# int8
--reset
--cfg=s8s8s8 --attr-oscale=per_oc:2.25 16x512:512x256:16x256

# int8 post bias+relu
--reset
--cfg=s8s8s8
--bia_dt=f32
--bia_mask=2
--attr-post-ops=eltwise_relu
--attr-oscale=per_oc
128x512:512x256:128x256

# int8 asym matmul
--reset
--cfg=u8s8u8
--attr-oscale=per_oc:2.25
--attr-zero-points=dst:common:3+src:common:2
10x10x15x30:10x10x30x15:10x10x15x15

# int8 post sum with scale, zp
--reset
--cfg=s8s8s8
--attr-oscale=per_oc:2.25 --attr-post-ops=sum:0.03:3 16x512:512x256:16x256

# int8 post relu with scale
--reset
--cfg=u8s8u8
--attr-post-ops=relu:0:0:1.2,relu:0.25:0:1.2 16x512:512x256:16x256

# x8s8f32 cases
--reset
--cfg=u8s8f32
--bia_dt=undef,f32
--attr-oscale=per_oc:2.25
# sum:1:0:s8 case will not work in --api=P due to sum_src_dt == dst_dt restriction
# oneDNN graph is not limited by it, because of additional reorder
# gelu_erf needs to be enabled below when the correctness issue will be addressed
--attr-post-ops=,relu,logistic,sum:1:0:s8,add:f32
--batch=shapes_int8_2d

--reset
--cfg=u8s8f32
--bia_dt=undef
--attr-oscale=per_oc:2.25
--attr-post-ops=div:f32,div:f32+add:f32 16x512:512x256:16x256

# x8s8bf16 - matmul + bias
--reset
--cfg=u8s8bf16
--bia_dt=bf16
--attr-oscale=per_oc:2.25
--batch=shapes_int8_2d

# x8s8bf16 - matmul + div
--reset
--cfg=u8s8bf16
--bia_dt=undef
--attr-oscale=per_oc:2.25
--attr-post-ops=,div:bf16
--batch=shapes_int8_2d

# x8s8bf16 - matmul + add
--reset
--cfg=u8s8bf16 
--attr-oscale=per_oc:2.25 
--attr-post-ops=add:bf16 
16x13:13x512:16x512

#x8s8bf16 - matmul + several binary post-ops
--reset
--cfg=u8s8bf16 
--attr-oscale=per_oc:2.25 
--attr-post-ops=div:bf16+add:bf16 
16x13:13x512:16x512

# int8 + several binary post-ops
--reset
--cfg=s8s8s8
--bia_dt=undef
--attr-post-ops=add:s8:common+add:s8:common,add:s8:common+mul:f32:per_oc,mul:f32:common+add:s8:common+div:f32:per_oc
16x256:256x1:16x1
