gemini-code-assist[bot] commented on code in PR #18627:
URL: https://github.com/apache/tvm/pull/18627#discussion_r2655025109
##########
python/tvm/tir/tensor_intrin/metal.py:
##########
@@ -249,9 +249,9 @@ def impl(a: T.handle, b: T.handle, c: T.handle) -> None:
SIMDGROUP_FILLED_8x8x8_f32_INTRIN,
*get_make_filled_simdgroup_matrix_intrin("float32", 8, 8)
)
-SIMDGROUP_FILLED_8x8x8_bf16_INTRIN = "simdgroup_fill_8x8x8_bf16"
+SIMDGROUP_MAKE_FILLED_8x8x8_bf16_INTRIN = "simdgroup_make_filled_8x8x8_bf16"
TensorIntrin.register(
- SIMDGROUP_FILLED_8x8x8_bf16_INTRIN,
*get_make_filled_simdgroup_matrix_intrin("bfloat16", 8, 8)
+ SIMDGROUP_MAKE_FILLED_8x8x8_bf16_INTRIN,
*get_make_filled_simdgroup_matrix_intrin("bfloat16", 8, 8)
)
Review Comment:
It's great that you're making the intrinsic name for `bfloat16` consistent
with `float16` by using `simdgroup_make_filled_...`. However, the `float32`
intrinsic `SIMDGROUP_FILLED_8x8x8_f32_INTRIN` is still using
`simdgroup_fill_...`. This will cause an issue because
`get_simdgroup_intrin_group` constructs the `init_intrin` name as
`simdgroup_make_filled_...` for all dtypes. With the changes in `matmul.py` to
support dynamic dtypes, this will break `float32` support. Please also update
the `float32` intrinsic name and value for consistency. It should be renamed to
`SIMDGROUP_MAKE_FILLED_8x8x8_f32_INTRIN` with value
`simdgroup_make_filled_8x8x8_f32`.
##########
python/tvm/dlight/gpu/matmul.py:
##########
@@ -1040,8 +1044,10 @@ def is_inner_reduction(block_stmt, iter_infos):
return tensorize_sch
elif target.kind.name == "metal":
try:
- return MetalMatmul().apply(func, target, _)
- except: # pylint: disable=bare-except
+ result = MetalMatmul().apply(func, target, _)
+ if result is not None:
+ return result
+ except Exception: # pylint: disable=broad-except
pass
Review Comment:
Per PEP 8, imports should be at the top of the file. Please move `import
warnings` to the top of `python/tvm/dlight/gpu/matmul.py` to improve code style
and readability.
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