Refactor WASI-NN to simplify the support for multiple frameworks (#1834)

- Reorganize the library structure
- Use the latest version of `wasi-nn` wit (Oct 25, 2022):
    0f77c48ec1/wasi-nn.wit.md
- Split logic that converts WASM structs to native structs in a separate file
- Simplify addition of new frameworks

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

@@ -3,63 +3,17 @@
  * SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
  */
 
-#ifndef WASI_NN_WASM_H
-#define WASI_NN_WASM_H
-
-#include "wasi_nn_common.h"
-
 /**
  * Following definition from:
- * [Aug 10th, 2022]
- * https://github.com/WebAssembly/wasi-nn/blob/e5e1a6c31f424c7cd63026cd270e9746775675a0/wasi-nn.wit.md
+ * [Oct 25th, 2022]
+ * https://github.com/WebAssembly/wasi-nn/blob/0f77c48ec195748990ff67928a4b3eef5f16c2de/wasi-nn.wit.md
  */
 
-/* The graph initialization data. */
+#ifndef WASI_NN_H
+#define WASI_NN_H
 
-// This consists of an array of buffers because implementing backends may encode
-// their graph IR in parts (e.g., OpenVINO stores its IR and weights
-// separately).
-typedef struct {
-    uint8_t *buf;
-    uint32_t size;
-} graph_builder;
-
-typedef struct {
-    graph_builder *buf;
-    uint32_t size;
-} graph_builder_array;
-
-/* The dimensions of a tensor. */
-
-// The array length matches the tensor rank and each element in the array
-// describes the size of each dimension.
-typedef struct {
-    uint32_t *buf;
-    uint32_t size;
-} tensor_dimensions;
-
-/* The tensor data. */
-
-// Initially conceived as a sparse representation, each empty cell would be
-// filled with zeros and the array length must match the product of all of the
-// dimensions and the number of bytes in the type (e.g., a 2x2 tensor with
-// 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;
-
-/* A tensor. */
-
-typedef struct {
-    // Describe the size of the tensor (e.g., 2x2x2x2 -> [2, 2, 2, 2]). To
-    // represent a tensor containing a single value, use `[1]` for the tensor
-    // dimensions.
-    tensor_dimensions *dimensions;
-    // Describe the type of element in the tensor (e.g., f32).
-    tensor_type type;
-    // Contains the tensor data.
-    tensor_data data;
-} tensor;
+#include <stdint.h>
+#include "wasi_nn_types.h"
 
 /**
  * @brief Load an opaque sequence of bytes to use for inference.
@@ -67,25 +21,31 @@ typedef struct {
  * @param builder   Model builder.
  * @param encoding  Model encoding.
  * @param target    Execution target.
- * @param graph     Graph.
+ * @param g         Graph.
  * @return error    Execution status.
  */
 error
 load(graph_builder_array *builder, graph_encoding encoding,
-     execution_target target, graph *graph)
-    __attribute__((export_module("wasi_nn")))
+     execution_target target, graph *g)
     __attribute__((import_module("wasi_nn")));
 
+/**
+ * INFERENCE
+ *
+ */
+
+// Bind a `graph` to the input and output tensors for an inference.
+typedef uint32_t graph_execution_context;
+
 /**
  * @brief Create an execution instance of a loaded graph.
  *
- * @param graph     Graph.
+ * @param g         Graph.
  * @param ctx       Execution context.
  * @return error    Execution status.
  */
 error
-init_execution_context(graph graph, graph_execution_context *ctx)
-    __attribute__((export_module("wasi_nn")))
+init_execution_context(graph g, graph_execution_context *ctx)
     __attribute__((import_module("wasi_nn")));
 
 /**
@@ -98,7 +58,6 @@ init_execution_context(graph graph, graph_execution_context *ctx)
  */
 error
 set_input(graph_execution_context ctx, uint32_t index, tensor *tensor)
-    __attribute__((export_module("wasi_nn")))
     __attribute__((import_module("wasi_nn")));
 
 /**
@@ -108,8 +67,7 @@ set_input(graph_execution_context ctx, uint32_t index, tensor *tensor)
  * @return error    Execution status.
  */
 error
-compute(graph_execution_context ctx) __attribute__((export_module("wasi_nn")))
-__attribute__((import_module("wasi_nn")));
+compute(graph_execution_context ctx) __attribute__((import_module("wasi_nn")));
 
 /**
  * @brief Extract the outputs after inference.
@@ -126,7 +84,6 @@ __attribute__((import_module("wasi_nn")));
 error
 get_output(graph_execution_context ctx, uint32_t index,
            tensor_data output_tensor, uint32_t *output_tensor_size)
-    __attribute__((export_module("wasi_nn")))
     __attribute__((import_module("wasi_nn")));
 
 #endif