d-smirnov commented on a change in pull request #6724:
URL: https://github.com/apache/incubator-tvm/pull/6724#discussion_r518320817
##########
File path: python/tvm/relay/op/contrib/arm_compute_lib.py
##########
@@ -305,14 +307,41 @@ def max_pool2d(expr):
typ = args[0].checked_type
if typ.dtype not in ["float32", "uint8"]:
return False
- return True
+ return not require_padding([*args, expr.checked_type])
+
+
+def require_padding(inputs):
+ """Checks whether supplied data will require padding.
+ Most of the operators ACL up to 20.11 uses padded data.
+ """
+
+ def _check(shape, dtype):
+ """NEON has 128bits/16bytes per vector"""
+ if len(shape) == 0:
+ return False
+ return (shape[-1] * np.dtype(dtype).itemsize) % 16 != 0
+
+ for i in inputs:
+ if isinstance(i, (tvm.relay.expr.Var, tvm.relay.expr.Call)):
+ if _check(i.checked_type.shape, i.checked_type.dtype):
+ return True
+ elif isinstance(i, tvm.relay.expr.Constant):
+ if _check(i.data.shape, i.data.dtype):
+ return True
+ elif isinstance(i, tvm.ir.tensor_type.TensorType):
+ if _check(i.shape, i.dtype):
+ return True
+ else:
+ raise Exception("Not supported")
Review comment:
Updated
##########
File path: tests/python/contrib/test_arm_compute_lib/test_pooling.py
##########
@@ -166,7 +167,12 @@ def test_pooling():
fp32_dtype = ("float32", -127, 128, 0.001, 0.001)
uint8_dtype = ("uint8", 0, 255, 1, 0)
+ # nn.max_pool2d(%arm_compute_lib_11_i0, pool_size=[3, 3], strides=[2, 2],
padding=[0, 0, 0, 0], layout="NHWC") /* ty=Tensor[(1, 27, 27, 256), float32] */
Review comment:
Yes. Removed.
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