fix: Add Android model E2E test (pytorch#19927)

Author: arnavnagzirkar

extension/android/executorch_android/android_test_setup.sh

@@ -39,6 +39,13 @@ prepare_golden() {
   done
 }
 
+prepare_add() {
+  pushd "${BASEDIR}/../../.."
+  "${PYTHON_EXECUTABLE}" -m test.models.export_program --modules "ModuleAdd" --outdir "${BASEDIR}/src/androidTest/resources/"
+  popd
+}
+
 prepare_xor
 prepare_tinyllama
 prepare_golden
+prepare_add

extension/android/executorch_android/src/androidTest/java/org/pytorch/executorch/ModuleE2ETest.kt

@@ -78,4 +78,28 @@ class ModuleE2ETest {
   fun testVitB16() {
     testGoldenModel("vit_b_16", longArrayOf(1, 3, 224, 224))
   }
+
+  @Test
+  fun testAdd() {
+    val x = Tensor.fromBlob(floatArrayOf(1f, 2f, 3f, 4f), longArrayOf(2, 2))
+    val y = Tensor.fromBlob(floatArrayOf(5f, 6f, 7f, 8f), longArrayOf(2, 2))
+
+    val pteFile = File(getTestFilePath("/ModuleAdd.pte"))
+    javaClass.getResourceAsStream("/ModuleAdd.pte")!!.use {
+      FileUtils.copyInputStreamToFile(it, pteFile)
+    }
+
+    val module = Module.load(pteFile.absolutePath)
+    try {
+      // ModuleAdd computes torch.add(x, y, alpha=alpha). The alpha scalar is
+      // passed as a Double because EValue only exposes a Double scalar factory
+      // (TYPE_CODE_DOUBLE); the float32 output dtype is determined by x and y.
+      val results = module.forward(EValue.from(x), EValue.from(y), EValue.from(1.0))
+      assertTrue(results[0].isTensor)
+      val actualOutput = results[0].toTensor().dataAsFloatArray
+      assertOutputsClose(actualOutput, floatArrayOf(6f, 8f, 10f, 12f))
+    } finally {
+      module.destroy()
+    }
+  }
 }

extension/android/executorch_android/src/androidTest/java/org/pytorch/executorch/ModuleInstrumentationTest.kt

@@ -45,7 +45,7 @@ class ModuleInstrumentationTest {
     val module = Module.load(getTestFilePath(TEST_FILE_NAME))
     try {
       val results = module.forward(EValue.from(dummyInput()))
-      Assert.assertTrue(results[0].isTensor)
+      assertSingleTensorResultWithShape(results, expectedOutputShape)
     } finally {
       module.destroy()
     }
@@ -59,7 +59,7 @@ class ModuleInstrumentationTest {
       module.loadMethod(FORWARD_METHOD)
 
       val results = module.forward(EValue.from(dummyInput()))
-      Assert.assertTrue(results[0].isTensor)
+      assertSingleTensorResultWithShape(results, expectedOutputShape)
     } finally {
       module.destroy()
     }
@@ -71,7 +71,7 @@ class ModuleInstrumentationTest {
     val module = Module.load(getTestFilePath(TEST_FILE_NAME))
     try {
       val results = module.execute(FORWARD_METHOD, EValue.from(dummyInput()))
-      Assert.assertTrue(results[0].isTensor)
+      assertSingleTensorResultWithShape(results, expectedOutputShape)
     } finally {
       module.destroy()
     }
@@ -177,7 +177,7 @@ class ModuleInstrumentationTest {
     val module = Module.load(getTestFilePath(TEST_FILE_NAME), Module.LOAD_MODE_MMAP)
     try {
       val results = module.forward(EValue.from(dummyInput()))
-      Assert.assertTrue(results[0].isTensor)
+      assertSingleTensorResultWithShape(results, expectedOutputShape)
     } finally {
       module.destroy()
     }
@@ -189,7 +189,7 @@ class ModuleInstrumentationTest {
     val module = Module.load(getTestFilePath(TEST_FILE_NAME), Module.LOAD_MODE_FILE)
     try {
       val results = module.forward(EValue.from(dummyInput()))
-      Assert.assertTrue(results[0].isTensor)
+      assertSingleTensorResultWithShape(results, expectedOutputShape)
     } finally {
       module.destroy()
     }
@@ -308,7 +308,16 @@ class ModuleInstrumentationTest {
     private const val FORWARD_METHOD = "forward"
     private const val NONE_METHOD = "none"
     private val inputShape = longArrayOf(1, 3, 224, 224)
+    private val expectedOutputShape = longArrayOf(1, 1000)
 
     private fun dummyInput(): Tensor = Tensor.ones(inputShape, DType.FLOAT)
+
+    private fun assertSingleTensorResultWithShape(
+        results: Array<EValue>,
+        expectedShape: LongArray,
+    ) {
+      Assert.assertTrue(results[0].isTensor)
+      Assert.assertArrayEquals(expectedShape, results[0].toTensor().shape())
+    }
   }
 }