wasi_ephemeral_nn.h: prefix identfiers to avoid too generic names (#4358)

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

@@ -4,4 +4,9 @@
  */
 
 #define WASM_ENABLE_WASI_EPHEMERAL_NN 1
+#define WASI_NN_NAME(name) wasi_ephemeral_nn_##name
+
 #include "wasi_nn.h"
+
+#undef WASM_ENABLE_WASI_EPHEMERAL_NN
+#undef WASI_NN_NAME

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

@@ -34,17 +34,22 @@
  * @return wasi_nn_error    Execution status.
  */
 #if WASM_ENABLE_WASI_EPHEMERAL_NN != 0
-wasi_nn_error
-load(graph_builder *builder, uint32_t builder_len, graph_encoding encoding,
-     execution_target target, graph *g) WASI_NN_IMPORT("load");
+WASI_NN_ERROR_TYPE
+WASI_NN_NAME(load)
+(WASI_NN_NAME(graph_builder) * builder, uint32_t builder_len,
+ WASI_NN_NAME(graph_encoding) encoding, WASI_NN_NAME(execution_target) target,
+ WASI_NN_NAME(graph) * g) WASI_NN_IMPORT("load");
 #else
-wasi_nn_error
-load(graph_builder_array *builder, graph_encoding encoding,
-     execution_target target, graph *g) WASI_NN_IMPORT("load");
+WASI_NN_ERROR_TYPE
+WASI_NN_NAME(load)
+(WASI_NN_NAME(graph_builder_array) * builder,
+ WASI_NN_NAME(graph_encoding) encoding, WASI_NN_NAME(execution_target) target,
+ WASI_NN_NAME(graph) * g) WASI_NN_IMPORT("load");
 #endif
 
-wasi_nn_error
-load_by_name(const char *name, uint32_t name_len, graph *g)
+WASI_NN_ERROR_TYPE
+WASI_NN_NAME(load_by_name)
+(const char *name, uint32_t name_len, WASI_NN_NAME(graph) * g)
     WASI_NN_IMPORT("load_by_name");
 
 /**
@@ -59,8 +64,9 @@ load_by_name(const char *name, uint32_t name_len, graph *g)
  * @param ctx       Execution context.
  * @return wasi_nn_error    Execution status.
  */
-wasi_nn_error
-init_execution_context(graph g, graph_execution_context *ctx)
+WASI_NN_ERROR_TYPE
+WASI_NN_NAME(init_execution_context)
+(WASI_NN_NAME(graph) g, WASI_NN_NAME(graph_execution_context) * ctx)
     WASI_NN_IMPORT("init_execution_context");
 
 /**
@@ -71,9 +77,10 @@ init_execution_context(graph g, graph_execution_context *ctx)
  * @param tensor    Input tensor.
  * @return wasi_nn_error    Execution status.
  */
-wasi_nn_error
-set_input(graph_execution_context ctx, uint32_t index, tensor *tensor)
-    WASI_NN_IMPORT("set_input");
+WASI_NN_ERROR_TYPE
+WASI_NN_NAME(set_input)
+(WASI_NN_NAME(graph_execution_context) ctx, uint32_t index,
+ WASI_NN_NAME(tensor) * tensor) WASI_NN_IMPORT("set_input");
 
 /**
  * @brief Compute the inference on the given inputs.
@@ -81,8 +88,9 @@ set_input(graph_execution_context ctx, uint32_t index, tensor *tensor)
  * @param ctx       Execution context.
  * @return wasi_nn_error    Execution status.
  */
-wasi_nn_error
-compute(graph_execution_context ctx) WASI_NN_IMPORT("compute");
+WASI_NN_ERROR_TYPE
+WASI_NN_NAME(compute)
+(WASI_NN_NAME(graph_execution_context) ctx) WASI_NN_IMPORT("compute");
 
