This is an automated email from the ASF dual-hosted git repository.
guanmingchiu pushed a commit to branch dev-qdp
in repository https://gitbox.apache.org/repos/asf/mahout.git
The following commit(s) were added to refs/heads/dev-qdp by this push:
new e87682390 [QDP] Add Python bindings for QDP using PyO3 (#649)
e87682390 is described below
commit e87682390aabb3cc5bcf863fd1dfe8d1e78bb146
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 @@
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+
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+
+[[package]]
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+ "memoffset",
+ "once_cell",
+ "portable-atomic",
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+ "unindent",
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+ "heck",
+ "proc-macro2",
+ "pyo3-build-config",
+ "quote",
+ "syn",
+]
+
+[[package]]
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+version = "0.1.0"
+dependencies = [
+ "cudarc",
+ "qdp-kernels",
+ "rayon",
+ "thiserror",
+]
+
+[[package]]
+name = "qdp-kernels"
+version = "0.1.0"
+dependencies = [
+ "cc",
+ "cudarc",
+]
+
+[[package]]
+name = "qdp-python"
+version = "0.1.0"
+dependencies = [
+ "pyo3",
+ "qdp-core",
+]
+
+[[package]]
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+dependencies = [
+ "proc-macro2",
+]
+
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+checksum = "368f01d005bf8fd9b1206fb6fa653e6c4a81ceb1466406b81792d87c5677a58f"
+dependencies = [
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+ "rayon-core",
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+
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+checksum = "22e18b0f0062d30d4230b2e85ff77fdfe4326feb054b9783a3460d8435c8ab91"
+dependencies = [
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+ "crossbeam-utils",
+]
+
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+ "unicode-ident",
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+
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+checksum = "f63587ca0f12b72a0600bcba1d40081f830876000bb46dd2337a3051618f4fc8"
+dependencies = [
+ "thiserror-impl",
+]
+
+[[package]]
+name = "thiserror-impl"
+version = "2.0.17"
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+ "proc-macro2",
+ "quote",
+ "syn",
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+
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+
+[[package]]
+name = "unindent"
+version = "0.2.4"
+source = "registry+https://github.com/rust-lang/crates.io-index";
+checksum = "7264e107f553ccae879d21fbea1d6724ac785e8c3bfc762137959b5802826ef3"
+
+[[package]]
+name = "windows-link"
+version = "0.2.1"
+source = "registry+https://github.com/rust-lang/crates.io-index";
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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"
+
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+name = "filelock"
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