Add operator test explanation 16744226553558370377

explain.txt

@@ -0,0 +1,65 @@
+The unit test for the `add.cc` operator is located in `tensorflow/lite/micro/kernels/add_test.cc`. This file contains several test cases to ensure the correctness of the Add operator for different data types, shapes, and activation functions.
+
+Here is a summary of the tests covered:
+
+1.  **FloatAddNoActivation**:
+    -   Tests floating-point addition.
+    -   Inputs are 4D tensors with shape {1, 2, 2, 1}.
+    -   No activation function is applied.
+
+2.  **FloatAddActivationRelu1**:
+    -   Tests floating-point addition with ReLU1 activation.
+    -   The output is clamped between -1 and 1.
+
+3.  **FloatAddActivationRelu**:
+    -   Tests floating-point addition with ReLU activation.
+    -   The output is clamped to be non-negative (>= 0).
+
+4.  **FloatAddVariousInputShapes**:
+    -   Tests floating-point addition with various input shapes.
+    -   It iterates through a set of predefined shapes (1D, 2D, 3D, 4D) to ensure the operator handles different dimensions correctly.
+
+5.  **FloatAddWithScalarBroadcast**:
+    -   Tests floating-point addition where one input is a scalar.
+    -   This verifies the broadcasting capability where a scalar value is added to every element of a tensor.
+
+6.  **Int32AddNoActivation**:
+    -   Tests 32-bit integer addition.
+    -   It checks for correct handling of large integer values and potential overflows/underflows (though standard add behavior is expected).
+
+7.  **QuantizedAddNoActivationInt8**:
+    -   Tests 8-bit quantized integer addition.
+    -   It involves quantization parameters (scales and zero points) for inputs and output.
+    -   No activation function.
+
+8.  **QuantizedAddActivationRelu1Int8**:
+    -   Tests 8-bit quantized integer addition with ReLU1 activation.
+    -   Verifies that the quantized output is correctly clamped.
+
+9.  **QuantizedAddVariousInputShapesInt8**:
+    -   Tests 8-bit quantized integer addition across various input shapes, similar to the float version.
+
+10. **QuantizedAddWithScalarBroadcastFloat**:
+    -   Despite the name, this test appears to verify broadcasting logic using float values against golden results that are used for broadcast tests. It calls `TestAddFloat`. It iterates through complex broadcast shapes.
+
+11. **QuantizedAddWithScalarBroadcastInt8**:
+    -   Tests 8-bit quantized integer addition with scalar broadcasting.
+
+12. **QuantizedAddWithMixedBroadcastInt8**:
+    -   Tests 8-bit quantized integer addition with mixed broadcasting (where inputs have different shapes but are broadcast-compatible).
+
+13. **QuantizedAddNoActivationInt16**:
+    -   Tests 16-bit quantized integer addition.
+    -   Similar to Int8 tests but with `int16_t` data type.
+
+14. **QuantizedAddActivationRelu1Int16**:
+    -   Tests 16-bit quantized integer addition with ReLU1 activation.
+
+15. **QuantizedAddVariousInputShapesInt16**:
+    -   Tests 16-bit quantized integer addition with various input shapes.
+
+16. **QuantizedAddWithScalarBroadcastInt16**:
+    -   Tests 16-bit quantized integer addition with scalar broadcasting.
+
+17. **QuantizedAddWithMixedBroadcastInt16**:
+    -   Tests 16-bit quantized integer addition with mixed broadcasting.

golden_data_calculation.txt

@@ -0,0 +1,36 @@
+Explanation of Golden Data Calculation for FloatAddActivationRelu
+
+The `FloatAddActivationRelu` test case verifies the addition operator with a ReLU activation function.
+The expected "golden" values were calculated manually based on the mathematical definition of the operation.
+
+**Operation:**
+Output = ReLU(Input1 + Input2)
+ReLU(x) = max(0, x)
+
+**Inputs:**
+Input 1: {-2.0, 0.2, 0.7, 0.8}
+Input 2: { 0.1, 0.2, 0.3, 0.5}
+
+**Step-by-Step Calculation:**
+
+1.  **Index 0:**
+    *   Addition: -2.0 + 0.1 = -1.9
+    *   Activation: max(0, -1.9) = 0.0
+
+2.  **Index 1:**
+    *   Addition: 0.2 + 0.2 = 0.4
+    *   Activation: max(0, 0.4) = 0.4
+
+3.  **Index 2:**
+    *   Addition: 0.7 + 0.3 = 1.0
+    *   Activation: max(0, 1.0) = 1.0
+
+4.  **Index 3:**
+    *   Addition: 0.8 + 0.5 = 1.3
+    *   Activation: max(0, 1.3) = 1.3
+
+**Resulting Golden Values:**
+{0.0, 0.4, 1.0, 1.3}
+
+These are the values used in the test case:
+`const float golden_values[] = {0.0, 0.4, 1.0, 1.3};`

