[ET-VK][qconv] Add layout-flexible impl of quantized depthwise conv2d

[SS-JIA]

Stack from ghstack (oldest at bottom):

• [ET-VK][qconv] Add flexible layout impl for quantized pointwise conv #17221
• [ET-VK][testing] Create dedicated test binary for pointwise convolutions #17220
• [ET-VK][qconv] Add layout-agnostic general shader for quantized conv #17219
• [ET-VK][quantization] Add layout-flexible clone for int8x4 tensors #17171
• -> [ET-VK][qconv] Add layout-flexible impl of quantized depthwise conv2d #17108
• [ET-VK][ez] Implement helper functions to get fastest moving dim #17107
• [ET-VK][quantization] Implement layout-flexible quantize/dequantize operators #17106
• [ET-VK] Add alignment fields to PackedDimInfo for padded size calculation #17170
• [ET-VK][testing] Add per-shader timing breakdown to benchmark output #17105

Adds a new layout-agnostic quantized depthwise convolution operator
etvk.q8ta_conv2d_dw that uses BufferMetadata and layout specialization
constants to support arbitrary memory layouts (contiguous, channels-last,
4W4C block-packed, etc.).

Key changes:

1. New shader q8ta_conv2d_dw.glsl:

   • Uses BufferMetadata for input/output tensor addressing
   • Layout-aware via inp_layout/outp_layout specialization constants
   • Processes 4 adjacent width positions × 4 channels per thread (4Wx4C tile)
   • Includes optimized paths for simple layouts (outer_block_size == 1)

2. New indexing utilities in indexing.glslh:

   • texel_idx_to_tensor4d_idx(): converts linear texel index to 4D tensor coords
   • tensor4d_idx_to_texel_idx(): converts 4D tensor index to texel index

3. Code refactoring:

   • Extract Conv2DParams struct and create_conv2d_params() to ConvolutionUtils.h
   • Create Q8taConv2dDW.cpp with new operator implementation
   • Add Q8taConv2d.h with public API declarations
   • Move prepack_quantized_conv2d_dw_weight() to new implementation file

4. New workgroup size helpers:

   • pick_q8ta_conv2d_dw_global_wg_size(): computes {W4, H, C4} dispatch size
   • pick_q8ta_conv2d_dw_local_wg_size(): adaptive local size based on tensor dims

5. Test updates:

   • Rename test to test_q8_conv2d_dw.cpp
   • Add TestQ8taConv2d.cpp with shared test utilities

Differential Revision: D92061368

[pytorch-bot]

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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/17108

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❌ 4 New Failures, 1 Pending, 1 Unrelated Failure

As of commit f77a947 with merge base 477867a ():

NEW FAILURES - The following jobs have failed:

• pull / test-multimodal-linux (gemma3-4b) / linux-job (gh)
  RuntimeError: Command docker exec -t a95b8de30f54fa93480a4fff57a8f7baef9e88c2c9dc9e1e2c8f5a13523878bc /exec failed with exit code 139
• pull / test-vulkan-operators-linux / linux-job (gh)
  RuntimeError: Command docker exec -t 22bf7743c7b2e1df7fec25fed48d07178415f543fcfe4d42a4908d070b95e7b0 /exec failed with exit code 134
• Test CUDA Builds / export-model-cuda-artifact (openai, whisper-small, quantized-int4-weight-only) / linux-job (gh)
  RuntimeError: Command docker exec -t b44405e0be4e6500f2053bd83d87d6ac542a584928d7978dd93ace00882f189d /exec failed with exit code 1
• Test CUDA Windows Export / export-model-cuda-windows-artifact (mistralai, Voxtral-Mini-3B-2507, non-quantized) / linux-job (gh)
  RuntimeError: Command docker exec -t 8e584969f471bdfeac62787582c3bc3f1a9b4ac3f06bbf15ea61144bc5f4027a /exec failed with exit code 1

BROKEN TRUNK - The following job failed but were present on the merge base:

👉 Rebase onto the `viable/strict` branch to avoid these failures

• pull / test-samsung-quantmodels-linux / linux-job (gh) (trunk failure)
  ##[error]The operation was canceled.

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