[GPU] Revert jit::gemm handling for f32 src, f16 fpmath

[kealan-barbieri]

Description

Revert to sending cases with f32 activations, fp16 fpmath setting to ref, as these cases cause additional register pressure from f32->f16 reorder that isnt supported by f16 gemm strategies:

onednn_verbose,v1,info,oneDNN v3.7.0 (commit 80b61e36646c9d1ab64d439a5bf1ea0966c6f0d9)
onednn_verbose,v1,info,cpu,runtime:OpenMP,nthr:224
onednn_verbose,v1,info,cpu,isa:Intel AVX-512 with float16, Intel DL Boost and bfloat16 support 
onednn_verbose,v1,info,gpu,runtime:OpenCL
onednn_verbose,v1,info,gpu,engine,opencl device count:1 
onednn_verbose,v1,info,gpu,engine,0,name:Intel(R) Data Center GPU Max 1100,driver_version:24.39.31294,binary_kernels:enabled
onednn_verbose,v1,info,experimental features are enabled
onednn_verbose,v1,info,use batch_normalization stats one pass is enabled
onednn_verbose,v1,info,GPU convolution v2 is disabled
onednn_verbose,v1,primitive,info,template:operation,engine,primitive,implementation,prop_kind,memory_descriptors,attributes,auxiliary,problem_desc,exec_time
onednn_verbose,v1,primitive,error,gpu,jit::gemm,Insufficient registers in requested bundle,src/gpu/intel/jit/gemm/gen_gemm_kernel.cpp:959
Error: Function 'create_primitive' at (/nfs/pdx/home/skazakov/hal9000_skazakov/DNNL_JIRA/oneDNN/tests/benchdnn/dnnl_common.hpp:422) returned 'runtime_error'
Error: Function 'init_prim' at (/nfs/pdx/home/skazakov/hal9000_skazakov/DNNL_JIRA/oneDNN/tests/benchdnn/dnnl_common.hpp:475) returned '1'
Error: Function 'createit' at (/nfs/pdx/home/skazakov/hal9000_skazakov/DNNL_JIRA/oneDNN/tests/benchdnn/matmul/matmul.cpp:884) returned '1'
Error: Function 'create' at (/nfs/pdx/home/skazakov/hal9000_skazakov/DNNL_JIRA/oneDNN/tests/benchdnn/utils/task.hpp:49) returned '1'
0:UNTESTED_FAILED __REPRO: --matmul --engine=gpu --allow-enum-tags-only=false --dt=f32:u8:f32 --stag=ab --wtag=ba --dtag=ab --bia_dt=f32 --attr-scales=wei:per_oc --attr-zero-points=wei:per_oc:u8 --attr-scratchpad=user --attr-fpmath=f16:true 16384x512:512x512

Similar cases should use --fpmath=strict:true to leverage f32 jit:gemm strategies.

Fixes # MFDNN-13045

Checklist

General

• Do all unit and benchdnn tests (make test and make test_benchdnn_*) pass locally for each commit?
• Have you formatted the code using clang-format?

Bug fixes

• Have you included information on how to reproduce the issue (either in a github issue or in this PR)?
• Have you added relevant regression tests?

[rjoursler]

The issue in the given case is that we should be matching the f32 input against [SB] and [SH], not B and H. Can we just extend the lambda inputs to add_mode_matches and drop these if statements? The add_mode_matches function already adds all matching strategy conversions.