Fix memory access violations in the CPU float16 min and max operators #22135
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This makes min and max with NaN for either operand always return NaN for float16 data, matching the behaviour of float and double. The behaviour for floats and doubles was previously fixed for the CPU provider in #21492 and the CUDA provider in #19984, but these PRs didn't fix the behaviour for float16 due to tests causing asan errors. The memory access violations with float16 data have now been fixed in #22135, so this PR is a follow up to make float16 min and max behave the same as float and double for both the CPU and CUDA providers now that we can add tests for this. ### Motivation and Context Relevant previous issues (not float16 specific): * #21455 * onnx/onnx#6003
Description
Fixes the logic for getting the number of elements for the input and output spans in the
MinMaxMLFloat16method. This was incorrectly using the full number of elements in the output rather than the number of elements in the current span, which worked fine with 1D inputs but breaks with 2D inputs.This meant that as the
BroadcastLooperiterated over spans,MinMaxMLFloat16would start at a position further forward in the input and output and read and write further beyond the end of the input and output respectively, causing the asan error in #21558 and sometimes segfaults in larger examples.Motivation and Context
Fixes #21558.
From further testing, this issue didn't only cause asan errors in tests but causes segfaults with larger sized inputs.