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Copilot AI commented Jan 28, 2026

Summary

Adds resource specification support for components to enable Ray actor resource allocation and Tuner placement group optimization.

Changes

Core Schema

  • Added Resource Pydantic class in plugboard_schemas.component with fields: cpu, gpu, memory (integer bytes), resources (custom dict)
  • Supports full SI prefix notation:
    • Decimal SI: n, u, m, k, M, G, T, P, E (e.g., "250m" → 0.25, "5k" → 5000)
    • Binary: Ki, Mi, Gi, Ti, Pi, Ei (e.g., "10Mi" → 10,485,760 bytes)
  • Default: cpu=0.001, others zero
  • Implements to_ray_options() for Ray actor configuration
  • Memory stored as integer bytes for precision

Component Integration

  • Extended Component.__init__() with optional resources parameter
  • Updated ComponentArgsDict, ComponentArgsSpec for YAML support
  • Resources auto-exported and reconstructed from configuration

Ray Execution

  • Modified RayProcess._create_component_actor() to apply resource requirements via ray.remote(**ray_options)
  • Falls back to default Resource() when unspecified
  • Import statements organized at top of file

Tuner Optimization

  • Added Tuner._calculate_placement_bundles() to aggregate component resources
  • Creates PlacementGroupFactory with tuner overhead (0.5 CPU) + component bundle
  • Import statements organized at top of file

Documentation

  • Added section in docs/examples/tutorials/running-in-parallel.md referencing resource requirements example
  • Python and YAML examples demonstrating resource specification

Usage Example

from plugboard.schemas import Resource

# Python API
component = MyComponent(
    name="worker",
    resources=Resource(cpu="2.5k", gpu=1, memory="512Mi")
)

# YAML config
resources:
  cpu: "500m"
  gpu: 1
  memory: "100Mi"
  resources:
    custom_accelerator: 2

Tests

  • Unit tests: Resource parsing with all SI prefixes, validation, Ray conversion
  • Integration tests: Component/ProcessSpec/Tuner scenarios
  • Manual verification (full test suite requires Ray dependencies)
Original prompt

This section details on the original issue you should resolve

<issue_title>feat: Implement resource requirements for components</issue_title>
<issue_description>### Summary

Users would like to be able to specify custom resource requirements on Component objects. These can be passed to Ray when a RayProcess is used or a Tuner object is run.

Requirements:

  • Must be able to specify Resource requirements for cpu, gpu, memory, resources. These should be defined as a Pydantic class in plugboard_schemas.
  • Must be able to specify resources as a numerical value, or as a string (to be validated by Pydantic), e.g. 250m for 0.25 or 10Mi for 1024 * 1024 * 10. resources should be a dictionary of string key, numerical value pairs.
  • Must be able to convert these requirements to their Ray equivalents, see https://docs.ray.io/en/latest/ray-core/api/doc/ray.actor.ActorClass.options.html, i.e. cpu = "250m" gets converted to num_cpus=0.25.
  • Must be able to pass a Resource to a Component when instantiating it. This will require changes to the Component and its schema, so that we can specify resource requirements in YAML config.
  • The default requirement should be {"cpu": 0.001}, to be used if the user does not provide anything.
  • Resource requirements should be passed to the actor options in RayProcess.
  • They should be used in the resource placement group inside Tuner.

Example

No response

Alternatives

No response</issue_description>

Comments on the Issue (you are @copilot in this section)


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Copilot AI changed the title [WIP] Add resource requirements for components feat: Implement resource requirements for components Jan 28, 2026
Copilot AI requested a review from toby-coleman January 28, 2026 20:01
"""Parse a resource value from string or number.

Supports:
- Direct numerical values: 1, 0.5, 2.0
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@toby-coleman toby-coleman Jan 28, 2026

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@copilot Can you make this more general? For example by using/supporting any of the following suffixes:

    suffixes = {
        'n': 1e-9, 'u': 1e-6, 'm': 1e-3,  # Decimal SI
        'k': 1e3, 'M': 1e6, 'G': 1e9, 'T': 1e12, 'P': 1e15, 'E': 1e18,
        'Ki': 1024, 'Mi': 1024**2, 'Gi': 1024**3, 'Ti': 1024**4, 'Pi': 1024**5, 'Ei': 1024**6
    }

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Done. Extended to support all decimal SI prefixes (n, u, m, k, M, G, T, P, E) and binary prefixes (Ki, Mi, Gi, Ti, Pi, Ei) in commit 9515154.


cpu: float = 0.001
gpu: float = 0
memory: float = 0
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Memory should be specified as an integer number of bytes

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Done. Changed memory field type to int and added separate validator to cast to integer in commit 9515154.

initial_values: _t.NotRequired[dict[str, _t.Any] | None]
parameters: _t.NotRequired[dict[str, _t.Any] | None]
constraints: _t.NotRequired[dict[str, _t.Any] | None]
resources: _t.NotRequired["Resource | None"]
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Suggested change
resources: _t.NotRequired["Resource | None"]
resources: _t.NotRequired[Resource | None]

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Done in commit 9515154.

).remote(**args)

# Get resource requirements from component
from plugboard.schemas import Resource
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Move this import to the top

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Done. Moved Resource import to top of file in commit 9515154.

Returns:
List of resource bundles for Ray placement group.
"""
from plugboard.schemas import Resource
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Move this import to the top

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Done. Moved Resource import to top of file in commit 9515154.

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feat: Implement resource requirements for components

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