Only export the inference engine functions in openvino-sys

crates/openvino-sys/Cargo.toml

@@ -21,8 +21,8 @@ include = [
 ]
 
 [build-dependencies]
-bindgen = "0.55.1"
-cmake = "0.1.44"
+bindgen = "0.58.1"
+cmake = "0.1.45"
 
 [features]
 default = ["cpu"]

crates/openvino-sys/build.rs

@@ -36,13 +36,18 @@ fn main() {
         file("upstream/inference-engine/ie_bridges/c/include/c_api/ie_c_api.h");
     let bindings = bindgen::Builder::default()
         .header(openvino_c_api_header.to_string_lossy())
+        .allowlist_function("ie_.*")
+        .blocklist_type("__uint8_t")
+        .blocklist_type("__int64_t")
+        .size_t_is_usize(true)
         // While understanding the warnings in https://docs.rs/bindgen/0.36.0/bindgen/struct.Builder.html#method.rustified_enum
         // that these enums could result in unspecified behavior if constructed from an invalid
         // value, the expectation here is that OpenVINO only returns valid layout and precision
         // values. This assumption is reasonable because otherwise OpenVINO itself would be broken.
         .rustified_enum("layout_e")
         .rustified_enum("precision_e")
         .rustified_enum("resize_alg_e")
+        .rustified_enum("colorformat_e")
         .parse_callbacks(Box::new(bindgen::CargoCallbacks))
         .generate()
         .expect("generate C API bindings");

crates/openvino/src/core.rs

@@ -56,13 +56,12 @@ impl Core {
         weights_content: &[u8],
     ) -> Result<CNNNetwork> {
         let mut instance = std::ptr::null_mut();
-        let weights_desc =
-            TensorDesc::new(Layout::ANY, &[weights_content.len() as u64], Precision::U8);
+        let weights_desc = TensorDesc::new(Layout::ANY, &[weights_content.len()], Precision::U8);
         let weights_blob = Blob::new(weights_desc, weights_content)?;
         try_unsafe!(ie_core_read_network_from_memory(
             self.instance,
             model_content as *const _ as *const u8,
-            model_content.len() as u64,
+            model_content.len(),
             weights_blob.instance,
             &mut instance as *mut *mut _,
         ))?;

crates/openvino/src/network.rs

@@ -24,7 +24,7 @@ impl CNNNetwork {
         let mut cname = std::ptr::null_mut();
         try_unsafe!(ie_network_get_input_name(
             self.instance,
-            index as u64,
+            index,
             &mut cname as *mut *mut _
         ))?;
         let name = unsafe { CStr::from_ptr(cname) }
@@ -40,7 +40,7 @@ impl CNNNetwork {
         let mut cname = std::ptr::null_mut();
         try_unsafe!(ie_network_get_output_name(
             self.instance,
-            index as u64,
+            index,
             &mut cname as *mut *mut _
         ))?;
         let name = unsafe { CStr::from_ptr(cname) }

crates/openvino/src/request.rs

@@ -14,7 +14,7 @@ drop_using_function!(InferRequest, ie_infer_request_free);
 impl InferRequest {
     /// Set the batch size of the inference requests.
     pub fn set_batch_size(&mut self, size: usize) -> Result<()> {
-        try_unsafe!(ie_infer_request_set_batch(self.instance, size as u64))
+        try_unsafe!(ie_infer_request_set_batch(self.instance, size))
     }
 
     /// Assign a [Blob] to the input (i.e. `name`) on the network.

crates/openvino/src/tensor_desc.rs

@@ -8,7 +8,7 @@ pub struct TensorDesc {
 
 impl TensorDesc {
     /// Construct a new [TensorDesc] from its C API components.
-    pub fn new(layout: Layout, dimensions: &[u64], precision: Precision) -> Self {
+    pub fn new(layout: Layout, dimensions: &[usize], precision: Precision) -> Self {
         // Setup dimensions.
         assert!(dimensions.len() < 8);
         let mut dims = [0; 8];
@@ -19,7 +19,7 @@ impl TensorDesc {
             instance: tensor_desc_t {
                 layout,
                 dims: dimensions_t {
-                    ranks: dimensions.len() as u64,
+                    ranks: dimensions.len(),
                     dims,
                 },
                 precision,