Skip to main content

ModelRunner

caution

This service is experimental and may change in the future.

Runs machine learning models.

Only models with a single input tensor and a single output tensor are supported at the moment. Input is provided by Sensor Aggregator service on the same device. Multiple instances of this service may be present, if more than one model format is supported by a device.

import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()

Commands​

setModel​

Open pipe for streaming in the model. The size of the model has to be declared upfront. The model is streamed over regular pipe data packets. The format supported by this instance of the service is specified in format register. When the pipe is closed, the model is written all into flash, and the device running the service may reset.

modelRunner.setModel(model_size: number): Promise<void>

Registers​

autoInvokeEvery​

When register contains N > 0, run the model automatically every time new N samples are collected. Model may be run less often if it takes longer to run than N * sampling_interval. The outputs register will stream its value after each run. This register is not stored in flash.

  • type: Register<number> (packing format u16)

  • read and write

import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
const value = await modelRunner.autoInvokeEvery.read()
await modelRunner.autoInvokeEvery.write(value)
  • track incoming values
import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
modelRunner.autoInvokeEvery.subscribe(async (value) => {
    ...
})
note

write and read will block until a server is bound to the client.

reading​

Results of last model invocation as float32 array.

  • type: Register<any[]> (packing format r: f32)

  • track incoming values

import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
modelRunner.reading.subscribe(async (value) => {
    ...
})
note

write and read will block until a server is bound to the client.

inputShape​

The shape of the input tensor.

  • type: Register<any[]> (packing format r: u16)

  • track incoming values

import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
modelRunner.inputShape.subscribe(async (value) => {
    ...
})
note

write and read will block until a server is bound to the client.

outputShape​

The shape of the output tensor.

  • type: Register<any[]> (packing format r: u16)

  • track incoming values

import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
modelRunner.outputShape.subscribe(async (value) => {
    ...
})
note

write and read will block until a server is bound to the client.

lastRunTime​

The time consumed in last model execution.

  • type: Register<number> (packing format u32)

  • read only

import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
const value = await modelRunner.lastRunTime.read()
  • track incoming values
import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
modelRunner.lastRunTime.subscribe(async (value) => {
    ...
})
note

write and read will block until a server is bound to the client.

allocatedArenaSize​

Number of RAM bytes allocated for model execution.

  • type: Register<number> (packing format u32)

  • read only

import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
const value = await modelRunner.allocatedArenaSize.read()
  • track incoming values
import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
modelRunner.allocatedArenaSize.subscribe(async (value) => {
    ...
})
note

write and read will block until a server is bound to the client.

modelSize​

The size of the model in bytes.

  • type: Register<number> (packing format u32)

  • read only

import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
const value = await modelRunner.modelSize.read()
  • track incoming values
import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
modelRunner.modelSize.subscribe(async (value) => {
    ...
})
note

write and read will block until a server is bound to the client.

lastError​

Textual description of last error when running or loading model (if any).

  • type: Register<string> (packing format s)

  • read only

import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
const value = await modelRunner.lastError.read()
  • track incoming values
import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
modelRunner.lastError.subscribe(async (value) => {
    ...
})
note

write and read will block until a server is bound to the client.

format​

The type of ML models supported by this service. TFLite is flatbuffer .tflite file. ML4F is compiled machine code model for Cortex-M4F. The format is typically present as first or second little endian word of model file.

  • type: Register<number> (packing format u32)

  • constant: the register value will not change (until the next reset)

  • read only

import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
const value = await modelRunner.format.read()
note

write and read will block until a server is bound to the client.

formatVersion​

A version number for the format.

  • type: Register<number> (packing format u32)

  • constant: the register value will not change (until the next reset)

  • read only

import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
const value = await modelRunner.formatVersion.read()
note

write and read will block until a server is bound to the client.

parallel​

If present and true this service can run models independently of other instances of this service on the device.

  • type: Register<boolean> (packing format u8)

  • optional: this register may not be implemented

  • constant: the register value will not change (until the next reset)

  • read only

import { ModelRunner } from "@devicescript/core"

const modelRunner = new ModelRunner()
// ...
const value = await modelRunner.parallel.read()
note

write and read will block until a server is bound to the client.