[slimtensor] Add utility functions to common_shims_slim

[Gasoonjia]

Stack from ghstack (oldest at bottom):

• rename slimtensor fiies to consistent with executorch files #16469
• -> [slimtensor] Add utility functions to common_shims_slim #16457
• [slimtensor] Add storage and device property getters to common_shims_slim #16455
• [slimtensor] Add common_shims_slim with basic property getters #16454
• [slimtensor] Add aoti_torch_item_bool for SlimTensor #16453
• [slimtensor] Add aoti_torch_assign_tensors_out for SlimTensor #16452
• [slimtensor] Add aoti_torch_copy_ for SlimTensor #16451
• [slimtensor] Add aoti_torch__reinterpret_tensor for SlimTensor #16450
• [slimtensor] Add aoti_torch_new_tensor_handle for SlimTensor #16449
• [slimtensor] Add aoti_torch_delete_tensor_object for SlimTensor #16448
• [slimtensor] Add SlimTensor-based aoti_torch_empty_strided #16447
• [slimtensor] Add SlimTensor-based aoti_torch_create_tensor_from_blob_v2 #16446
• [slimtensor] Add item() methods with CUDA and CPU support for scalar value extraction #16445
• [slimtensor] Add permute() and reshape() view operations #16444
• [slimtensor] Add as_strided() view operation for tensor reinterpretation #16443
• [slimtensor] Add from_blob() factory function for wrapping external memory #16442
• [slimtensor] Add non-owning storage mode for wrapping external memory #16441
• [slimtensor] Enable CUDA tensor copy #16440
• [slimtensor] Add CUDA slimtensor creation with basic functionality #16439
• [slimtensor] Add CUDA Storage with DeviceTraits and memory allocation #16438
• [slimtensor] Add CUDA DeviceType and extend Device class #16437
• [slimtensor] Add all required dtype support (Int8/16/32/64, Bool, BFloat16) #16399
• [slimtensor] Add factory functions for creating empty CPU tensors #16398
• [slimtensor] Add SlimTensor class with basic properties and CPU copy operation #16385
• [slimtensor] Add SizesAndStrides and dimension utility functions for slimtensor usage #16384
• [slimtensor] Storage and SharedPtr for CPU owning mode #16383
• [slimtensor] Introduce Device and ScalarType headers for SlimTensor minimal support #16382

Add utility functions to the header-only common_shims_slim library:

1. DType constants:

   • aoti_torch_dtype_float32() - Returns 6 (ScalarType::Float)
   • aoti_torch_dtype_bfloat16() - Returns 15 (ScalarType::BFloat16)
   • aoti_torch_dtype_int64() - Returns 4 (ScalarType::Long)
   • aoti_torch_dtype_int32() - Returns 3 (ScalarType::Int)
   • aoti_torch_dtype_int16() - Returns 2 (ScalarType::Short)
   • aoti_torch_dtype_int8() - Returns 1 (ScalarType::Char)
   • aoti_torch_dtype_bool() - Returns 11 (ScalarType::Bool)

2. Device type constants:

   • aoti_torch_device_type_cpu() - Returns 0 (DeviceType::CPU)
   • aoti_torch_device_type_cuda() - Returns 1 (DeviceType::CUDA)

3. Grad mode functions (not supported in ExecuTorch):

   • aoti_torch_grad_mode_is_enabled() - Always returns false
   • aoti_torch_grad_mode_set_enabled() - Returns Ok for false, NotSupported for true

Differential Revision: D90126250

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/16457

• 📄 Preview Python docs built from this PR

Note: Links to docs will display an error until the docs builds have been completed.

❗ 1 Active SEVs

There are 1 currently active SEVs. If your PR is affected, please view them below:

• B200 runners are down due to network issues

❌ 6 New Failures, 5 Unrelated Failures

As of commit be66d01 with merge base fd6fa87 ():

NEW FAILURES - The following jobs have failed:

• pull / test-samsung-models-linux / linux-job (gh)
  RuntimeError: Command docker exec -t d3139101a17e0eb0194bc628211bb92202ad3b262f0360b639d1c0be33749dae /exec failed with exit code 1
• pull / unittest-arm-backend-with-no-fvp (test_pytest_ops) / linux-job (gh)
  RuntimeError: Command docker exec -t 2725ba3e89f5a27dbaf8c14bddc963119fa14aea92e159d74dbaa07714bf7517 /exec failed with exit code 1
• Test CUDA Builds / check-all-cuda-builds (gh)
  Process completed with exit code 1.
• Test CUDA Builds / export-model-cuda-artifact (mistralai, Voxtral-Mini-3B-2507, quantized-int4-tile-packed) / linux-job (gh)
  RuntimeError: Command docker exec -t 4c49ff042887d0b3765895f516e15a6ad22eeff9d1b6adc60721668d5aa793c7 /exec failed with exit code 1
• Test CUDA Builds / export-model-cuda-artifact (mistralai, Voxtral-Mini-3B-2507, quantized-int4-weight-only) / linux-job (gh)
  RuntimeError: Command docker exec -t 46e00d10acc9f19c51d4c8f73fa3cada79b997a95bf00af4e87ea2c3b1ff578b /exec failed with exit code 1
• Test CUDA Builds / test-executorch-cuda-build-12.6 / linux-job (gh)
  RuntimeError: Command docker exec -t e131ab4246c84c2d60c018f479e2ed1d20ba851028f408a7aef79633d90a28e0 /exec failed with exit code 1

FLAKY - The following jobs failed but were likely due to flakiness present on trunk:

• pull / test-models-linux (linear, xnnpack-quantization-delegation, linux.2xlarge) / linux-job (gh) (detected as infra flaky with no log or failing log classifier)
• pull / test-models-linux (resnet18, portable, linux.2xlarge) / linux-job (gh) (matched linux rule in flaky-rules.json)
  The runner has received a shutdown signal. This can happen when the runner service is stopped, or a manually started runner is canceled.
• pull / test-samsung-quantmodels-linux / linux-job (gh) (matched linux rule in flaky-rules.json)
  The runner has received a shutdown signal. This can happen when the runner service is stopped, or a manually started runner is canceled.
• pull / test-vulkan-models-linux / linux-job (gh) (matched linux rule in flaky-rules.json)
  The runner has received a shutdown signal. This can happen when the runner service is stopped, or a manually started runner is canceled.

UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:

• pull / android / run-emulator (gh) (#16137)
  Timeout waiting for emulator to boot.

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[github-actions]

This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.