 /**
  * @brief Extract the outputs after inference.
@@ -97,14 +105,16 @@ compute(graph_execution_context ctx) WASI_NN_IMPORT("compute");
  * @return wasi_nn_error                Execution status.
  */
 #if WASM_ENABLE_WASI_EPHEMERAL_NN != 0
-wasi_nn_error
-get_output(graph_execution_context ctx, uint32_t index,
-           tensor_data output_tensor, uint32_t output_tensor_max_size,
-           uint32_t *output_tensor_size) WASI_NN_IMPORT("get_output");
+WASI_NN_ERROR_TYPE
+WASI_NN_NAME(get_output)
+(WASI_NN_NAME(graph_execution_context) ctx, uint32_t index,
+ WASI_NN_NAME(tensor_data) output_tensor, uint32_t output_tensor_max_size,
+ uint32_t *output_tensor_size) WASI_NN_IMPORT("get_output");
 #else
-wasi_nn_error
-get_output(graph_execution_context ctx, uint32_t index,
-           tensor_data output_tensor, uint32_t *output_tensor_size)
+WASI_NN_ERROR_TYPE
+WASI_NN_NAME(get_output)
+(graph_execution_context ctx, uint32_t index,
+ WASI_NN_NAME(tensor_data) output_tensor, uint32_t *output_tensor_size)
     WASI_NN_IMPORT("get_output");
 #endif
 

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

@@ -13,6 +13,23 @@
 extern "C" {
 #endif
 
+/* our host logic doesn't use any prefix. neither legacy wasi_nn.h does. */
+
+#if !defined(__wasm__) || !defined(WASI_NN_NAME)
+#define WASI_NN_NAME(name) name
+#define WASI_NN_ERROR_NAME(name) name
+#define WASI_NN_TYPE_NAME(name) name
+#define WASI_NN_ENCODING_NAME(name) name
+#define WASI_NN_TARGET_NAME(name) name
+#define WASI_NN_ERROR_TYPE wasi_nn_error
+#else
+#define WASI_NN_ERROR_NAME(name) WASI_NN_NAME(error_##name)
+#define WASI_NN_TYPE_NAME(name) WASI_NN_NAME(type_##name)
+#define WASI_NN_ENCODING_NAME(name) WASI_NN_NAME(encoding_##name)
+#define WASI_NN_TARGET_NAME(name) WASI_NN_NAME(target_##name)
+#define WASI_NN_ERROR_TYPE WASI_NN_NAME(error);
+#endif
+
 /**
  * ERRORS
  *
@@ -22,22 +39,22 @@ extern "C" {
 // https://github.com/WebAssembly/wasi-nn/blob/71320d95b8c6d43f9af7f44e18b1839db85d89b4/wasi-nn.witx#L5-L17
 // Error codes returned by functions in this API.
 typedef enum {
-    success = 0,
-    invalid_argument,
-    invalid_encoding,
-    missing_memory,
-    busy,
-    runtime_error,
-    unsupported_operation,
-    too_large,
-    not_found,
+    WASI_NN_ERROR_NAME(success) = 0,
+    WASI_NN_ERROR_NAME(invalid_argument),
+    WASI_NN_ERROR_NAME(invalid_encoding),
+    WASI_NN_ERROR_NAME(missing_memory),
+    WASI_NN_ERROR_NAME(busy),
+    WASI_NN_ERROR_NAME(runtime_error),
+    WASI_NN_ERROR_NAME(unsupported_operation),
+    WASI_NN_ERROR_NAME(too_large),
+    WASI_NN_ERROR_NAME(not_found),
 
     // for WasmEdge-wasi-nn
-    end_of_sequence = 100,  // End of Sequence Found.
-    context_full = 101,     // Context Full.
-    prompt_tool_long = 102, // Prompt Too Long.
-    model_not_found = 103,  // Model Not Found.
-} wasi_nn_error;
+    WASI_NN_ERROR_NAME(end_of_sequence) = 100,  // End of Sequence Found.
+    WASI_NN_ERROR_NAME(context_full) = 101,     // Context Full.
+    WASI_NN_ERROR_NAME(prompt_tool_long) = 102, // Prompt Too Long.
+    WASI_NN_ERROR_NAME(model_not_found) = 103,  // Model Not Found.
+} WASI_NN_ERROR_TYPE;
 
 /**
  * TENSOR
@@ -51,15 +68,27 @@ typedef enum {
 typedef struct {
     uint32_t *buf;
     uint32_t size;
-} tensor_dimensions;
+} WASI_NN_NAME(tensor_dimensions);
 
