Keep the legacy test apis for now. Maybe it is not a proper time to o support both of legacy and ephemeral apis.

core/iwasm/libraries/wasi-nn/test/build.sh

@@ -22,8 +22,6 @@ CURR_PATH=$(cd $(dirname $0) && pwd -P)
 
 /opt/wasi-sdk/bin/clang \
     --target=wasm32-wasi \
-    -DWASM_ENABLE_WASI_NN=1 \
-    -DWASM_ENABLE_WASI_EPHEMERAL_NN=1 \
     -DNN_LOG_LEVEL=1 \
     -Wl,--allow-undefined \
     -I../include -I../src/utils \
@@ -44,8 +42,6 @@ python3 sum.py
 cd ${CURR_PATH}
 /opt/wasi-sdk/bin/clang \
     --target=wasm32-wasi \
-    -DWASM_ENABLE_WASI_NN=1 \
-    -DWASM_ENABLE_WASI_EPHEMERAL_NN=1 \
     -DNN_LOG_LEVEL=1 \
     -Wl,--allow-undefined \
     -I../include -I../src/utils \

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

@@ -5,16 +5,17 @@
 
 #include "utils.h"
 #include "logger.h"
+#include "wasi_nn.h"
+
 #include <stdio.h>
 #include <stdlib.h>
 
-wasi_ephemeral_nn_error
-wasm_load(char *model_name, wasi_ephemeral_nn_graph *g,
-          wasi_ephemeral_nn_execution_target target)
+wasi_nn_error
+wasm_load(char *model_name, graph *g, execution_target target)
 {
     FILE *pFile = fopen(model_name, "r");
     if (pFile == NULL)
-        return wasi_ephemeral_nn_error_invalid_argument;
+        return invalid_argument;
 
     uint8_t *buffer;
     size_t result;
@@ -23,23 +24,30 @@ wasm_load(char *model_name, wasi_ephemeral_nn_graph *g,
     buffer = (uint8_t *)malloc(sizeof(uint8_t) * MAX_MODEL_SIZE);
     if (buffer == NULL) {
         fclose(pFile);
-        return wasi_ephemeral_nn_error_too_large;
+        return too_large;
     }
 
     result = fread(buffer, 1, MAX_MODEL_SIZE, pFile);
     if (result <= 0) {
         fclose(pFile);
         free(buffer);
-        return wasi_ephemeral_nn_error_too_large;
+        return too_large;
     }
 
-    wasi_ephemeral_nn_graph_builder arr;
+    graph_builder_array arr;
 
-    arr.buf = buffer;
-    arr.size = result;
+    arr.size = 1;
+    arr.buf = (graph_builder *)malloc(sizeof(graph_builder));
+    if (arr.buf == NULL) {
+        fclose(pFile);
+        free(buffer);
+        return too_large;
+    }
 
-    wasi_ephemeral_nn_error res = wasi_ephemeral_nn_load(
-        &arr, result, wasi_ephemeral_nn_encoding_tensorflowlite, target, g);
+    arr.buf[0].size = result;
+    arr.buf[0].buf = buffer;
+
+    wasi_nn_error res = load(&arr, tensorflowlite, target, g);
 
     fclose(pFile);
     free(buffer);
@@ -47,98 +55,77 @@ wasm_load(char *model_name, wasi_ephemeral_nn_graph *g,
     return res;
 }
 
-wasi_ephemeral_nn_error
-wasm_load_by_name(const char *model_name, wasi_ephemeral_nn_graph *g)
+wasi_nn_error
+wasm_load_by_name(const char *model_name, graph *g)
 {
-    wasi_ephemeral_nn_error res =
-        wasi_ephemeral_nn_load_by_name(model_name, strlen(model_name), g);
+    wasi_nn_error res = load_by_name(model_name, strlen(model_name), g);
     return res;
 }
 
-wasi_ephemeral_nn_error
-wasm_init_execution_context(wasi_ephemeral_nn_graph g,
-                            wasi_ephemeral_nn_graph_execution_context *ctx)
+wasi_nn_error
+wasm_init_execution_context(graph g, graph_execution_context *ctx)
 {
-    return wasi_ephemeral_nn_init_execution_context(g, ctx);
+    return init_execution_context(g, ctx);
 }
 
-wasi_ephemeral_nn_error
-wasm_set_input(wasi_ephemeral_nn_graph_execution_context ctx,
-               float *input_tensor, uint32_t *dim)
+wasi_nn_error
+wasm_set_input(graph_execution_context ctx, float *input_tensor, uint32_t *dim)
 {
-    wasi_ephemeral_nn_tensor_dimensions dims;
+    tensor_dimensions dims;
     dims.size = INPUT_TENSOR_DIMS;
     dims.buf = (uint32_t *)malloc(dims.size * sizeof(uint32_t));
     if (dims.buf == NULL)
-        return wasi_ephemeral_nn_error_too_large;
+        return too_large;
 
-    wasi_ephemeral_nn_tensor tensor;
-    tensor.dimensions = dims;
-    for (int i = 0; i < tensor.dimensions.size; ++i)
-        tensor.dimensions.buf[i] = dim[i];
-    tensor.type = wasi_ephemeral_nn_type_fp32;
-    tensor.data.buf = (uint8_t *)input_tensor;
-
-    uint32_t tmp_size = 1;
-    if (dim)
-        for (int i = 0; i < INPUT_TENSOR_DIMS; ++i)
-            tmp_size *= dim[i];
-
-    tensor.data.size = (tmp_size * sizeof(float));
-
-    wasi_ephemeral_nn_error err = wasi_ephemeral_nn_set_input(ctx, 0, &tensor);
+    tensor tensor;
+    tensor.dimensions = &dims;
+    for (int i = 0; i < tensor.dimensions->size; ++i)
+        tensor.dimensions->buf[i] = dim[i];
+    tensor.type = fp32;
+    tensor.data = (uint8_t *)input_tensor;
+    wasi_nn_error err = set_input(ctx, 0, &tensor);
 
     free(dims.buf);
     return err;
 }
 
-wasi_ephemeral_nn_error
-wasm_compute(wasi_ephemeral_nn_graph_execution_context ctx)
+wasi_nn_error
+wasm_compute(graph_execution_context ctx)
 {
-    return wasi_ephemeral_nn_compute(ctx);
+    return compute(ctx);
 }
 
