[
https://issues.apache.org/jira/browse/MAHOUT-878?focusedWorklogId=1000974&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-1000974
]
ASF GitHub Bot logged work on MAHOUT-878:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 20/Jan/26 12:05
Start Date: 20/Jan/26 12:05
Worklog Time Spent: 10m
Work Description: CheyuWu commented on code in PR #881:
URL: https://github.com/apache/mahout/pull/881#discussion_r2708070502
##########
qdp/qdp-python/src/lib.rs:
##########
@@ -321,6 +460,78 @@ impl QdpEngine {
// Check if it's a PyTorch tensor
if is_pytorch_tensor(data)? {
+ // Check if it's a CUDA tensor - use zero-copy GPU encoding
+ if is_cuda_tensor(data)? {
+ // Validate CUDA tensor for direct GPU encoding
+ validate_cuda_tensor_for_encoding(
+ data,
+ self.engine.device().ordinal(),
+ encoding_method,
+ )?;
+
+ // Extract GPU pointer via DLPack
+ let dlpack_info = extract_dlpack_tensor(data.py(), data)?;
+
+ let ndim: usize = data.call_method0("dim")?.extract()?;
+
+ match ndim {
+ 1 => {
+ // 1D CUDA tensor: single sample encoding
+ let input_len = dlpack_info.shape[0] as usize;
+ // SAFETY: dlpack_info.data_ptr was validated via
DLPack protocol from a
+ // valid PyTorch CUDA tensor. The tensor remains alive
during this call
+ // (held by Python's GIL), and we validated
dtype/contiguity/device above.
+ let ptr = unsafe {
+ self.engine
+ .encode_from_gpu_ptr(
+ dlpack_info.data_ptr,
+ input_len,
+ num_qubits,
+ encoding_method,
+ )
+ .map_err(|e| {
+ PyRuntimeError::new_err(format!("Encoding
failed: {}", e))
+ })?
+ };
+ return Ok(QuantumTensor {
+ ptr,
+ consumed: false,
+ });
+ }
+ 2 => {
+ // 2D CUDA tensor: batch encoding
+ let num_samples = dlpack_info.shape[0] as usize;
+ let sample_size = dlpack_info.shape[1] as usize;
+ // SAFETY: Same as above - pointer from validated
DLPack tensor
+ let ptr = unsafe {
+ self.engine
+ .encode_batch_from_gpu_ptr(
+ dlpack_info.data_ptr,
+ num_samples,
+ sample_size,
+ num_qubits,
+ encoding_method,
+ )
+ .map_err(|e| {
+ PyRuntimeError::new_err(format!("Encoding
failed: {}", e))
+ })?
+ };
+ return Ok(QuantumTensor {
+ ptr,
+ consumed: false,
+ });
+ }
+ _ => {
+ return Err(PyRuntimeError::new_err(format!(
+ "Unsupported CUDA tensor shape: {}D. Expected 1D
tensor for single \
+ sample encoding or 2D tensor (batch_size,
features) for batch encoding.",
+ ndim
+ )));
+ }
+ }
+ }
+
+ // CPU tensor path (existing code)
validate_tensor(data)?;
Review Comment:
I think we don't need this anymore
Issue Time Tracking
-------------------
Worklog Id: (was: 1000974)
Time Spent: 1h 40m (was: 1.5h)
> Provide better examples for the parallel ALS recommender code
> -------------------------------------------------------------
>
> Key: MAHOUT-878
> URL: https://issues.apache.org/jira/browse/MAHOUT-878
> Project: Mahout
> Issue Type: Task
> Affects Versions: 1.0.0
> Reporter: Sebastian Schelter
> Assignee: Sebastian Schelter
> Priority: Major
> Fix For: 0.6
>
> Attachments: MAHOUT-878.patch
>
> Time Spent: 1h 40m
> Remaining Estimate: 0h
>
> We should provide examples that show how to apply the parallel ALS
> recommender to the Netflix or KDD2011 datasets.
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