 #if WASM_ENABLE_WASI_EPHEMERAL_NN != 0
 // sync up with
 // https://github.com/WebAssembly/wasi-nn/blob/71320d95b8c6d43f9af7f44e18b1839db85d89b4/wasi-nn.witx#L19-L28
 // The type of the elements in a tensor.
-typedef enum { fp16 = 0, fp32, fp64, u8, i32, i64 } tensor_type;
+typedef enum {
+    WASI_NN_TYPE_NAME(fp16) = 0,
+    WASI_NN_TYPE_NAME(fp32),
+    WASI_NN_TYPE_NAME(fp64),
+    WASI_NN_TYPE_NAME(u8),
+    WASI_NN_TYPE_NAME(i32),
+    WASI_NN_TYPE_NAME(i64),
+} WASI_NN_NAME(tensor_type);
 #else
-typedef enum { fp16 = 0, fp32, up8, ip32 } tensor_type;
+typedef enum {
+    WASI_NN_TYPE_NAME(fp16) = 0,
+    WASI_NN_TYPE_NAME(fp32),
+    WASI_NN_TYPE_NAME(up8),
+    WASI_NN_TYPE_NAME(ip32),
+} WASI_NN_NAME(tensor_type);
 #endif /* WASM_ENABLE_WASI_EPHEMERAL_NN != 0 */
 
 // The tensor data.
@@ -70,7 +99,7 @@ typedef enum { fp16 = 0, fp32, up8, ip32 } tensor_type;
 // 4-byte f32 elements would have a data array of length 16). Naturally, this
 // representation requires some knowledge of how to lay out data in
 // memory--e.g., using row-major ordering--and could perhaps be improved.
-typedef uint8_t *tensor_data;
+typedef uint8_t *WASI_NN_NAME(tensor_data);
 
 // A tensor.
 typedef struct {
@@ -78,16 +107,16 @@ typedef struct {
     // represent a tensor containing a single value, use `[1]` for the tensor
     // dimensions.
 #if WASM_ENABLE_WASI_EPHEMERAL_NN != 0 && defined(__wasm__)
-    tensor_dimensions dimensions;
+    WASI_NN_NAME(tensor_dimensions) dimensions;
 #else
-    tensor_dimensions *dimensions;
+    WASI_NN_NAME(tensor_dimensions) * dimensions;
 #endif
     // Describe the type of element in the tensor (e.g., f32).
     uint8_t type;
     uint8_t _pad[3];
     // Contains the tensor data.
-    tensor_data data;
-} tensor;
+    WASI_NN_NAME(tensor_data) data;
+} WASI_NN_NAME(tensor);
 
 /**
  * GRAPH
@@ -102,15 +131,15 @@ typedef struct {
 typedef struct {
     uint8_t *buf;
     uint32_t size;
-} graph_builder;
+} WASI_NN_NAME(graph_builder);
 
 typedef struct {
-    graph_builder *buf;
+    WASI_NN_NAME(graph_builder) * buf;
     uint32_t size;
-} graph_builder_array;
+} WASI_NN_NAME(graph_builder_array);
 
 // An execution graph for performing inference (i.e., a model).
-typedef uint32_t graph;
+typedef uint32_t WASI_NN_NAME(graph);
 
 // sync up with
 // https://github.com/WebAssembly/wasi-nn/blob/main/wit/wasi-nn.wit#L75
@@ -118,21 +147,25 @@ typedef uint32_t graph;
 // various backends that encode (i.e., serialize) their graph IR with different
 // formats.
 typedef enum {
-    openvino = 0,
-    onnx,
-    tensorflow,
-    pytorch,
-    tensorflowlite,
-    ggml,
-    autodetect,
-    unknown_backend,
-} graph_encoding;
+    WASI_NN_ENCODING_NAME(openvino) = 0,
+    WASI_NN_ENCODING_NAME(onnx),
+    WASI_NN_ENCODING_NAME(tensorflow),
+    WASI_NN_ENCODING_NAME(pytorch),
+    WASI_NN_ENCODING_NAME(tensorflowlite),
+    WASI_NN_ENCODING_NAME(ggml),
+    WASI_NN_ENCODING_NAME(autodetect),
+    WASI_NN_ENCODING_NAME(unknown_backend),
+} WASI_NN_NAME(graph_encoding);
 
