conventions.

Parameters

        
    
class Resources(
    cpu: typing.Union[str, int, float, list, tuple, NoneType] = None,
    mem: typing.Union[str, int, list, tuple, NoneType] = None,
    gpu: typing.Union[str, int, list, tuple, NoneType] = None,
    ephemeral_storage: typing.Union[str, int, NoneType] = None,
)

Parameter	Type	Description
`cpu`	`typing.Union[str, int, float, list, tuple, NoneType]`
`mem`	`typing.Union[str, int, list, tuple, NoneType]`
`gpu`	`typing.Union[str, int, list, tuple, NoneType]`
`ephemeral_storage`	`typing.Union[str, int, NoneType]`

Methods

Method	Description
`from_dict()`
`to_dict()`

from_dict()

        
    
def from_dict(
    d,
    dialect = None,
)

Parameter	Type	Description
`d`
`dialect`

to_dict()

        
    
def to_dict()

flytekit.core.resources

Directory

Classes

Methods

Variables

Methods

construct_extended_resources()

convert_resources_to_resource_model()

pod_spec_from_resources()

flytekit.core.resources.ResourceSpec

Parameters

Methods

from_dict()

from_multiple_resource()

to_dict()

flytekit.core.resources.Resources

Parameters

Methods

from_dict()

to_dict()