restructure config to use Device class directly

Also include device validation

README.md

@@ -67,7 +67,8 @@ sagemaker:
     hyperparameters: {}
 
 aihub:
-  device: Samsung Galaxy S25 (Family)
+  device:
+    name: Samsung Galaxy S25 (Family)
   target_runtime: tflite
   input_specs: {}           # Required before running qc-cli ai-hub commands
   job_name: null            # Optional prefix for AI Hub Workbench jobs

examples/ai-hub/README.md

@@ -28,7 +28,8 @@ Your `config.yaml` must include AI Hub settings:
 
 ```yaml
 aihub:
-  device: Samsung Galaxy S25 (Family)
+  device:
+    name: Samsung Galaxy S25 (Family)
   target_runtime: tflite
   input_specs:
     input: [[1, 3, 160, 160], float32]

src/commands/ai_hub.py

@@ -4,7 +4,9 @@ from enum import StrEnum
 from pathlib import Path
 from typing import Any
 
+import qai_hub.hub as hub
 import typer
+from qai_hub.client import Device
 
 from src import state as state_ops
 from src.commands.utils import CONFIG_OPT, CONSOLE, load_cfg
@@ -99,6 +101,33 @@ def _model_id_or_state(config_path: str, model_id: str | None, *, quantized: boo
     return resolved
 
 
+def _device_selector(device: Device) -> str:
+    parts: list[str] = []
+    if device.name:
+        parts.append(f"name={device.name!r}")
+    if device.os:
+        parts.append(f"os={device.os!r}")
+    if device.attributes:
+        parts.append(f"attributes={device.attributes!r}")
+    return ", ".join(parts) if parts else "empty selector"
+
+
+def _validate_device(cfg: Config) -> None:
+    device = cfg.aihub.device
+    try:
+        matches = hub.get_devices(name=device.name, os=device.os, attributes=device.attributes)
+    except Exception as e:
+        CONSOLE.print(f"[red]Unable to validate AI Hub device {_device_selector(device)}: {e}[/red]")
+        raise typer.Exit(1)
+
+    if matches:
+        return
+
+    CONSOLE.print(f"[red]AI Hub device not found: {_device_selector(device)}[/red]")
+    CONSOLE.print("Run [bold]qai-hub list-devices[/bold] to see valid device names.")
+    raise typer.Exit(1)
+
+
 def _quantize_step(
     cfg: Config,
     config_path: str,
@@ -156,6 +185,7 @@ def _compile_step(
     prefer_quantized: bool,
 ) -> str:
     st = state_ops.store(config_path)
+    _validate_device(cfg)
     specs = _input_specs(cfg)
 
     model: Any
@@ -184,7 +214,7 @@ def _compile_step(
     try:
         result = aihub_jobs.submit_compile_job(
             model=model,
-            device_name=cfg.aihub.device,
+            device=cfg.aihub.device,
             input_specs=specs,
             target_runtime=cfg.aihub.target_runtime,
             options=cfg.aihub.compile_options,
@@ -214,6 +244,7 @@ def _validate_step(
     model_id: str | None,
     input_name: str | None,
 ) -> str:
+    _validate_device(cfg)
     specs = _input_specs(cfg)
     resolved_model_id = _model_id_or_state(config_path, model_id)
     try:
@@ -247,6 +278,7 @@ def _validate_step(
 
 
 def _profile_step(cfg: Config, config_path: str, model_id: str | None) -> str:
+    _validate_device(cfg)
     resolved_model_id = _model_id_or_state(config_path, model_id)
     try:
         result = aihub_jobs.submit_profile_job(

src/config.py

@@ -4,7 +4,8 @@ from typing import Any, Literal, TypedDict
 
 from mypy_boto3_s3.literals import BucketLocationConstraintType
 from mypy_boto3_sagemaker.literals import TrainingInstanceTypeType
-from pydantic import BaseModel, Field, model_validator
+from pydantic import BaseModel, Field, field_validator, model_validator
+from qai_hub.client import Device
 
 
 class MlflowMode(StrEnum):
@@ -81,7 +82,7 @@ class SageMakerConfig(BaseModel):
 
 
 class AIHubConfig(BaseModel):
-    device: str = "Samsung Galaxy S25 (Family)"
+    device: Device = Field(default_factory=lambda: Device("Samsung Galaxy S25 (Family)"))
     target_runtime: str = "tflite"
     input_specs: dict[str, tuple[list[int], str]] = Field(default_factory=dict)
     job_name: str | None = None
@@ -91,6 +92,13 @@ class AIHubConfig(BaseModel):
     quantize_options: str | None = None
     output_dir: str = "build/qai-hub"
 
+    @field_validator("device", mode="before")
+    @classmethod
+    def parse_device(cls, value: Any) -> Any:
+        if isinstance(value, str):
+            return Device(value)
+        return value
+
 
 class MlflowConfig(BaseModel):
     mode: MlflowMode = MlflowMode.disabled

src/qualcomm/aihub_jobs.py

@@ -29,7 +29,7 @@ def _dataset_entries(inputs: dict[str, Any]) -> dict[str, list[Any]]:
 
 def submit_compile_job(
     model: Any,
-    device_name: str,
+    device: Device,
     input_specs: dict[str, tuple[tuple[int, ...], str]],
     target_runtime: str,
     options: str | None = None,
@@ -52,7 +52,7 @@ def submit_compile_job(
 
     job = hub.submit_compile_job(
         model=model_arg,
-        device=Device(device_name),
+        device=device,
         name=job_name,
         input_specs=input_specs,
         options=compile_options,
@@ -65,14 +65,14 @@ def submit_compile_job(
 
 def submit_inference_job(
     model_id: str,
-    device_name: str,
+    device: Device,
     inputs: dict[str, Any],
     output_dir: str | Path,
     job_name: str | None = None,
 ) -> InferenceJobResult:
     job = hub.submit_inference_job(
         model=hub.get_model(model_id),
-        device=Device(device_name),
+        device=device,
         inputs=_dataset_entries(inputs),
         name=job_name,
     )
@@ -84,13 +84,13 @@ def submit_inference_job(
 
 def submit_profile_job(
     model_id: str,
-    device_name: str,
+    device: Device,
     options: str | None = None,
     job_name: str | None = None,
 ) -> ProfileJobResult:
     job = hub.submit_profile_job(
         model=hub.get_model(model_id),
-        device=Device(device_name),
+        device=device,
         name=job_name,
         options=options or "",
     )