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commit b631319f17b3174d8df1a2d793ba6669e124dcae Author: Guan-Ming (Wesley) Chiu <[email protected]> AuthorDate: Sat Nov 29 20:13:18 2025 +0800 [QDP] Add Python bindings for QDP using PyO3 (#649) * Add Python bindings for QDP using PyO3 * Add QuantumTensor class for DLPack integration * Add TODO * Update qdp/qdp-python/src/lib.rs Co-authored-by: Ryan Huang <[email protected]> --------- Co-authored-by: Ryan Huang <[email protected]> --- .github/workflows/pre-commit.yml | 4 +- .github/workflows/python-bindings.yml | 35 +++ qdp/Cargo.lock | 315 +++++++++++++++++++++ qdp/Cargo.toml | 5 +- qdp/qdp-core/.gitignore | 1 - qdp/qdp-core/src/dlpack.rs | 9 +- qdp/qdp-core/src/error.rs | 1 - qdp/qdp-core/src/gpu/encodings/amplitude.rs | 7 +- qdp/qdp-core/src/gpu/encodings/angle.rs | 1 - qdp/qdp-core/src/gpu/encodings/basis.rs | 1 - qdp/qdp-core/src/gpu/encodings/mod.rs | 1 - qdp/qdp-core/src/gpu/memory.rs | 16 +- qdp/qdp-core/src/gpu/mod.rs | 1 - qdp/qdp-core/src/lib.rs | 14 +- qdp/qdp-kernels/build.rs | 17 +- qdp/qdp-kernels/src/amplitude.cu | 9 +- qdp/qdp-kernels/src/lib.rs | 3 +- qdp/qdp-python/.gitignore | 72 +++++ qdp/qdp-python/Cargo.toml | 5 +- qdp/qdp-python/README.md | 49 ++++ qdp/qdp-python/pyproject.toml | 32 +++ qdp/qdp-python/src/lib.rs | 172 ++++++++++++ qdp/qdp-python/tests/test_bindings.py | 91 ++++++ qdp/qdp-python/uv.lock | 422 ++++++++++++++++++++++++++++ 24 files changed, 1228 insertions(+), 55 deletions(-) diff --git a/.github/workflows/pre-commit.yml b/.github/workflows/pre-commit.yml index 69dd15a2c..c4670c65b 100644 --- a/.github/workflows/pre-commit.yml +++ b/.github/workflows/pre-commit.yml @@ -17,9 +17,9 @@ name: Pre-commit on: push: - branches: [main] + branches: [main, dev-qdp] pull_request: - branches: [main] + branches: [main, dev-qdp] jobs: test: diff --git a/.github/workflows/python-bindings.yml b/.github/workflows/python-bindings.yml new file mode 100644 index 000000000..71bddb17a --- /dev/null +++ b/.github/workflows/python-bindings.yml @@ -0,0 +1,35 @@ +name: Python Bindings + +on: + push: + branches: + - dev-qdp + pull_request: + workflow_dispatch: + +permissions: + contents: read + +jobs: + build: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v6 + + - name: Set up uv + uses: astral-sh/setup-uv@v7 + with: + enable-cache: true + python-version: '3.11' + + - name: Build PyO3 bindings + working-directory: qdp/qdp-python + run: | + uv sync --group dev + uv run maturin develop + + - name: Upload wheel + uses: actions/upload-artifact@v4 + with: + name: python-wheel + path: qdp/qdp-python/target/wheels/*.whl diff --git a/qdp/Cargo.lock b/qdp/Cargo.lock new file mode 100644 index 000000000..f19b8ac3a --- /dev/null +++ b/qdp/Cargo.lock @@ -0,0 +1,315 @@ +# This file is automatically @generated by Cargo. +# It is not intended for manual editing. +version = 4 + +[[package]] +name = "autocfg" +version = "1.5.0" +source = "registry+https://github.com/rust-lang/crates.io-index"; 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+checksum = "7264e107f553ccae879d21fbea1d6724ac785e8c3bfc762137959b5802826ef3" + +[[package]] +name = "windows-link" +version = "0.2.1" +source = "registry+https://github.com/rust-lang/crates.io-index"; +checksum = "f0805222e57f7521d6a62e36fa9163bc891acd422f971defe97d64e70d0a4fe5" diff --git a/qdp/Cargo.toml b/qdp/Cargo.toml index 408183cda..982b15c1d 100644 --- a/qdp/Cargo.toml +++ b/qdp/Cargo.toml @@ -2,8 +2,7 @@ members = [ "qdp-core", "qdp-kernels", - # TODO: Python bindings (add later) - # "qdp-python", + "qdp-python", ] resolver = "2" @@ -25,5 +24,3 @@ cc = "1.2" thiserror = "2.0" # Parallel computing (for CPU preprocessing) rayon = "1.10" - - diff --git a/qdp/qdp-core/.gitignore b/qdp/qdp-core/.gitignore index 8b1378917..e69de29bb 100644 --- a/qdp/qdp-core/.gitignore +++ b/qdp/qdp-core/.gitignore @@ -1 +0,0 @@ - diff --git a/qdp/qdp-core/src/dlpack.rs b/qdp/qdp-core/src/dlpack.rs index cd05cb696..b31ba0603 100644 --- a/qdp/qdp-core/src/dlpack.rs +++ b/qdp/qdp-core/src/dlpack.rs @@ -59,7 +59,7 @@ pub struct DLManagedTensor { // Deleter: frees memory when PyTorch is done /// Called by PyTorch to free tensor memory -/// +/// /// # Safety /// Frees shape, strides, GPU buffer, and managed tensor. /// Caller must ensure the pointer is valid and points to a properly initialized DLManagedTensor. @@ -70,7 +70,7 @@ pub unsafe extern "C" fn dlpack_deleter(managed: *mut DLManagedTensor) { } let tensor = &(*managed).dl_tensor; - + // 1. Free shape array (Box<[i64]>) if !tensor.shape.is_null() { let len = if tensor.ndim > 0 { tensor.ndim as usize } else { 1 }; @@ -97,9 +97,9 @@ pub unsafe extern "C" fn dlpack_deleter(managed: *mut DLManagedTensor) { impl GpuStateVector { /// Convert to DLPack format for PyTorch - /// + /// /// Returns raw pointer for torch.from_dlpack() (zero-copy, GPU memory). - /// + /// /// # Safety /// Freed by DLPack deleter when PyTorch releases tensor. /// Do not free manually. @@ -141,4 +141,3 @@ impl GpuStateVector { Box::into_raw(Box::new(managed)) } } - diff --git a/qdp/qdp-core/src/error.rs b/qdp/qdp-core/src/error.rs index 5c8d4dc75..db57d948d 100644 --- a/qdp/qdp-core/src/error.rs +++ b/qdp/qdp-core/src/error.rs @@ -21,4 +21,3 @@ pub enum MahoutError { /// Result type alias for Mahout operations pub type Result<T> = std::result::Result<T, MahoutError>; - diff --git a/qdp/qdp-core/src/gpu/encodings/amplitude.rs b/qdp/qdp-core/src/gpu/encodings/amplitude.rs index fecaf1dff..761656821 100644 --- a/qdp/qdp-core/src/gpu/encodings/amplitude.rs +++ b/qdp/qdp-core/src/gpu/encodings/amplitude.rs @@ -15,7 +15,7 @@ use cudarc::driver::{CudaSlice, DevicePtr}; use qdp_kernels::launch_amplitude_encode; /// Amplitude encoding: data → normalized quantum amplitudes -/// +/// /// Steps: L2 norm (CPU) → GPU allocation → CUDA kernel (normalize + pad) /// Fast: ~50-100x vs circuit-based methods pub struct AmplitudeEncoder; @@ -56,7 +56,7 @@ impl QuantumEncoder for AmplitudeEncoder { // Calculate L2 norm (parallel on CPU for speed) let norm_sq: f64 = host_data.par_iter().map(|x| x * x).sum(); let norm = norm_sq.sqrt(); - + if norm == 0.0 { return Err(MahoutError::InvalidInput("Input data has zero norm".to_string())); } @@ -94,7 +94,7 @@ impl QuantumEncoder for AmplitudeEncoder { Ok(state_vector) } - + #[cfg(not(target_os = "linux"))] { Err(MahoutError::Cuda("CUDA unavailable (non-Linux)".to_string())) @@ -128,4 +128,3 @@ fn cuda_error_to_string(code: i32) -> &'static str { _ => "Unknown