[WebNN] Support AveragePool with count_include_pad == 1

[Honry]

Description

WebNN doesn't support AveragePool with count_include_pad == 1.

Motivation and Context

Support it by adding a pad and calling averagePool2D with pads as 0's.

[Honry]

@fdwr, @guschmue, PTAL, thanks!

[fdwr]

/azp run ONNX Runtime Web CI Pipeline,Windows GPU CI Pipeline,Linux Android Emulator QNN CI Pipeline,Windows GPU WebGPU CI Pipeline,Windows OpenVINO CI Pipeline

[fdwr]

/azp run Linux CPU CI Pipeline,Linux CPU Minimal Build E2E CI Pipeline,Linux GPU CI Pipeline,Linux GPU TensorRT CI Pipeline,Linux OpenVINO CI Pipeline,Linux QNN CI Pipeline,MacOS CI Pipeline,Windows ARM64 QNN CI Pipeline,Windows CPU CI Pipeline

[fdwr]

/azp run Windows GPU CUDA CI Pipeline,Windows GPU DML CI Pipeline,Windows GPU Doc Gen CI Pipeline,Win_TRT_Minimal_CUDA_Test_CI

[fdwr]

/azp run Windows GPU TensorRT CI Pipeline,onnxruntime-binary-size-checks-ci-pipeline,orttraining-linux-ci-pipeline,orttraining-linux-gpu-ci-pipeline,orttraining-ortmodule-distributed,Windows x64 QNN CI Pipeline,Big Models

[azure-pipelines]

Azure Pipelines successfully started running 1 pipeline(s).

[azure-pipelines]

Azure Pipelines successfully started running 2 pipeline(s).

[azure-pipelines]

Azure Pipelines successfully started running 3 pipeline(s).

[azure-pipelines]

Azure Pipelines successfully started running 3 pipeline(s).

[fdwr]

👍

[fdwr]

Completing despite the 5 test failures above which keep failing in this PR and others, as they are unrelated (and not required either):

• Big Models
• Big Models (Build_Onnxruntime_Cuda Linux_Build)
• Big Models (Llama2_7B_ONNX Llama2_7B_ONNX)
• Linux CPU Minimal Build E2E CI Pipeline
• onnxruntime-binary-size-checks-ci-pipeline

e.g.

#2 [internal] load metadata for onnxruntimebuildcache.azurecr.io/internal/azureml/onnxruntime/build/cpu_x64_ubi8_gcc14_dotnet:20250124.1
#2 ERROR: failed to authorize: failed to fetch anonymous token

https://dev.azure.com/onnxruntime/onnxruntime/_build/results?buildId=1669389&view=logs&j=c0b799d6-18b6-56f3-32a9-d967e9a2810f&t=9c614e8a-74a4-58bb-cc51-8d2510ee34f2&l=19