remove tensor new_from_host_ptr function (#125)

Remove the `Tensor::new_from_host_ptr` function since it passed along a pointer across the FFI boundary to OpenVINO that relied on the lifetime of the buffer, a `&[u8]`, which only was required to live as long as the function call. When that buffer went out of scope the pointer was invalid, causing some observed segfaults with later usage of that tensor. The offending function in this case was `Core::read_model_from_buffer`, which ended up holding on to the weights tensor until some later time.

This will force all tensor creation to occur via copying (e.g., `slice::copy_from_slice`). Eventually we should work out a scheme to avoid this extra work; using `PhantomData` to propagate lifetimes started touching too much code but there is likely something else that can be done here instead.

Author: rahulchaphalkar

crates/openvino/src/prepostprocess.rs

@@ -12,7 +12,9 @@
 //! # ).expect("to read the model from file");
 //! # let data = fs::read("tests/fixtures/inception/tensor-1x3x299x299-f32.bgr").expect("to read the tensor from file");
 //! # let input_shape = Shape::new(&vec![1, 299, 299, 3]).expect("to create a new shape");
-//! # let tensor = Tensor::new_from_host_ptr(ElementType::F32, &input_shape, &data).expect("to create a new tensor from host pointer");
+//! # let mut tensor = Tensor::new(ElementType::F32, &input_shape).expect("to create a new tensor");
+//! # let buffer = tensor.buffer_mut().unwrap();
+//! # buffer.copy_from_slice(&data);
 //! // Insantiate a new core, read in a model, and set up a tensor with input data before performing pre/post processing
 //! // Pre-process the input by:
 //! // - converting NHWC to NCHW

crates/openvino/src/tensor.rs

@@ -5,9 +5,9 @@ use crate::element_type::ElementType;
 use crate::shape::Shape;
 use crate::{drop_using_function, try_unsafe, util::Result};
 use openvino_sys::{
-    self, ov_shape_t, ov_tensor_create, ov_tensor_create_from_host_ptr, ov_tensor_data,
-    ov_tensor_free, ov_tensor_get_byte_size, ov_tensor_get_element_type, ov_tensor_get_shape,
-    ov_tensor_get_size, ov_tensor_set_shape, ov_tensor_t,
+    self, ov_shape_t, ov_tensor_create, ov_tensor_data, ov_tensor_free, ov_tensor_get_byte_size,
+    ov_tensor_get_element_type, ov_tensor_get_shape, ov_tensor_get_size, ov_tensor_set_shape,
+    ov_tensor_t,
 };
 
 /// See [`Tensor`](https://docs.openvino.ai/2023.3/api/c_cpp_api/group__ov__tensor__c__api.html).
@@ -34,30 +34,6 @@ impl Tensor {
         Self { ptr }
     }
 
-    /// Create a new [`Tensor`] from a host pointer.
-    ///
-    /// # Arguments
-    ///
-    /// * `data_type` - The data type of the tensor.
-    /// * `shape` - The shape of the tensor.
-    /// * `data` - The data buffer.
-    ///
-    /// # Returns
-    ///
-    /// A new `Tensor` object.
-    pub fn new_from_host_ptr(data_type: ElementType, shape: &Shape, data: &[u8]) -> Result<Self> {
-        let mut tensor: *mut ov_tensor_t = std::ptr::null_mut();
-        let element_type: u32 = data_type as u32;
-        let buffer = data.as_ptr() as *mut std::os::raw::c_void;
-        try_unsafe!(ov_tensor_create_from_host_ptr(
-            element_type,
-            shape.as_c_struct(),
-            buffer,
-            std::ptr::addr_of_mut!(tensor)
-        ))?;
-        Ok(Self { ptr: tensor })
-    }
-
     /// Get the pointer to the underlying OpenVINO tensor.
     #[inline]
     pub(crate) fn as_ptr(&self) -> *const ov_tensor_t {

crates/openvino/tests/classify-alexnet.rs

@@ -27,7 +27,9 @@ fn classify_alexnet() -> anyhow::Result<()> {
     let data = fs::read(Fixture::tensor())?;
     let input_shape = Shape::new(&vec![1, 227, 227, 3])?;
     let element_type = ElementType::F32;
-    let tensor = Tensor::new_from_host_ptr(element_type, &input_shape, &data)?;
+    let mut tensor = Tensor::new(element_type, &input_shape)?;
+    let buffer = tensor.buffer_mut()?;
+    buffer.copy_from_slice(&data);
 
     // Pre-process the input by:
     // - converting NHWC to NCHW

crates/openvino/tests/classify-inception.rs

@@ -27,7 +27,9 @@ fn classify_inception() -> anyhow::Result<()> {
     let data = fs::read(Fixture::tensor())?;
     let input_shape = Shape::new(&vec![1, 299, 299, 3])?;
     let element_type = ElementType::F32;
-    let tensor = Tensor::new_from_host_ptr(element_type, &input_shape, &data)?;
+    let mut tensor = Tensor::new(element_type, &input_shape)?;
+    let buffer = tensor.buffer_mut()?;
+    buffer.copy_from_slice(&data);
 
     // Pre-process the input by:
     // - converting NHWC to NCHW

crates/openvino/tests/classify-mobilenet.rs

@@ -27,7 +27,9 @@ fn classify_mobilenet() -> anyhow::Result<()> {
     let data = fs::read(Fixture::tensor())?;
     let input_shape = Shape::new(&vec![1, 224, 224, 3])?;
     let element_type = ElementType::F32;
-    let tensor = Tensor::new_from_host_ptr(element_type, &input_shape, &data)?;
+    let mut tensor = Tensor::new(element_type, &input_shape)?;
+    let buffer = tensor.buffer_mut()?;
+    buffer.copy_from_slice(&data);
 
     // Pre-process the input by:
     // - converting NHWC to NCHW