CUDA error", } } - diff --git a/qdp/qdp-core/src/gpu/encodings/angle.rs b/qdp/qdp-core/src/gpu/encodings/angle.rs index 0404599ea..92d7f4e34 100644 --- a/qdp/qdp-core/src/gpu/encodings/angle.rs +++ b/qdp/qdp-core/src/gpu/encodings/angle.rs @@ -31,4 +31,3 @@ impl QuantumEncoder for AngleEncoder { "Angle encoding (not implemented)" } } - diff --git a/qdp/qdp-core/src/gpu/encodings/basis.rs b/qdp/qdp-core/src/gpu/encodings/basis.rs index bd01cbad0..72c0217aa 100644 --- a/qdp/qdp-core/src/gpu/encodings/basis.rs +++ b/qdp/qdp-core/src/gpu/encodings/basis.rs @@ -31,4 +31,3 @@ impl QuantumEncoder for BasisEncoder { "Basis encoding (not implemented)" } } - diff --git a/qdp/qdp-core/src/gpu/encodings/mod.rs b/qdp/qdp-core/src/gpu/encodings/mod.rs index e06b20703..6f6e987ca 100644 --- a/qdp/qdp-core/src/gpu/encodings/mod.rs +++ b/qdp/qdp-core/src/gpu/encodings/mod.rs @@ -43,4 +43,3 @@ pub fn get_encoder(name: &str) -> Result<Box<dyn QuantumEncoder>> { )), } } - diff --git a/qdp/qdp-core/src/gpu/memory.rs b/qdp/qdp-core/src/gpu/memory.rs index e822b183f..be2fe41d0 100644 --- a/qdp/qdp-core/src/gpu/memory.rs +++ b/qdp/qdp-core/src/gpu/memory.rs @@ -11,7 +11,7 @@ pub struct GpuBufferRaw { impl GpuBufferRaw { /// Get raw pointer to GPU memory - /// + /// /// # Safety /// Valid only while GpuBufferRaw is alive pub fn ptr(&self) -> *mut CuDoubleComplex { @@ -20,7 +20,7 @@ impl GpuBufferRaw { } /// Quantum state vector on GPU -/// +/// /// Manages complex128 array of size 2^n (n = qubits) in GPU memory. /// Uses Arc for shared ownership (needed for DLPack/PyTorch integration). /// Thread-safe: Send + Sync @@ -40,7 +40,7 @@ impl GpuStateVector { /// Allocates 2^n complex numbers on GPU (freed on drop) pub fn new(_device: &Arc<CudaDevice>, qubits: usize) -> Result<Self> { let _size_elements = 1 << qubits; - + // Use alloc_zeros for device-side allocation (critical for performance): // - No CPU RAM usage (avoids OOM for large states) // - No PCIe transfer (GPU hardware zero-fill) @@ -51,9 +51,9 @@ impl GpuStateVector { let zeros = vec![CuDoubleComplex { x: 0.0, y: 0.0 }; _size_elements]; let slice = _device.htod_sync_copy(&zeros) .map_err(|e| MahoutError::MemoryAllocation( - format!("Failed to allocate {} bytes of GPU memory (qubits={}): {:?}", - _size_elements * std::mem::size_of::<CuDoubleComplex>(), - qubits, + format!("Failed to allocate {} bytes of GPU memory (qubits={}): {:?}", + _size_elements * std::mem::size_of::<CuDoubleComplex>(), + qubits, e) ))?; @@ -63,7 +63,7 @@ impl GpuStateVector { size_elements: _size_elements, }) } - + #[cfg(not(target_os = "linux"))] { // Non-Linux: compiles but GPU unavailable @@ -72,7 +72,7 @@ impl GpuStateVector { } /// Get raw GPU pointer for DLPack/FFI - /// + /// /// # Safety /// Valid while GpuStateVector or any Arc clone is alive pub fn ptr(&self) -> *mut CuDoubleComplex { diff --git a/qdp/qdp-core/src/gpu/mod.rs b/qdp/qdp-core/src/gpu/mod.rs index 00e990ec2..23c020ea0 100644 --- a/qdp/qdp-core/src/gpu/mod.rs +++ b/qdp/qdp-core/src/gpu/mod.rs @@ -3,4 +3,3 @@ pub mod encodings; pub use memory::GpuStateVector; pub use encodings::{QuantumEncoder, AmplitudeEncoder, AngleEncoder, BasisEncoder, get_encoder}; - diff --git a/qdp/qdp-core/src/lib.rs b/qdp/qdp-core/src/lib.rs