[ET-VK] Do not partition batch norm on a non-4d input

[msluszniak]

Summary

add_native_batch_norm_node() asserts on both the input and the output sizes:

VK_CHECK_COND(in_sizes.size() == 4, "BatchNorm only support 4d tensor");
VK_CHECK_COND(out_sizes.size() == 4, "BatchNorm only support 4d tensor");

but the partitioner claims _native_batch_norm_legit_no_training at any rank. A batch norm on rank-3 activations, which is every conv1d model, therefore lowers cleanly and aborts at execute time rather than falling back.

This declines the node when the input is not 4d, following the existing _check_copy_is_noop / check_conv_node precedent.

Split out of #22399, which is now scoped to constant_pad_nd.

cc @SS-JIA @manuelcandales @digantdesai @cbilgin

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