1 files changed, 146 insertions, 0 deletions
diff --git a/fluent-bit/lib/wasm-micro-runtime-WAMR-1.2.2/core/iwasm/libraries/wasi-nn/test/test_tensorflow.c b/fluent-bit/lib/wasm-micro-runtime-WAMR-1.2.2/core/iwasm/libraries/wasi-nn/test/test_tensorflow.c
new file mode 100644
index 000000000..2fa516538
--- /dev/null
+++ b/fluent-bit/lib/wasm-micro-runtime-WAMR-1.2.2/core/iwasm/libraries/wasi-nn/test/test_tensorflow.c
@@ -0,0 +1,146 @@
+/*
+ * Copyright (C) 2019 Intel Corporation.  All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+ */
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <assert.h>
+#include <string.h>
+#include <math.h>
+
+#include "utils.h"
+#include "logger.h"
+
+void
+test_sum(execution_target target)
+{
+    int dims[] = { 1, 5, 5, 1 };
+    input_info input = create_input(dims);
+
+    uint32_t output_size = 0;
+    float *output = run_inference(target, input.input_tensor, input.dim,
+                                  &output_size, "/assets/models/sum.tflite", 1);
+
+    assert(output_size == 1);
+    assert(fabs(output[0] - 300.0) < EPSILON);
+
+    free(input.dim);
+    free(input.input_tensor);
+    free(output);
+}
+
+void
+test_max(execution_target target)
+{
+    int dims[] = { 1, 5, 5, 1 };
+    input_info input = create_input(dims);
+
+    uint32_t output_size = 0;
+    float *output = run_inference(target, input.input_tensor, input.dim,
+                                  &output_size, "/assets/models/max.tflite", 1);
+
+    assert(output_size == 1);
+    assert(fabs(output[0] - 24.0) < EPSILON);
+    NN_INFO_PRINTF("Result: max is %f", output[0]);
+
+    free(input.dim);
+    free(input.input_tensor);
+    free(output);
+}
+
+void
+test_average(execution_target target)
+{
+    int dims[] = { 1, 5, 5, 1 };
+    input_info input = create_input(dims);
+
+    uint32_t output_size = 0;
+    float *output =
+        run_inference(target, input.input_tensor, input.dim, &output_size,
+                      "/assets/models/average.tflite", 1);
+
+    assert(output_size == 1);
+    assert(fabs(output[0] - 12.0) < EPSILON);
+    NN_INFO_PRINTF("Result: average is %f", output[0]);
+
+    free(input.dim);
+    free(input.input_tensor);
+    free(output);
+}
+
+void
+test_mult_dimensions(execution_target target)
+{
+    int dims[] = { 1, 3, 3, 1 };
+    input_info input = create_input(dims);
+
+    uint32_t output_size = 0;
+    float *output =
+        run_inference(target, input.input_tensor, input.dim, &output_size,
+                      "/assets/models/mult_dim.tflite", 1);
+
+    assert(output_size == 9);
+    for (int i = 0; i < 9; i++)
+        assert(fabs(output[i] - i) < EPSILON);
+
+    free(input.dim);
+    free(input.input_tensor);
+    free(output);
+}
+
+void
+test_mult_outputs(execution_target target)
+{
+    int dims[] = { 1, 4, 4, 1 };
+    input_info input = create_input(dims);
+
+    uint32_t output_size = 0;
+    float *output =
+        run_inference(target, input.input_tensor, input.dim, &output_size,
+                      "/assets/models/mult_out.tflite", 2);
+
+    assert(output_size == 8);
+    // first tensor check
+    for (int i = 0; i < 4; i++)
+        assert(fabs(output[i] - (i * 4 + 24)) < EPSILON);
+    // second tensor check
+    for (int i = 0; i < 4; i++)
+        assert(fabs(output[i + 4] - (i + 6)) < EPSILON);
+
+    free(input.dim);
+    free(input.input_tensor);
+    free(output);
+}
+
+int
+main()
+{
+    char *env = getenv("TARGET");
+    if (env == NULL) {
+        NN_INFO_PRINTF("Usage:\n--env=\"TARGET=[cpu|gpu]\"");
+        return 1;
+    }
+    execution_target target;
+    if (strcmp(env, "cpu") == 0)
+        target = cpu;
+    else if (strcmp(env, "gpu") == 0)
+        target = gpu;
+    else {
+        NN_ERR_PRINTF("Wrong target!");
+        return 1;
+    }
+    NN_INFO_PRINTF("################### Testing sum...");
+    test_sum(target);
+    NN_INFO_PRINTF("################### Testing max...");
+    test_max(target);
+    NN_INFO_PRINTF("################### Testing average...");
+    test_average(target);
+    NN_INFO_PRINTF("################### Testing multiple dimensions...");
+    test_mult_dimensions(target);
+    NN_INFO_PRINTF("################### Testing multiple outputs...");
+    test_mult_outputs(target);
+
+    NN_INFO_PRINTF("Tests: passed!");
+    return 0;
+}