index 99b9d5a0a..b8991c2de 100644 --- a/qdp/qdp-core/src/lib.rs +++ b/qdp/qdp-core/src/lib.rs @@ -10,7 +10,7 @@ use crate::dlpack::DLManagedTensor; use crate::gpu::get_encoder; /// Main entry point for Mahout QDP -/// +/// /// Manages GPU context and dispatches encoding tasks. /// Provides unified interface for device management, memory allocation, and DLPack. pub struct QdpEngine { @@ -19,29 +19,29 @@ pub struct QdpEngine { impl QdpEngine { /// Initialize engine on GPU device - /// + /// /// # Arguments /// * `device_id` - CUDA device ID (typically 0) pub fn new(device_id: usize) -> Result<Self> { let device = CudaDevice::new(device_id) .map_err(|e| MahoutError::Cuda(format!("Failed to initialize CUDA device {}: {:?}", device_id, e)))?; - Ok(Self { + Ok(Self { device // CudaDevice::new already returns Arc<CudaDevice> in cudarc 0.11 }) } /// Encode classical data into quantum state - /// + /// /// Selects encoding strategy, executes on GPU, returns DLPack pointer. - /// + /// /// # Arguments /// * `data` - Input data /// * `num_qubits` - Number of qubits /// * `encoding_method` - Strategy: "amplitude", "angle", or "basis" - /// + /// /// # Returns /// DLPack pointer for zero-copy PyTorch integration - /// + /// /// # Safety /// Pointer freed by DLPack deleter, do not free manually. pub fn encode( diff --git a/qdp/qdp-kernels/build.rs b/qdp/qdp-kernels/build.rs index a8b016bf6..007934a71 100644 --- a/qdp/qdp-kernels/build.rs +++ b/qdp/qdp-kernels/build.rs @@ -13,13 +13,13 @@ use std::process::Command; fn main() { // Tell Cargo to rerun this script if the kernel source changes println!("cargo:rerun-if-changed=src/amplitude.cu"); - + // Check if CUDA is available by looking for nvcc let has_cuda = Command::new("nvcc") .arg("--version") .output() .is_ok(); - + if !has_cuda { println!("cargo:warning=CUDA not found (nvcc not in PATH). Skipping kernel compilation."); println!("cargo:warning=This is expected on macOS or non-CUDA environments."); @@ -27,23 +27,23 @@ fn main() { println!("cargo:warning=For production deployment, ensure CUDA toolkit is installed."); return; } - + // Get CUDA installation path // Priority: CUDA_PATH env var > /usr/local/cuda (default Linux location) let cuda_path = env::var("CUDA_PATH") .unwrap_or_else(|_| "/usr/local/cuda".to_string()); - + println!("cargo:rustc-link-search=native={}/lib64", cuda_path); println!("cargo:rustc-link-lib=cudart"); - + // On macOS, also check /usr/local/cuda/lib #[cfg(target_os = "macos")] println!("cargo:rustc-link-search=native={}/lib", cuda_path); - + // Compile CUDA kernels // This uses cc crate's CUDA support to invoke nvcc let mut build = cc::Build::new(); - + build .cuda(true) .flag("-cudart=shared") // Use shared CUDA runtime @@ -63,7 +63,6 @@ fn main() { // .flag("arch=compute_89,code=sm_89") .file("src/amplitude.cu") .compile("kernels"); - + println!