-wasi_ephemeral_nn_error
-wasm_get_output(wasi_ephemeral_nn_graph_execution_context ctx, uint32_t index,
-                float *out_tensor, uint32_t *out_size)
+wasi_nn_error
+wasm_get_output(graph_execution_context ctx, uint32_t index, float *out_tensor,
+                uint32_t *out_size)
 {
-    return wasi_ephemeral_nn_get_output(ctx, index, (uint8_t *)out_tensor,
-                                        MAX_OUTPUT_TENSOR_SIZE, out_size);
+    return get_output(ctx, index, (uint8_t *)out_tensor, out_size);
 }
 
 float *
-run_inference(float *input, uint32_t *input_size, uint32_t *output_size,
-              char *model_name, uint32_t num_output_tensors)
+run_inference(float *input, uint32_t *input_size,
+              uint32_t *output_size, char *model_name,
+              uint32_t num_output_tensors)
 {
-    wasi_ephemeral_nn_graph graph;
+    graph graph;
 
-    wasi_ephemeral_nn_error res = wasm_load_by_name(model_name, &graph);
-
-    if (res == wasi_ephemeral_nn_error_not_found) {
-        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_ephemeral_nn_error_success) {
+    if (wasm_load_by_name(model_name, &graph) != success) {
         NN_ERR_PRINTF("Error when loading model.");
         exit(1);
     }
 
-    wasi_ephemeral_nn_graph_execution_context ctx;
-    if (wasm_init_execution_context(graph, &ctx)
-        != wasi_ephemeral_nn_error_success) {
+    graph_execution_context ctx;
+    if (wasm_init_execution_context(graph, &ctx) != success) {
         NN_ERR_PRINTF("Error when initialixing execution context.");
         exit(1);
     }
 
-    if (wasm_set_input(ctx, input, input_size)
-        != wasi_ephemeral_nn_error_success) {
+    if (wasm_set_input(ctx, input, input_size) != success) {
         NN_ERR_PRINTF("Error when setting input tensor.");
         exit(1);
     }
 
-    if (wasm_compute(ctx) != wasi_ephemeral_nn_error_success) {
+    if (wasm_compute(ctx) != success) {
         NN_ERR_PRINTF("Error when running inference.");
         exit(1);
     }
@@ -153,7 +140,7 @@ run_inference(float *input, uint32_t *input_size, uint32_t *output_size,
     for (int i = 0; i < num_output_tensors; ++i) {
         *output_size = MAX_OUTPUT_TENSOR_SIZE - *output_size;
         if (wasm_get_output(ctx, i, &out_tensor[offset], output_size)
-            != wasi_ephemeral_nn_error_success) {
+            != success) {
             NN_ERR_PRINTF("Error when getting index %d.", i);
             break;
         }

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

@@ -8,11 +8,6 @@
 
 #include <stdint.h>
 
-#if WASM_ENABLE_WASI_EPHEMERAL_NN != 0
-#include "wasi_ephemeral_nn.h"
-#elif WASM_ENABLE_WASI_NN != 0
-#include "wasi_nn.h"
-#endif
 #include "wasi_nn_types.h"
 
 #define MAX_MODEL_SIZE 85000000
@@ -28,30 +23,28 @@ typedef struct {
 
 /* wasi-nn wrappers */
 
-wasi_ephemeral_nn_error
-wasm_load(char *model_name, wasi_ephemeral_nn_graph *g,
-          wasi_ephemeral_nn_execution_target target);
+wasi_nn_error
+wasm_load(char *model_name, graph *g, execution_target target);
 
-wasi_ephemeral_nn_error
-wasm_init_execution_context(wasi_ephemeral_nn_graph g,
-                            wasi_ephemeral_nn_graph_execution_context *ctx);
+wasi_nn_error
+wasm_init_execution_context(graph g, graph_execution_context *ctx);
 
-wasi_ephemeral_nn_error
-wasm_set_input(wasi_ephemeral_nn_graph_execution_context ctx,
-               float *input_tensor, uint32_t *dim);
+wasi_nn_error
+wasm_set_input(graph_execution_context ctx, float *input_tensor, uint32_t *dim);
 
-wasi_ephemeral_nn_error
-wasm_compute(wasi_ephemeral_nn_graph_execution_context ctx);
+wasi_nn_error
+wasm_compute(graph_execution_context ctx);
 
-wasi_ephemeral_nn_error
-wasm_get_output(wasi_ephemeral_nn_graph_execution_context ctx, uint32_t index,
-                float *out_tensor, uint32_t *out_size);
+wasi_nn_error
+wasm_get_output(graph_execution_context ctx, uint32_t index, float *out_tensor,
+                uint32_t *out_size);
 
 /* Utils */
 
 float *
-run_inference(float *input, uint32_t *input_size, uint32_t *output_size,
-              char *model_name, uint32_t num_output_tensors);
+run_inference(float *input, uint32_t *input_size,
+              uint32_t *output_size, char *model_name,
+              uint32_t num_output_tensors);
 
 input_info
 create_input(int *dims);