result/result_add.txt

@@ -0,0 +1,18 @@
+Testing FloatAddNoActivation
+Testing FloatAddActivationRelu1
+Testing FloatAddVariousInputShapes
+Testing FloatAddWithScalarBroadcast
+Testing Int32AddNoActivation
+Testing QuantizedAddNoActivationInt8
+Testing QuantizedAddActivationRelu1Int8
+Testing QuantizedAddVariousInputShapesInt8
+Testing QuantizedAddWithScalarBroadcastFloat
+Testing QuantizedAddWithScalarBroadcastInt8
+Testing QuantizedAddWithMixedBroadcastInt8
+Testing QuantizedAddNoActivationInt16
+Testing QuantizedAddActivationRelu1Int16
+Testing QuantizedAddVariousInputShapesInt16
+Testing QuantizedAddWithScalarBroadcastInt16
+Testing QuantizedAddWithMixedBroadcastInt16
+16/16 tests passed
+~~~ALL TESTS PASSED~~~

result/result_add_1.txt

@@ -0,0 +1,19 @@
+Testing FloatAddNoActivation
+Testing FloatAddActivationRelu1
+Testing FloatAddActivationRelu
+Testing FloatAddVariousInputShapes
+Testing FloatAddWithScalarBroadcast
+Testing Int32AddNoActivation
+Testing QuantizedAddNoActivationInt8
+Testing QuantizedAddActivationRelu1Int8
+Testing QuantizedAddVariousInputShapesInt8
+Testing QuantizedAddWithScalarBroadcastFloat
+Testing QuantizedAddWithScalarBroadcastInt8
+Testing QuantizedAddWithMixedBroadcastInt8
+Testing QuantizedAddNoActivationInt16
+Testing QuantizedAddActivationRelu1Int16
+Testing QuantizedAddVariousInputShapesInt16
+Testing QuantizedAddWithScalarBroadcastInt16
+Testing QuantizedAddWithMixedBroadcastInt16
+17/17 tests passed
+~~~ALL TESTS PASSED~~~

result/result_add_1_01.txt

@@ -0,0 +1,19 @@
+Testing FloatAddNoActivation
+Testing FloatAddActivationRelu1
+Testing FloatAddActivationRelu
+Testing FloatAddVariousInputShapes
+Testing FloatAddWithScalarBroadcast
+Testing Int32AddNoActivation
+Testing QuantizedAddNoActivationInt8
+Testing QuantizedAddActivationRelu1Int8
+Testing QuantizedAddVariousInputShapesInt8
+Testing QuantizedAddWithScalarBroadcastFloat
+Testing QuantizedAddWithScalarBroadcastInt8
+Testing QuantizedAddWithMixedBroadcastInt8
+Testing QuantizedAddNoActivationInt16
+Testing QuantizedAddActivationRelu1Int16
+Testing QuantizedAddVariousInputShapesInt16
+Testing QuantizedAddWithScalarBroadcastInt16
+Testing QuantizedAddWithMixedBroadcastInt16
+17/17 tests passed
+~~~ALL TESTS PASSED~~~

tensorflow/lite/micro/kernels/add_test.cc

@@ -192,6 +192,19 @@ TF_LITE_MICRO_TEST(FloatAddActivationRelu1) {
                                 kTfLiteActReluN1To1, output_data);
 }
 
+TF_LITE_MICRO_TEST(FloatAddActivationRelu) {
+  int inout_shape[] = {4, 1, 2, 2, 1};
+  const float input1_values[] = {-2.0, 0.2, 0.7, 0.8};
+  const float input2_values[] = {0.1, 0.2, 0.3, 0.5};
+  const float golden_values[] = {0.0, 0.4, 1.0, 1.3};
+
+  constexpr int kOutputDimsCount = 4;
+  float output_data[kOutputDimsCount];
+  tflite::testing::TestAddFloat(inout_shape, input1_values, inout_shape,
+                                input2_values, inout_shape, golden_values,
+                                kTfLiteActRelu, output_data);
+}
+
 TF_LITE_MICRO_TEST(FloatAddVariousInputShapes) {
   constexpr int kOutputDimsCount = 6;
   float output_data[kOutputDimsCount];