("cargo:warning=CUDA kernels compiled successfully"); } - diff --git a/qdp/qdp-kernels/src/amplitude.cu b/qdp/qdp-kernels/src/amplitude.cu index f7bde4d9b..9e4537a71 100644 --- a/qdp/qdp-kernels/src/amplitude.cu +++ b/qdp/qdp-kernels/src/amplitude.cu @@ -17,7 +17,7 @@ extern "C" { /// Launch amplitude encoding kernel (skeleton implementation) -/// +/// /// TODO: Full implementation with: /// - Parallel normalization kernel /// - Coalesced memory access patterns @@ -46,13 +46,13 @@ int launch_amplitude_encode( ) { // Skeleton implementation - ensures FFI linkage is correct // This allows the project to compile and pass CI/CD checks. - // + // // TODO: Implement full CUDA kernel: // 1. Kernel launch with optimal grid/block dimensions // 2. Parallel normalization and complex number construction // 3. Zero-padding for unused state vector elements // 4. Error checking and stream synchronization - + // Suppress unused parameter warnings (parameters will be used in full implementation) (void)input_d; (void)state_d; @@ -60,7 +60,7 @@ int launch_amplitude_encode( (void)state_len; (void)norm; (void)stream; - + // For now, just return success // TODO: Launch actual kernel here return cudaSuccess; @@ -72,4 +72,3 @@ int launch_amplitude_encode( // - launch_iqp_encode (IQP encoding) } // extern "C" - diff --git a/qdp/qdp-kernels/src/lib.rs b/qdp/qdp-kernels/src/lib.rs index 8f1e4b5c2..2f7660f95 100644 --- a/qdp/qdp-kernels/src/lib.rs +++ b/qdp/qdp-kernels/src/lib.rs @@ -25,7 +25,7 @@ unsafe impl cudarc::driver::ValidAsZeroBits for CuDoubleComplex {} unsafe extern "C" { /// Launch amplitude encoding kernel /// Returns CUDA error code (0 = success) - /// + /// /// # Safety /// Requires valid GPU pointers, must sync before freeing pub fn launch_amplitude_encode( @@ -53,4 +53,3 @@ pub extern "C" fn launch_amplitude_encode( ) -> i32 { 999 // Error: CUDA unavailable } - diff --git a/qdp/qdp-python/.gitignore b/qdp/qdp-python/.gitignore new file mode 100644 index 000000000..c8f044299 --- /dev/null +++ b/qdp/qdp-python/.gitignore @@ -0,0 +1,72 @@ +/target + +# Byte-compiled / optimized / DLL files +__pycache__/ +.pytest_cache/ +*.py[cod] + +# C extensions +*.so + +# Distribution / packaging +.Python +.venv/ +env/ +bin/ +build/ +develop-eggs/ +dist/ +eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +include/ +man/ +venv/ +*.egg-info/ +.installed.cfg +*.egg + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt +pip-selfcheck.json + +# Unit test / coverage reports +htmlcov/ +.tox/ +.coverage +.cache +nosetests.xml +coverage.xml + +# Translations +*.mo + +# Mr Developer +.mr.developer.cfg +.project +.pydevproject + +# Rope +.ropeproject + +# Django stuff: +*.log +*.pot + +.DS_Store + +# Sphinx documentation +docs/_build/ + +# PyCharm +.idea/ + +# VSCode +.vscode/ + +# Pyenv +.python-version diff --git a/qdp/qdp-python/Cargo.toml b/qdp/qdp-python/Cargo.toml index ded35bfaa..b6fbbef7e 100644 --- a/qdp/qdp-python/Cargo.toml +++ b/qdp/qdp-python/Cargo.toml @@ -4,10 +4,9 @@ version.workspace = true edition.workspace = true [lib] -name = "mahout" +name = "mahout_qdp" crate-type = ["cdylib"] [dependencies] -pyo3 = { version = "0.23", features = ["abi3-py311"] } +pyo3 = { version = "0.27", features = ["extension-module"] } qdp-core = { path = "../qdp-core" } -cudarc = { workspace = true } diff --git a/qdp/qdp-python/README.md b/qdp/qdp-python/README.md new file mode 100644 index 000000000..f4d7b43b0 --- /dev/null +++ b/qdp/qdp-python/README.md @@ -0,0 +1,49 @@ +# qdp-python + +PyO3 Python bindings for Apache Mahout QDP. + +## Usage + +```python +from mahout_qdp import QdpEngine + +# Initialize