feat: copy tensors (#382)

Adds `Tensor::to` to allow copying tensors to another device, and impls
`Clone` for tensors.

.gitignore

@@ -6,6 +6,7 @@ Cargo.lock
 **/*.ort
 tools/train-data/**/checkpoint
 !tests/data/**/*
+!src/value/impl_tensor/identity.ort
 
 .venv*
 docs/.next

src/io_binding.rs

@@ -121,7 +121,7 @@ impl IoBinding {
 	///
 	/// The data is only copied upon invocation of this function. Any changes to the given value afterwards will not
 	/// affect the data seen by the session until the value is re-bound.
-	pub fn bind_input<T: ValueTypeMarker, S: Into<String>>(&mut self, name: S, ort_value: &Value<T>) -> Result<()> {
+	pub fn bind_input<T: ValueTypeMarker + ?Sized, S: Into<String>>(&mut self, name: S, ort_value: &Value<T>) -> Result<()> {
 		let name: String = name.into();
 		let ptr = self.ptr_mut();
 		with_cstr(name.as_bytes(), &|name| {
@@ -142,7 +142,7 @@ impl IoBinding {
 	/// `name`.
 	///
 	/// [`Tensor::new`]: crate::value::Tensor::new
-	pub fn bind_output<T: ValueTypeMarker, S: Into<String>>(&mut self, name: S, ort_value: Value<T>) -> Result<()> {
+	pub fn bind_output<T: ValueTypeMarker + ?Sized, S: Into<String>>(&mut self, name: S, ort_value: Value<T>) -> Result<()> {
 		let name: String = name.into();
 		let ptr = self.ptr_mut();
 		with_cstr(name.as_bytes(), &|name| {

src/memory.rs

@@ -244,7 +244,7 @@ impl Drop for AllocatedBlock<'_> {
 }
 
 /// Represents possible devices that have their own device allocator.
-#[derive(Debug, Copy, Clone, PartialEq, Eq)]
+#[derive(Debug, Copy, Clone, PartialEq, Eq, Hash)]
 // &'static str should be valid here since they're only ever defined in C++ with `const char *` literals
 pub struct AllocationDevice(&'static str);
 

src/session/builder/impl_commit.rs

@@ -112,7 +112,9 @@ impl SessionBuilder {
 		let model_path = crate::util::path_to_os_char(model_filepath);
 
 		let env = get_environment()?;
-		apply_execution_providers(&mut self, &env.execution_providers, "environment")?;
+		if !self.no_env_eps {
+			apply_execution_providers(&mut self, &env.execution_providers, "environment")?;
+		}
 
 		if env.has_global_threadpool && !self.no_global_thread_pool {
 			ortsys![unsafe DisablePerSessionThreads(self.ptr_mut())?];
@@ -185,7 +187,9 @@ impl SessionBuilder {
 		let mut session_ptr: *mut ort_sys::OrtSession = ptr::null_mut();
 
 		let env = get_environment()?;
-		apply_execution_providers(&mut self, &env.execution_providers, "environment")?;
+		if !self.no_env_eps {
+			apply_execution_providers(&mut self, &env.execution_providers, "environment")?;
+		}
 
 		if env.has_global_threadpool && !self.no_global_thread_pool {
 			ortsys![unsafe DisablePerSessionThreads(self.ptr_mut())?];

src/session/builder/impl_options.rs

@@ -215,6 +215,11 @@ impl SessionBuilder {
 		Ok(self)
 	}
 
+	pub fn with_no_environment_execution_providers(mut self) -> Result<Self> {
+		self.no_env_eps = true;
+		Ok(self)
+	}
+
 	pub fn with_thread_manager<T: ThreadManager + Any + 'static>(mut self, manager: T) -> Result<Self> {
 		let manager = Rc::new(manager);
 		ortsys![unsafe SessionOptionsSetCustomThreadCreationOptions(self.ptr_mut(), (&*manager as *const T) as *mut c_void)?];

src/session/builder/mod.rs

@@ -38,7 +38,8 @@ pub struct SessionBuilder {
 	external_initializer_buffers: Vec<Cow<'static, [u8]>>,
 	prepacked_weights: Option<PrepackedWeights>,
 	thread_manager: Option<Rc<dyn Any>>,
-	no_global_thread_pool: bool
+	no_global_thread_pool: bool,
+	no_env_eps: bool
 }
 
