Add fp8 quantization for conv and linear layers #277
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rsuderman
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nithinsubbiah
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This reverts commit ec5672e.
| @@ -80,7 +80,7 @@ def generate(self, ksel: KernelSelection, kb: KernelBuilder): | |||
| spec_sig = f"L{a_ident}_R{b_ident}" | |||
| template_file = "batch_matmul_transpose_b.mlir" | |||
| target_function_name = f"sharktank_batch_matmul_transpose_b_{spec_sig}" | |||
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| cst_zero = "0." if "f" in str(accum_type) else "0" | |||
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Be specific. Don't just use stringy char-in-str.
In this case, I think you can say something like:
cst_zero = "0" if IntegerType.isa(accum_type) else "0."
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This is a follow-up to (#202) which injects fp8 linear and convolution kernels in punet.