on GPU 0 +engine = QdpEngine(0) + +# Encode data +data = [0.5, 0.5, 0.5, 0.5] +dlpack_ptr = engine.encode(data, num_qubits=2, encoding_method="amplitude") +``` + +## Build from source + +```bash +uv sync --extra dev +uv run maturin develop +``` + +## Encoding methods + +- `"amplitude"` - Amplitude encoding +- `"angle"` - Angle encoding +- `"basis"` - Basis encoding + +## Adding new bindings + +1. Add method to `#[pymethods]` in `src/lib.rs`: +```rust +#[pymethods] +impl QdpEngine { + fn my_method(&self, arg: f64) -> PyResult<String> { + Ok(format!("Result: {}", arg)) + } +} +``` + +2. Rebuild: `uv run maturin develop` + +3. Use in Python: +```python +engine = QdpEngine(0) +result = engine.my_method(42.0) +``` diff --git a/qdp/qdp-python/pyproject.toml b/qdp/qdp-python/pyproject.toml new file mode 100644 index 000000000..b109b30fc --- /dev/null +++ b/qdp/qdp-python/pyproject.toml @@ -0,0 +1,32 @@ +[build-system] +requires = ["maturin>=1.10,<2.0"] +build-backend = "maturin" + +[project] +name = "qdp-python" +requires-python = ">=3.11" +classifiers = [ + "Programming Language :: Rust", + "Programming Language :: Python :: Implementation :: CPython", + "Programming Language :: Python :: Implementation :: PyPy", +] +dynamic = ["version"] + +[dependency-groups] +dev = [ + "maturin>=1.10.2", + "patchelf>=0.17.2.4", + "pytest>=9.0.1", + "torch>=2.2,<2.3", +] + +[[tool.uv.index]] +name = "pytorch" +url = "https://download.pytorch.org/whl/cu122"; +explicit = true + +[tool.pytest.ini_options] +testpaths = ["tests"] +markers = [ + "gpu: tests that require GPU (deselect with '-m \"not gpu\"')", +] diff --git a/qdp/qdp-python/src/lib.rs b/qdp/qdp-python/src/lib.rs new file mode 100644 index 000000000..c5490b717 --- /dev/null +++ b/qdp/qdp-python/src/lib.rs @@ -0,0 +1,172 @@ +use pyo3::prelude::*; +use pyo3::exceptions::PyRuntimeError; +use pyo3::ffi; +use qdp_core::QdpEngine as CoreEngine; +use qdp_core::dlpack::DLManagedTensor; + +/// Quantum tensor wrapper implementing DLPack protocol +/// +/// This class wraps a GPU-allocated quantum state vector and implements +/// the DLPack protocol for zero-copy integration with PyTorch and other +/// array libraries. +/// +/// Example: +/// >>> engine = QdpEngine(device_id=0) +/// >>> qtensor = engine.encode([1.0, 2.0, 3.0], num_qubits=2, encoding_method="amplitude") +/// >>> torch_tensor = torch.from_dlpack(qtensor) +#[pyclass] +struct QuantumTensor { + ptr: *mut DLManagedTensor, + consumed: bool, +} + +#[pymethods] +impl QuantumTensor { + /// Implements DLPack protocol - returns PyCapsule for PyTorch + /// + /// This method is called by torch.from_dlpack() to get the GPU memory pointer. + /// The capsule can only be consumed once to prevent double-free errors. + /// + /// Args: + /// stream: Optional CUDA stream pointer (for DLPack 0.8+) + /// + /// Returns: + /// PyCapsule containing DLManagedTensor pointer + /// + /// Raises: + /// RuntimeError: If the tensor has already been consumed + #[pyo3(signature = (stream=None))] + fn __dlpack__<'py>(&mut self, py: Python<'py>, stream: Option<i64>) -> PyResult<Py<PyAny>> { + let _ = stream; // Suppress unused variable warning + if self.consumed { + return Err(PyRuntimeError::new_err( + "DLPack tensor already consumed (can only be used once)" + )); + } + + if self.ptr.is_null() { + return Err(PyRuntimeError::new_err("Invalid DLPack tensor pointer")); + } + + // Mark as consumed to prevent double-free + self.consumed = true; + + // Create PyCapsule using FFI + // PyTorch will call the deleter stored in DLManagedTensor.deleter + // Use a static C string for the capsule name to avoid lifetime issues + const DLTENSOR_NAME: &[u8] = b"dltensor\0"; + + unsafe { + // Create PyCapsule without a destructor + // PyTorch will manually call the deleter from DLManagedTensor + let capsule_ptr = ffi::PyCapsule_New( + self.ptr as *mut std::ffi::c_void, + DLTENSOR_NAME.as_ptr() as *const i8, + None // No destructor - PyTorch handles it + ); + + if capsule_ptr.is_null() { + return Err(PyRuntimeError::new_err("Failed to create PyCapsule")); + } + + Ok(Py::from_owned_ptr(py, capsule_ptr)) + } + } + + /// Returns DLPack device information + /// + /// Returns: + /// Tuple of (device_type, device_id) where device_type=2 for CUDA + fn __dlpack_device__(&self) -> PyResult<(i32, i32)> { + // DLDeviceType::kDLCUDA = 2, device_id = 0 + Ok((2, 0)) + } +} + +impl Drop for QuantumTensor { + fn drop(&mut self) { + // Only free if not consumed by __dlpack__ + // If consumed, PyTorch/consumer will call the deleter + if !self.consumed && !self.ptr.is_null() { + unsafe { + // Call the DLPack deleter to properly free memory + if let Some(deleter) = (*self.ptr).deleter { + deleter(self.ptr); + } + } + } + } +} + +// Safety: QuantumTensor can be sent between threads +// The DLManagedTensor pointer management is thread-safe via Arc in the deleter +unsafe impl Send for QuantumTensor {} +unsafe impl Sync for QuantumTensor {} + +/// PyO3 wrapper for QdpEngine +/// +/// Provides Python bindings for GPU-accelerated quantum state encoding. +#[pyclass] +struct QdpEngine { + engine: CoreEngine, +} + +#[pymethods] +impl QdpEngine { + /// Initialize QDP engine on specified GPU device + /// + /// Args: + /// device_id: CUDA device ID (typically 0) + /// + /// Returns: + /// QdpEngine instance + /// + /// Raises: + /// RuntimeError: If CUDA device initialization fails + #[new] + #[pyo3(signature = (device_id=0))] + fn new(device_id: usize) -> PyResult<Self> { + let engine = CoreEngine::new(device_id) + .map_err(|e| PyRuntimeError::new_err(format!("Failed to initialize: {}", e)))?; + Ok(Self { engine }) + } + + /// Encode classical data into quantum state + /// + /// Args: + /// data: Input data as list of floats + /// num_qubits: Number of qubits for encoding + /// encoding_method: Encoding strategy ("amplitude", "angle", or "basis") + /// + /// Returns: + /// QuantumTensor: DLPack-compatible tensor for zero-copy PyTorch integration + /// + /// Raises: + /// RuntimeError: If encoding fails + /// + /// Example: + /// >>> engine = QdpEngine(device_id=0) + /// >>> qtensor = engine.encode([1.0, 2.0, 3.0, 4.0], num_qubits=2, encoding_method="amplitude") + /// >>> torch_tensor = torch.from_dlpack(qtensor) + /// + /// TODO: Replace Vec<f64> with numpy array input to enable zero-copy reading. + /// Consider using the numpy crate (e.g., PyReadonlyArray1<f64>) for better performance. + fn encode(&self, data: Vec<f64>, num_qubits: usize, encoding_method: &str) -> PyResult<QuantumTensor> { + let ptr = self.engine.encode(&data, num_qubits, encoding_method) + .map_err(|e| PyRuntimeError::new_err(format!