 impl Clone for SessionBuilder {
@@ -57,7 +58,8 @@ impl Clone for SessionBuilder {
 			external_initializer_buffers: self.external_initializer_buffers.clone(),
 			prepacked_weights: self.prepacked_weights.clone(),
 			thread_manager: self.thread_manager.clone(),
-			no_global_thread_pool: self.no_global_thread_pool
+			no_global_thread_pool: self.no_global_thread_pool,
+			no_env_eps: self.no_env_eps
 		}
 	}
 }
@@ -93,7 +95,8 @@ impl SessionBuilder {
 			external_initializer_buffers: Vec::new(),
 			prepacked_weights: None,
 			thread_manager: None,
-			no_global_thread_pool: false
+			no_global_thread_pool: false,
+			no_env_eps: false
 		})
 	}
 

src/util.rs

@@ -298,6 +298,102 @@ impl<T> Drop for OnceLock<T> {
 	}
 }
 
+pub use self::mutex::{Mutex, MutexGuard};
+#[cfg(feature = "std")]
+mod mutex {
+	use std::sync::Mutex as StdMutex;
+	pub use std::sync::MutexGuard;
+
+	#[repr(transparent)]
+	pub struct Mutex<T>(StdMutex<T>);
+
+	impl<T> Mutex<T> {
+		pub fn new(data: T) -> Self {
+			Self(StdMutex::new(data))
+		}
+
+		pub fn lock(&self) -> MutexGuard<'_, T> {
+			match self.0.lock() {
+				Ok(guard) => guard,
+				// ignore poison error
+				Err(p) => p.into_inner()
+			}
+		}
+	}
+}
+#[cfg(not(feature = "std"))]
+mod mutex {
+	use core::{
+		cell::UnsafeCell,
+		ops::{Deref, DerefMut},
+		sync::atomic::{AtomicBool, Ordering}
+	};
+
+	pub struct Mutex<T> {
+		is_locked: AtomicBool,
+		data: UnsafeCell<T>
+	}
+
+	unsafe impl<T: Send> Send for Mutex<T> {}
+	unsafe impl<T: Send> Sync for Mutex<T> {}
+
+	impl<T> Mutex<T> {
+		pub fn new(data: T) -> Self {
+			Mutex {
+				is_locked: AtomicBool::new(false),
+				data: UnsafeCell::new(data)
+			}
+		}
+
+		pub fn lock(&self) -> MutexGuard<'_, T> {
+			loop {
+				if self
+					.is_locked
+					.compare_exchange_weak(false, true, Ordering::Acquire, Ordering::Relaxed)
+					.is_ok()
+				{
+					return MutexGuard {
+						is_locked: &self.is_locked,
+						data: unsafe { &mut *self.data.get() }
+					};
+				}
+
+				while self.is_locked.load(Ordering::Relaxed) {
+					core::hint::spin_loop();
+				}
+			}
+		}
+	}
+
+	pub struct MutexGuard<'a, T: 'a> {
+		is_locked: &'a AtomicBool,
+		data: *mut T
+	}
+
+	unsafe impl<T: Send> Send for MutexGuard<'_, T> {}
+	unsafe impl<T: Sync> Sync for MutexGuard<'_, T> {}
+
+	impl<T> Deref for MutexGuard<'_, T> {
+		type Target = T;
+
+		fn deref(&self) -> &Self::Target {
+			unsafe { &*self.data }
+		}
+	}
+
+	impl<T> DerefMut for MutexGuard<'_, T> {
+		fn deref_mut(&mut self) -> &mut Self::Target {
+			unsafe { &mut *self.data }
+		}
+	}
+
+	impl<T> Drop for MutexGuard<'_, T> {
+		fn drop(&mut self) {
+			self.is_locked.store(false, Ordering::Release);
+		}
+	}
+}
+
 #[cold]
 #[inline]
 #[doc(hidden)]

src/value/impl_tensor/extract.rs

@@ -246,6 +246,13 @@ impl<Type: TensorValueTypeMarker + ?Sized> Value<Type> {
 			_ => unreachable!()
 		}
 	}
+
+	pub fn data_type(&self) -> &TensorElementType {
+		match self.dtype() {
+			ValueType::Tensor { ty, .. } => ty,
+			_ => unreachable!()
+		}
+	}
 }
 
 fn extract_tensor<'t>(

src/value/impl_tensor/mod.rs

@@ -1,7 +1,7 @@
 mod create;
 mod extract;
 
