Add conv fp16 kernel in xnnpack EP #22301
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added 2 commits
October 3, 2024 13:37
added 3 commits
October 4, 2024 03:01
skottmckay
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Oct 4, 2024
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| const float output_min = -65504.0; | ||
| const float output_max = 65504.0; |
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Where are these values coming from? I would have expected we use something based on foutput_min/foutput_max so any clip parameters (from a fusion of two nodes) are honoured.
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It's calculated by FP16 format, 1 sign bit, 5 exponent bits and 11 mantissa bits.
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I just checked that tensorflow is using 65504 directly
# Note 65504. is the max float16 value.
if scores.dtype is dtypes.float16:
scores -= 65504. * math_ops.cast(padding_mask, dtype=scores.dtype)
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And it looks that we can't get the FP16 max/min value by std::numeric_limits like u8s8
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updated to const auto output_min = clip_min_max ? onnxruntime::math::floatToHalf(clip_min_max->first) : -65504.0;
added 7 commits
October 4, 2024 09:02
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Description
Add FP16 kernels of Conv and ConvTranspose
Motivation and Context