("Encoding failed: {}", e)))?; + Ok(QuantumTensor { + ptr, + consumed: false, + }) + } +} + +/// Mahout QDP Python module +/// +/// GPU-accelerated quantum data encoding with DLPack integration. +#[pymodule] +fn mahout_qdp(m: &Bound<'_, PyModule>) -> PyResult<()> { + m.add_class::<QdpEngine>()?; + m.add_class::<QuantumTensor>()?; + Ok(()) +} diff --git a/qdp/qdp-python/tests/test_bindings.py b/qdp/qdp-python/tests/test_bindings.py new file mode 100644 index 000000000..0f7866299 --- /dev/null +++ b/qdp/qdp-python/tests/test_bindings.py @@ -0,0 +1,91 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Simple tests for PyO3 bindings.""" + +import pytest +import mahout_qdp + + +def test_import(): + """Test that PyO3 bindings are properly imported.""" + assert hasattr(mahout_qdp, "QdpEngine") + assert hasattr(mahout_qdp, "QuantumTensor") + + [email protected] +def test_encode(): + """Test encoding returns QuantumTensor (requires GPU).""" + from mahout_qdp import QdpEngine + + engine = QdpEngine(0) + data = [0.5, 0.5, 0.5, 0.5] + qtensor = engine.encode(data, 2, "amplitude") + assert isinstance(qtensor, mahout_qdp.QuantumTensor) + + [email protected] +def test_dlpack_device(): + """Test __dlpack_device__ method (requires GPU).""" + from mahout_qdp import QdpEngine + + engine = QdpEngine(0) + data = [1.0, 2.0, 3.0, 4.0] + qtensor = engine.encode(data, 2, "amplitude") + + device_info = qtensor.__dlpack_device__() + assert device_info == (2, 0), "Expected (2, 0) for CUDA device 0" + + [email protected] +def test_dlpack_single_use(): + """Test that __dlpack__ can only be called once (requires GPU).""" + import torch + from mahout_qdp import QdpEngine + + engine = QdpEngine(0) + data = [1.0, 2.0, 3.0, 4.0] + qtensor = engine.encode(data, 2, "amplitude") + + # First call succeeds - let PyTorch consume it + _ = torch.from_dlpack(qtensor) + + # Second call should fail because tensor was already consumed + qtensor2 = engine.encode(data, 2, "amplitude") + _ = qtensor2.__dlpack__() # Consume the capsule + with pytest.raises(RuntimeError, match="already consumed"): + qtensor2.__dlpack__() + + [email protected] +def test_pytorch_integration(): + """Test PyTorch integration via DLPack (requires GPU and PyTorch).""" + pytest.importorskip("torch") + import torch + from mahout_qdp import QdpEngine + + engine = QdpEngine(0) + data = [1.0, 2.0, 3.0, 4.0] + qtensor = engine.encode(data, 2, "amplitude") + + # Convert to PyTorch tensor using DLPack + torch_tensor = torch.from_dlpack(qtensor) + assert torch_tensor.is_cuda + assert torch_tensor.device.index == 0 + assert torch_tensor.dtype == torch.complex128 + + # Verify shape (2 qubits = 2^2 = 4 elements) + assert torch_tensor.shape == (4,) diff --git a/qdp/qdp-python/uv.lock b/qdp/qdp-python/uv.lock new file mode 100644 index 000000000..07b338f5e --- /dev/null +++ b/qdp/qdp-python/uv.lock @@ -0,0 +1,422 @@ +version = 1 +revision = 3 +requires-python = ">=3.11" + +[[package]] +name = "colorama" +version = "0.4.6" +source = { registry = "https://pypi.org/simple"; } +sdist = { url = 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