 // Define where the graph should be executed.
-typedef enum execution_target { cpu = 0, gpu, tpu } execution_target;
+typedef enum WASI_NN_NAME(execution_target) {
+    WASI_NN_TARGET_NAME(cpu) = 0,
+    WASI_NN_TARGET_NAME(gpu),
+    WASI_NN_TARGET_NAME(tpu),
+} WASI_NN_NAME(execution_target);
 
 // Bind a `graph` to the input and output tensors for an inference.
-typedef uint32_t graph_execution_context;
+typedef uint32_t WASI_NN_NAME(graph_execution_context);
 
 #ifdef __cplusplus
 }

wamr-wasi-extensions/samples/nn/app.c

@@ -93,7 +93,7 @@ print_result(const float *result, size_t sz)
 int
 main(int argc, char **argv)
 {
-    wasi_nn_error nnret;
+    wasi_ephemeral_nn_error nnret;
     int ret;
     void *xml;
     size_t xmlsz;
@@ -112,25 +112,27 @@ main(int argc, char **argv)
         exit(1);
     }
     /* note: openvino takes two buffers, namely IR and weights */
-    graph_builder builders[2] = { {
-                                      .buf = xml,
-                                      .size = xmlsz,
-                                  },
-                                  {
-                                      .buf = weights,
-                                      .size = weightssz,
-                                  } };
-    graph g;
-    nnret = load(builders, 2, openvino, cpu, &g);
+    wasi_ephemeral_nn_graph_builder builders[2] = { {
+                                                        .buf = xml,
+                                                        .size = xmlsz,
+                                                    },
+                                                    {
+                                                        .buf = weights,
+                                                        .size = weightssz,
+                                                    } };
+    wasi_ephemeral_nn_graph g;
+    nnret =
+        wasi_ephemeral_nn_load(builders, 2, wasi_ephemeral_nn_encoding_openvino,
+                               wasi_ephemeral_nn_target_cpu, &g);
     unmap_file(xml, xmlsz);
     unmap_file(weights, weightssz);
-    if (nnret != success) {
+    if (nnret != wasi_ephemeral_nn_error_success) {
         fprintf(stderr, "load failed with %d\n", (int)nnret);
         exit(1);
     }
-    graph_execution_context ctx;
-    nnret = init_execution_context(g, &ctx);
-    if (nnret != success) {
+    wasi_ephemeral_nn_graph_execution_context ctx;
+    nnret = wasi_ephemeral_nn_init_execution_context(g, &ctx);
+    if (nnret != wasi_ephemeral_nn_error_success) {
         fprintf(stderr, "init_execution_context failed with %d\n", (int)nnret);
         exit(1);
     }
@@ -142,26 +144,27 @@ main(int argc, char **argv)
                 strerror(ret));
         exit(1);
     }
-    tensor tensor = {
+    wasi_ephemeral_nn_tensor tensor = {
         .dimensions = { .buf = (uint32_t[]){1, 3, 224, 224,}, .size = 4, },
-        .type = fp32,
+        .type = wasi_ephemeral_nn_type_fp32,
         .data = tensordata,
     };
-    nnret = set_input(ctx, 0, &tensor);
+    nnret = wasi_ephemeral_nn_set_input(ctx, 0, &tensor);
     unmap_file(tensordata, tensordatasz);
-    if (nnret != success) {
+    if (nnret != wasi_ephemeral_nn_error_success) {
         fprintf(stderr, "set_input failed with %d\n", (int)nnret);
         exit(1);
     }
-    nnret = compute(ctx);
-    if (nnret != success) {
+    nnret = wasi_ephemeral_nn_compute(ctx);
+    if (nnret != wasi_ephemeral_nn_error_success) {
         fprintf(stderr, "compute failed with %d\n", (int)nnret);
         exit(1);
     }
     float result[1001];
     uint32_t resultsz;
-    nnret = get_output(ctx, 0, (void *)result, sizeof(result), &resultsz);
-    if (nnret != success) {
+    nnret = wasi_ephemeral_nn_get_output(ctx, 0, (void *)result, sizeof(result),
+                                         &resultsz);
+    if (nnret != wasi_ephemeral_nn_error_success) {
         fprintf(stderr, "get_output failed with %d\n", (int)nnret);
         exit(1);
     }