-use alloc::sync::Arc;
+use alloc::{format, string::ToString, sync::Arc};
 use core::{
 	fmt::{self, Debug},
 	marker::PhantomData,
@@ -14,7 +14,7 @@ use super::{DowncastableTarget, DynValue, Value, ValueInner, ValueRef, ValueRefM
 use crate::{
 	AsPointer,
 	error::Result,
-	memory::{Allocator, MemoryInfo},
+	memory::{AllocationDevice, Allocator, MemoryInfo},
 	ortsys,
 	tensor::{IntoTensorElementType, Shape, SymbolicDimensions, TensorElementType}
 };
@@ -216,6 +216,141 @@ impl<Type: TensorValueTypeMarker + ?Sized> Value<Type> {
 	pub fn memory_info(&self) -> &MemoryInfo {
 		unsafe { self.inner.memory_info.as_ref().unwrap_unchecked() }
 	}
+
+	/// Copies the contents of this tensor to another device, returning the newly created tensor value.
+	///
+	/// ```
+	/// # use ort::{memory::{Allocator, AllocatorType, AllocationDevice, MemoryInfo, MemoryType}, session::Session, value::Tensor};
+	/// # fn main() -> ort::Result<()> {
+	/// # if false {
+	/// # let session = Session::builder()?.commit_from_file("tests/data/upsample.onnx")?;
+	/// let cuda_allocator = Allocator::new(
+	/// 	&session,
+	/// 	MemoryInfo::new(AllocationDevice::CUDA, 0, AllocatorType::Device, MemoryType::Default)?
+	/// )?;
+	/// let cuda_tensor = Tensor::<f32>::new(&cuda_allocator, [1_usize, 3, 224, 224])?;
+	/// # }
+	/// # let cuda_tensor = Tensor::<f32>::new(&Allocator::default(), [1_usize, 3, 224, 224])?;
+	///
+	/// let cpu_tensor = cuda_tensor.to(AllocationDevice::CPU, 0)?;
+	/// assert_eq!(cpu_tensor.memory_info().allocation_device(), AllocationDevice::CPU);
+	/// assert_eq!(**cpu_tensor.shape(), [1, 3, 224, 224]);
+	/// # Ok(())
+	/// # }
+	/// ```
+	pub fn to(&self, device: AllocationDevice, device_id: i32) -> Result<Value<Type>> {
+		use crate::{
+			OnceLock, execution_providers as ep,
+			io_binding::IoBinding,
+			memory::{AllocatorType, MemoryType},
+			session::{Session, builder::GraphOptimizationLevel},
+			util::{MiniMap, Mutex}
+		};
+
+		type IdentitySessionKey = (AllocationDevice, i32, ort_sys::ONNXTensorElementDataType);
+		type IdentitySession = (Session, IoBinding);
+
+		static SESSIONS: OnceLock<Mutex<MiniMap<IdentitySessionKey, IdentitySession>>> = OnceLock::new();
+		static IDENTITY_MODEL: &[u8] = include_bytes!("./identity.ort");
+
+		let target_memory_info = MemoryInfo::new(device, device_id, AllocatorType::Device, MemoryType::Default)?;
+		let tensor_type = ort_sys::ONNXTensorElementDataType::from(*self.data_type());
+
+		let mut sessions = SESSIONS.get_or_init(|| Mutex::new(MiniMap::new())).lock();
+		let (session, binding) = match sessions.get_mut(&(device, device_id, tensor_type)) {
+			Some(entry) => entry,
+			None => {
+				let mut model_bytes = IDENTITY_MODEL.to_vec();
+				// Override the expected element type of the input & output nodes, respectively.
+				model_bytes[544] = tensor_type as u8;
+				model_bytes[604] = tensor_type as u8;
+
+				let session = Session::builder()?
+					.with_optimization_level(GraphOptimizationLevel::Disable)?
+					.with_intra_threads(1)?
+					.with_inter_threads(1)?
+					.with_inter_op_spinning(false)?
+					.with_intra_op_spinning(false)?
+					.with_memory_pattern(false)?
+					.with_no_environment_execution_providers()?
+					.with_execution_providers([match device {
+						AllocationDevice::CPU => ep::CPUExecutionProvider::default().with_arena_allocator(false).build(),
