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feat: ExecuTorch bindings for android (#38)
## Description Added TurboModule(ETModule) which let's user use ExecuTorch Module methods such as: - loadMethod - loadModule - loadForward - forward ### Type of change - [ ] Bug fix (non-breaking change which fixes an issue) - [x] New feature (non-breaking change which adds functionality) - [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected) - [ ] Documentation update (improves or adds clarity to existing documentation) ### Tested on - [ ] iOS - [x] Android ### Testing instructions <!-- Provide step-by-step instructions on how to test your changes. Include setup details if necessary. --> ### Screenshots <!-- Add screenshots here, if applicable --> ### Related issues <!-- Link related issues here using #issue-number --> ### Checklist - [x] I have performed a self-review of my code - [x] I have commented my code, particularly in hard-to-understand areas - [ ] I have updated the documentation accordingly - [x] My changes generate no new warnings ### Additional notes <!-- Include any additional information, assumptions, or context that reviewers might need to understand this PR. -->
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android/src/main/java/com/swmansion/rnexecutorch/ETModule.kt
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| @@ -0,0 +1,97 @@ | ||
| package com.swmansion.rnexecutorch | ||
|
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| import com.facebook.react.bridge.Promise | ||
| import com.facebook.react.bridge.ReactApplicationContext | ||
| import com.facebook.react.bridge.ReadableArray | ||
| import com.swmansion.rnexecutorch.utils.ArrayUtils | ||
| import com.swmansion.rnexecutorch.utils.Fetcher | ||
| import com.swmansion.rnexecutorch.utils.ProgressResponseBody | ||
| import com.swmansion.rnexecutorch.utils.ResourceType | ||
| import com.swmansion.rnexecutorch.utils.TensorUtils | ||
| import okhttp3.OkHttpClient | ||
| import org.pytorch.executorch.Module | ||
| import org.pytorch.executorch.Tensor | ||
| import java.net.URL | ||
|
|
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| class ETModule(reactContext: ReactApplicationContext) : NativeETModuleSpec(reactContext) { | ||
| private lateinit var module: Module | ||
| private val client = OkHttpClient() | ||
|
|
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| override fun getName(): String { | ||
| return NAME | ||
| } | ||
|
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| private fun downloadModel( | ||
| url: URL, resourceType: ResourceType, callback: (path: String?, error: Exception?) -> Unit | ||
| ) { | ||
| Fetcher.downloadResource(reactApplicationContext, | ||
| client, | ||
| url, | ||
| resourceType, | ||
| { path, error -> callback(path, error) }, | ||
| object : ProgressResponseBody.ProgressListener { | ||
| override fun onProgress(bytesRead: Long, contentLength: Long, done: Boolean) { | ||
| } | ||
| }) | ||
| } | ||
|
|
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| override fun loadModule(modelPath: String, promise: Promise) { | ||
| try { | ||
| downloadModel( | ||
| URL(modelPath), ResourceType.MODEL | ||
| ) { path, error -> | ||
| if (error != null) { | ||
| promise.reject(error.message!!, "-1") | ||
| return@downloadModel | ||
| } | ||
|
|
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| module = Module.load(path) | ||
| promise.resolve(0) | ||
| return@downloadModel | ||
| } | ||
| } catch (e: Exception) { | ||
| promise.reject(e.message!!, "-1") | ||
| } | ||
| } | ||
|
|
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| override fun loadMethod(methodName: String, promise: Promise) { | ||
| val result = module.loadMethod(methodName) | ||
| if (result != 0) { | ||
| promise.reject("Method loading failed", result.toString()) | ||
| return | ||
| } | ||
|
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| promise.resolve(result) | ||
| } | ||
|
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| override fun forward( | ||
| input: ReadableArray, | ||
| shape: ReadableArray, | ||
| inputType: Double, | ||
| promise: Promise | ||
| ) { | ||
| try { | ||
| val executorchInput = | ||
| TensorUtils.getExecutorchInput(input, ArrayUtils.createLongArray(shape), inputType.toInt()) | ||
|
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| lateinit var result: Tensor | ||
| module.forward(executorchInput)[0].toTensor().also { result = it } | ||
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| promise.resolve(ArrayUtils.createReadableArray(result)) | ||
| return | ||
| } catch (e: IllegalArgumentException) { | ||
| //The error is thrown when transformation to Tensor fails | ||
| promise.reject("Forward Failed Execution", "18") | ||
| return | ||
| } catch (e: Exception) { | ||
| //Executorch forward method throws an exception with a message: "Method forward failed with code XX" | ||
| val exceptionCode = e.message!!.substring(e.message!!.length - 2) | ||
| promise.reject("Forward Failed Execution", exceptionCode) | ||
| return | ||
| } | ||
| } | ||
|
|
||
| companion object { | ||
| const val NAME = "ETModule" | ||
| } | ||
| } |
14 changes: 8 additions & 6 deletions
14
android/src/main/java/com/swmansion/rnexecutorch/RnExecutorchModule.kt
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96 changes: 96 additions & 0 deletions
96
android/src/main/java/com/swmansion/rnexecutorch/utils/ArrayUtils.kt
