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15 changes: 6 additions & 9 deletions backends/webgpu/test/op_tests/cases.py
Original file line number Diff line number Diff line change
Expand Up @@ -1254,10 +1254,12 @@ def _linear_fp32_suite() -> WebGPUTestSuite:
def _conv2d_suite() -> WebGPUTestSuite:
# DaViT patch-embed / downsample convs + conv_transpose2d (same registration,
# folded by the `transposed` arg). NCHW fp32. Routing coverage (all vs the
# same fp64 golden): patch_embed/conv3x3_pad1/strided/gemm_batched are
# groups==1 → im2col tiled GEMM (gemm_batched pins the B>1 output write);
# grouped_vec4 (groups=2, icpg=4) → direct vec4 kernel; depthwise (groups=8,
# icpg=1) → direct scalar; transpose2x → conv_transpose2d.
# same fp64 golden): patch_embed/conv3x3_pad1/strided are groups==1 → im2col
# tiled GEMM; grouped_vec4 (groups=2, icpg=4) → direct vec4 kernel; depthwise
# (groups=8, icpg=1) → direct scalar; transpose2x → conv_transpose2d.
# No batched (B>1) case: check_conv_node in backends/vulkan/op_registry.py
# refuses to delegate a 4-D convolution whose batch is not 1, so the export
# would fall back to CPU and test nothing. Add one back once it is accepted.
return WebGPUTestSuite(
module_factory=make_conv,
cases=[
Expand Down Expand Up @@ -1304,11 +1306,6 @@ def _conv2d_suite() -> WebGPUTestSuite:
},
inputs=(InputSpec(shape=(1, 8, 8, 8), gen=_chw_ramp),),
),
Case(
name="gemm_batched",
construct={"in_ch": 8, "out_ch": 16, "kernel": 3, "padding": 1},
inputs=(InputSpec(shape=(2, 8, 16, 16), gen=_chw_ramp),),
),
Case(
name="transpose2x",
construct={
Expand Down
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