+						AllocationDevice::CUDA | AllocationDevice::CUDA_PINNED => ep::CUDAExecutionProvider::default()
+							.with_device_id(device_id)
+							.with_arena_extend_strategy(ep::ArenaExtendStrategy::SameAsRequested)
+							.with_conv_max_workspace(false)
+							.with_conv_algorithm_search(ep::cuda::CuDNNConvAlgorithmSearch::Default)
+							.build(),
+						AllocationDevice::DIRECTML | AllocationDevice::DIRECTML_CPU => {
+							ep::DirectMLExecutionProvider::default().with_device_id(device_id).build()
+						}
+						AllocationDevice::CANN | AllocationDevice::CANN_PINNED => ep::CANNExecutionProvider::default()
+							.with_arena_extend_strategy(ep::ArenaExtendStrategy::SameAsRequested)
+							.with_cann_graph(false)
+							.with_device_id(device_id)
+							.build(),
+						AllocationDevice::OPENVINO_CPU | AllocationDevice::OPENVINO_GPU => ep::OpenVINOExecutionProvider::default()
+							.with_num_threads(1)
+							.with_device_type(if device == AllocationDevice::OPENVINO_CPU {
+								"CPU".to_string()
+							} else {
+								format!("GPU.{device_id}")
+							})
+							.build(),
+						AllocationDevice::HIP | AllocationDevice::HIP_PINNED => ep::ROCmExecutionProvider::default()
+							.with_arena_extend_strategy(ep::ArenaExtendStrategy::SameAsRequested)
+							.with_hip_graph(false)
+							.with_exhaustive_conv_search(false)
+							.with_device_id(device_id)
+							.build(),
+						AllocationDevice::TVM => ep::TVMExecutionProvider::default().build(),
+						AllocationDevice::XNNPACK => ep::XNNPACKExecutionProvider::default().build(),
+						_ => return Err(crate::Error::new("Unsupported allocation device {device} for tensor copy target"))
+					}])?
+					.with_allocator(MemoryInfo::new(AllocationDevice::CPU, 0, AllocatorType::Device, MemoryType::Default)?)?
+					.commit_from_memory(&model_bytes)?;
+				let binding = session.create_binding()?;
+				sessions.insert((device, device_id, tensor_type), (session, binding));
+				sessions.get_mut(&(device, device_id, tensor_type)).expect("insert should have worked")
+			}
+		};
+
+		binding.bind_input("input", self)?;
+		binding.bind_output_to_device("output", &target_memory_info)?;
+
+		let output = session
+			.run_binding(binding)?
+			.remove("output")
+			.expect("identity model should have single output");
+		Ok(unsafe { output.transmute_type() })
+	}
+}
+
+impl<Type: TensorValueTypeMarker + ?Sized> Clone for Value<Type> {
+	/// Creates a copy of this tensor and its data on the same device it resides on.
+	///
+	/// ```
+	/// # use ort::{value::Tensor, AsPointer};
+	/// # fn main() -> ort::Result<()> {
+	/// let array = vec![1_i64, 2, 3, 4, 5];
+	/// let tensor = Tensor::from_array(([array.len()], array.into_boxed_slice()))?;
+	///
+	/// let new_tensor = tensor.clone();
+	///
+	/// // same data
+	/// assert_eq!(tensor.extract_tensor(), new_tensor.extract_tensor());
+	///
+	/// // different allocations
+	/// assert_ne!(tensor.ptr(), new_tensor.ptr());
+	/// assert_ne!(tensor.data_ptr()?, new_tensor.data_ptr()?);
+	/// # 	Ok(())
+	/// # }
+	/// ```
+	fn clone(&self) -> Self {
+		let memory_info = self.memory_info();
+		self.to(memory_info.allocation_device(), memory_info.device_id())
+			.expect("Failed to clone tensor")
+	}
 }
 
 impl<T: IntoTensorElementType + Debug> Tensor<T> {