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,96 @@ | ||
| package com.swmansion.rnexecutorch.utils | ||
|
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| import com.facebook.react.bridge.Arguments | ||
| import com.facebook.react.bridge.ReadableArray | ||
| import org.pytorch.executorch.DType | ||
| import org.pytorch.executorch.Tensor | ||
|
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| class ArrayUtils { | ||
| companion object { | ||
| fun createByteArray(input: ReadableArray): ByteArray { | ||
| val byteArray = ByteArray(input.size()) | ||
| for (i in 0 until input.size()) { | ||
| byteArray[i] = input.getInt(i).toByte() | ||
| } | ||
| return byteArray | ||
| } | ||
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| fun createIntArray(input: ReadableArray): IntArray { | ||
| val intArray = IntArray(input.size()) | ||
| for (i in 0 until input.size()) { | ||
| intArray[i] = input.getInt(i) | ||
| } | ||
| return intArray | ||
| } | ||
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| fun createFloatArray(input: ReadableArray): FloatArray { | ||
| val floatArray = FloatArray(input.size()) | ||
| for (i in 0 until input.size()) { | ||
| floatArray[i] = input.getDouble(i).toFloat() | ||
| } | ||
| return floatArray | ||
| } | ||
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| fun createLongArray(input: ReadableArray): LongArray { | ||
| val longArray = LongArray(input.size()) | ||
| for (i in 0 until input.size()) { | ||
| longArray[i] = input.getInt(i).toLong() | ||
| } | ||
| return longArray | ||
| } | ||
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| fun createDoubleArray(input: ReadableArray): DoubleArray { | ||
| val doubleArray = DoubleArray(input.size()) | ||
| for (i in 0 until input.size()) { | ||
| doubleArray[i] = input.getDouble(i) | ||
| } | ||
| return doubleArray | ||
| } | ||
|
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| fun createReadableArray(result: Tensor): ReadableArray { | ||
| val resultArray = Arguments.createArray() | ||
| when (result.dtype()) { | ||
| DType.UINT8 -> { | ||
| val byteArray = result.dataAsByteArray | ||
| for (i in byteArray) { | ||
| resultArray.pushInt(i.toInt()) | ||
| } | ||
| } | ||
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| DType.INT32 -> { | ||
| val intArray = result.dataAsIntArray | ||
| for (i in intArray) { | ||
| resultArray.pushInt(i) | ||
| } | ||
| } | ||
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| DType.FLOAT -> { | ||
| val longArray = result.dataAsFloatArray | ||
| for (i in longArray) { | ||
| resultArray.pushDouble(i.toDouble()) | ||
| } | ||
| } | ||
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| DType.DOUBLE -> { | ||
| val floatArray = result.dataAsDoubleArray | ||
| for (i in floatArray) { | ||
| resultArray.pushDouble(i) | ||
| } | ||
| } | ||
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| DType.INT64 -> { | ||
| val doubleArray = result.dataAsLongArray | ||
| for (i in doubleArray) { | ||
| resultArray.pushLong(i) | ||
| } | ||
| } | ||
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| else -> { | ||
| throw IllegalArgumentException("Invalid dtype: ${result.dtype()}") | ||
| } | ||
| } | ||
|
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| return resultArray | ||
| } | ||
| } | ||
| } |
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2 changes: 1 addition & 1 deletion
2
...sion/rnexecutorch/ProgressResponseBody.kt → ...nexecutorch/utils/ProgressResponseBody.kt
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46 changes: 46 additions & 0 deletions
46
android/src/main/java/com/swmansion/rnexecutorch/utils/TensorUtils.kt
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,46 @@ | ||
| package com.swmansion.rnexecutorch.utils | ||
|
|
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| import com.facebook.react.bridge.ReadableArray | ||
| import org.pytorch.executorch.EValue | ||
| import org.pytorch.executorch.Tensor | ||
|
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| class TensorUtils { | ||
| companion object { | ||
| fun getExecutorchInput(input: ReadableArray, shape: LongArray, type: Int): EValue { | ||
| try { | ||
| when (type) { | ||
| 0 -> { | ||
| val inputTensor = Tensor.fromBlob(ArrayUtils.createByteArray(input), shape) | ||
| return EValue.from(inputTensor) | ||
| } | ||
|
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| 1 -> { | ||
| val inputTensor = Tensor.fromBlob(ArrayUtils.createIntArray(input), shape) | ||
| return EValue.from(inputTensor) | ||
| } | ||
|
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| 2 -> { | ||
| val inputTensor = Tensor.fromBlob(ArrayUtils.createLongArray(input), shape) | ||
| return EValue.from(inputTensor) | ||
| } | ||
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| 3 -> { | ||
| val inputTensor = Tensor.fromBlob(ArrayUtils.createFloatArray(input), shape) | ||
| return EValue.from(inputTensor) | ||
| } | ||
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| 4 -> { | ||
| val inputTensor = Tensor.fromBlob(ArrayUtils.createDoubleArray(input), shape) | ||
| return EValue.from(inputTensor) | ||
| } | ||
|
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| else -> { | ||
| throw IllegalArgumentException("Invalid input type: $type") | ||
| } | ||
| } | ||
| } catch (e: IllegalArgumentException) { | ||
| throw e | ||
| } | ||
| } | ||
| } | ||
| } |
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