[WIP] Add standalone batch norm support via depthwise conv conversion.

[ayushrajdahal]

Summary

Implement ConvertBatchNormToDepthwiseConvPass to handle standalone batch normalization operations that cannot be fused with preceding convolutions.

Fixes #11586

Key changes:

• New pass converts standalone BatchNorm to equivalent 1x1 depthwise convolutions
• Updated BatchNormConfig to support both fusable and standalone batch norms
• Added pass to XNNPACKPassManager before existing fusion pass
• Updated tests to expect successful partitioning of standalone batch norms

Uses mathematical equivalence:
conv_weight = bn_weight / sqrt(bn_var + eps)
conv_bias = bn_bias - bn_mean * conv_weight

Test plan

# test fused batch norm
python -m pytest backends/xnnpack/test/passes/test_batch_norm_fusion.py -v

# for standalone batch norm
python -m pytest backends/xnnpack/test/passes/test_batch_norm_to_depthwise_conv.py -v

[pytorch-bot]

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As of commit 3a62512 with merge base daebcde ():
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[keyprocedure]

Hi @penknife6153, I worked on the linear fused batchnorm PR and noticed some overlap between our work. Let me know if I can help with anything!

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