Add new errno for new test cases

Author: zhanheng1

core/iwasm/libraries/wasi-nn/include/wasi_nn_types.h

@@ -48,6 +48,7 @@ typedef enum {
     WASI_NN_ERROR_NAME(unsupported_operation),
     WASI_NN_ERROR_NAME(too_large),
     WASI_NN_ERROR_NAME(not_found),
+    WASI_NN_ERROR_NAME(not_loaded),
 
     // for WasmEdge-wasi-nn
     WASI_NN_ERROR_NAME(end_of_sequence) = 100,  // End of Sequence Found.

core/iwasm/libraries/wasi-nn/src/wasi_nn.c

@@ -688,10 +688,10 @@ wasi_nn_load_by_name(wasm_exec_env_t exec_env, char *name, uint32_t name_len,
             res = too_large;
         }
         else if (model_idx >= global_n_graphs) {
-            NN_ERR_PRINTF("Cannot find model %s, you should pass its path "
+            NN_ERR_PRINTF("Model %s is not loaded, you should pass its path "
                           "through --wasi-nn-graph",
                           nul_terminated_name);
-            res = not_found;
+            res = not_loaded;
         }
         goto fail;
     }

core/iwasm/libraries/wasi-nn/test/test_tensorflow.c

@@ -22,8 +22,10 @@ test_sum()
     float *output =
         run_inference(input.input_tensor, input.dim, &output_size, "sum", 1);
 
-    assert((output_size / sizeof(float)) == 1);
-    assert(fabs(output[0] - 300.0) < EPSILON);
+    if (output) {
+        assert((output_size / sizeof(float)) == 1);
+        assert(fabs(output[0] - 300.0) < EPSILON);
+    }
 
     free(input.dim);
     free(input.input_tensor);
@@ -40,9 +42,11 @@ test_max()
     float *output =
         run_inference(input.input_tensor, input.dim, &output_size, "max", 1);
 
-    assert((output_size / sizeof(float)) == 1);
-    assert(fabs(output[0] - 24.0) < EPSILON);
-    NN_INFO_PRINTF("Result: max is %f", output[0]);
+    if (output) {
+        assert((output_size / sizeof(float)) == 1);
+        assert(fabs(output[0] - 24.0) < EPSILON);
+        NN_INFO_PRINTF("Result: max is %f", output[0]);
+    }
 
     free(input.dim);
     free(input.input_tensor);
@@ -59,9 +63,11 @@ test_average()
     float *output = run_inference(input.input_tensor, input.dim, &output_size,
                                   "average", 1);
 
-    assert((output_size / sizeof(float)) == 1);
-    assert(fabs(output[0] - 12.0) < EPSILON);
-    NN_INFO_PRINTF("Result: average is %f", output[0]);
+    if (output) {
+        assert((output_size / sizeof(float)) == 1);
+        assert(fabs(output[0] - 12.0) < EPSILON);
+        NN_INFO_PRINTF("Result: average is %f", output[0]);
+    }
 
     free(input.dim);
     free(input.input_tensor);
@@ -78,9 +84,11 @@ test_mult_dimensions()
     float *output = run_inference(input.input_tensor, input.dim, &output_size,
                                   "mult_dim", 1);
 
-    assert((output_size / sizeof(float)) == 9);
-    for (int i = 0; i < 9; i++)
-        assert(fabs(output[i] - i) < EPSILON);
+    if (output) {
+        assert((output_size / sizeof(float)) == 9);
+        for (int i = 0; i < 9; i++)
+            assert(fabs(output[i] - i) < EPSILON);
+    }
 
     free(input.dim);
     free(input.input_tensor);
@@ -97,13 +105,15 @@ test_mult_outputs()
     float *output = run_inference(input.input_tensor, input.dim, &output_size,
                                   "mult_out", 2);
 
-    assert((output_size / sizeof(float)) == 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);
+    if (output) {
+        assert((output_size / sizeof(float)) == 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);

core/iwasm/libraries/wasi-nn/test/utils.c

@@ -144,7 +144,15 @@ run_inference(float *input, uint32_t *input_size, uint32_t *output_size,
 {
     WASI_NN_NAME(graph) graph;
 
-    if (wasm_load_by_name(model_name, &graph) != WASI_NN_ERROR_NAME(success)) {
+    WASI_NN_ERROR_TYPE res = wasm_load_by_name(model_name, &graph);
+
+    if (res == WASI_NN_ERROR_NAME(not_loaded)) {
+        NN_INFO_PRINTF("Model %s is not loaded, you should pass its path "
+                       "through --wasi-nn-graph",
+                       model_name);
+        return NULL;
+    }
+    else if (res != WASI_NN_ERROR_NAME(success)) {
         NN_ERR_PRINTF("Error when loading model.");
         exit(1);
     }