[fedonman]

Replaces the 14 remaining assert statements in cuda_core/cuda/core with explicit errors, following the rules in the issue: a value from a caller, a DLPack or CAI producer, or an NVML payload raises ValueError or TypeError naming the value, and an internal invariant raises the "internal cuda.core error, please report" RuntimeError. The assert False in view_as_dlpack gets a ValueError instead, since a producer reaches it by returning anything other than an unconsumed capsule. S101 is enforced for cuda_core/cuda/core/** only, because enabling it everywhere outside tests/ flags about 180 asserts in pathfinder, the samples and the test helpers. The two in _ipc.pyx stay with #2704.

Closes #3202

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[coderabbitai]

📝 Summary

Summary by CodeRabbit

• Bug Fixes
  • Invalid CUDA contexts, streams, memory locations, and program options now produce clear exceptions instead of assertion failures.
  • DLPack and CUDA Array Interface inputs receive explicit validation, with invalid device IDs, capsules, and producer streams reported as ValueError.
  • Invalid device power states and event or field data with unexpected counts now raise ValueError, including when Python assertions are disabled.
  • Additional invalid inputs, such as unsupported code types, are reported with specific exceptions.

The PR replaces assertions with explicit exceptions across CUDA device, memory, interop, program-cache, and system code. It adds tests for several invalid inputs and changes Ruff’s S101 ignore configuration.

Changes: Library assertion replacements

Layer / File(s)	Summary
CUDA and interop validation cuda_core/cuda/core/_device.pyx, cuda_core/cuda/core/_memory/*, cuda_core/cuda/core/_memoryview.pyx, cuda_core/tests/test_memory.py, cuda_core/tests/test_utils.py, cuda_core/tests/test_utils_dlpack.py, ruff.toml	Device, memory, and interop checks now raise explicit exceptions for invalid states or inputs. Tests cover invalid stream types, DLPack device IDs and capsules, and CUDA Array Interface stream values. Ruff’s global S101 ignore is removed, with a per-file ignore added for cuda_core/cuda/core/**.
Program and cache checks cuda_core/cuda/core/_module.pyx, cuda_core/cuda/core/_program.pyx, cuda_core/cuda/core/utils/_program_cache/*, cuda_core/tests/test_module.py	Unsupported code types, missing architecture values, and missing program-cache exceptions now raise explicit errors. A test checks rejection of an unsupported code type.
System value validation cuda_core/cuda/core/system/_device.pyx, cuda_core/cuda/core/system/_field_values.pxi, cuda_core/cuda/core/system/_system_events.pyx, cuda_core/tests/system/*	P-state bounds, field-value count, and event count checks now raise explicit errors. Tests check rejection of multiple field values and events.

Assessment against linked issues

Objective	Addressed	Explanation
Replace the remaining library assertions with explicit errors [#3202]	✅
Enable Ruff S101 for library code and limit the per-file ignore to tests [#3202]	❌	The per-file ignore applies to cuda_core/cuda/core/**, so Ruff still ignores S101 for library code.

Possibly related PRs

• NVIDIA/cuda-python#3222: Its tests overlap this PR’s coverage of invalid code types, stream types, and DLPack validation.

Suggested labels: bug, cuda.core

Suggested reviewers: mdboom, andy-jost, cpcloud

Priority: Normal

Change: Bug fix

Merge Risk: Low · up to 35983

A failing test may leave a managed resource alive and cause subsequent CUDA test teardown failures; add explicit cleanup.

Finishing Touches: 💡 1

🛠️ Fix failing CI checks: 💡

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[coderabbitai]

Actionable comments posted: 1

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Review info

Run configuration

• Source mode: Auto
• Repository: NVIDIA/cuda-python
• Branch: main
• File: .coderabbit.yaml
• Commit: a2fb804
• Layers: Repository YAML
• Review profile: CHILL
• Plan: Enterprise
• Run ID: 80a8bc3b-f982-42c6-b3de-45e71db0863c

Commits

Reviewing files that changed from the base of the PR and between a2fb804 and 35983fa.

Files selected for processing: 18

• cuda_core/cuda/core/_device.pyx
• cuda_core/cuda/core/_memory/_managed_buffer.py
• cuda_core/cuda/core/_memory/_managed_memory_resource.pyx
• cuda_core/cuda/core/_memoryview.pyx
• cuda_core/cuda/core/_module.pyx
• cuda_core/cuda/core/_program.pyx
• cuda_core/cuda/core/system/_device.pyx
• cuda_core/cuda/core/system/_field_values.pxi
• cuda_core/cuda/core/system/_system_events.pyx
• cuda_core/cuda/core/utils/_program_cache/_file_stream.py
• cuda_core/cuda/core/utils/_program_cache/_keys.py
• cuda_core/tests/system/test_system_device.py
• cuda_core/tests/system/test_system_events.py
• cuda_core/tests/test_memory.py
• cuda_core/tests/test_module.py
• cuda_core/tests/test_utils.py
• cuda_core/tests/test_utils_dlpack.py
• ruff.toml

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[coderabbitai]

Minor · Stability & Availability · Quick win

important: Close the owned managed memory resource. ManagedMemoryResourceOptions(...) creates an owned pool, but the finally block closes only gb. If the assertion fails and pytest retains the test frame, mr can remain live through fixture teardown and trigger an unreleased-resource failure. Close mr in a finally block that also covers graph-builder creation. As per coding guidelines, “Release what you construct regardless”. As per path instructions, “Release constructed resources; use context managers where suitable”.

Sources: Coding guidelines, Path instructions