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40 changes: 40 additions & 0 deletions backends/webgpu/test/op_tests/cases.py
Original file line number Diff line number Diff line change
@@ -1,3 +1,3 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
Expand Down Expand Up @@ -629,3 +629,43 @@
atol=1e-4,
rtol=1e-3,
)
from executorch.backends.webgpu.test.ops.test_max_pool2d import (
_det_input as _maxpool_det_input,
MaxPool2dModule,
)


@register_op_test("max_pool2d")
def _max_pool2d_suite() -> WebGPUTestSuite:
# SAM2 Hiera q_pool (native shape) + real Hiera channel count (ch768) +
# a padding case + a tiny eyeball case.
return WebGPUTestSuite(
module_factory=lambda kernel_size, stride, padding: MaxPool2dModule(
kernel_size, stride, padding
),
cases=[
Case(
name="q_pool",
construct={"kernel_size": 2, "stride": 2, "padding": 0},
inputs=(InputSpec(shape=(1, 8, 12, 12), gen=_maxpool_det_input),),
),
Case(
name="ch768",
construct={"kernel_size": 2, "stride": 2, "padding": 0},
inputs=(InputSpec(shape=(1, 768, 14, 14), gen=_maxpool_det_input),),
),
Case(
name="pad1",
construct={"kernel_size": 3, "stride": 2, "padding": 1},
inputs=(InputSpec(shape=(1, 8, 7, 7), gen=_maxpool_det_input),),
),
Case(
name="tiny",
construct={"kernel_size": 2, "stride": 2, "padding": 0},
inputs=(InputSpec(shape=(1, 4, 5, 5), gen=_maxpool_det_input),),
),
],
golden_dtype="float32",
atol=1e-4,
rtol=1e-3,
)
42 changes: 42 additions & 0 deletions backends/webgpu/test/ops/test_max_pool2d.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,42 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.

"""`aten.max_pool2d_with_indices.default` module for the WebGPU op-test
framework.

`F.max_pool2d` decomposes to `aten.max_pool2d_with_indices.default`, a
multi-output op whose out is a ValueList `[values, indices]`; the handler
writes the VALUES only and never the int64 indices
(`runtime/ops/max_pool2d/MaxPool2d.cpp`). Max-pool is on the SAM2 Hiera
q_pool path.
"""

import torch


class MaxPool2dModule(torch.nn.Module):
def __init__(self, kernel_size: int, stride: int, padding: int) -> None:
super().__init__()
self.kernel_size = kernel_size
self.stride = stride
self.padding = padding

def forward(self, x: torch.Tensor) -> torch.Tensor:
return torch.nn.functional.max_pool2d(
x,
kernel_size=self.kernel_size,
stride=self.stride,
padding=self.padding,
)


def _det_input(shape) -> torch.Tensor:
# ((i % 23) - 11) / 16: exact in fp32, spans negatives through positives.
n = 1
for s in shape:
n *= s
idx = torch.arange(n, dtype=torch.int64)
return (((idx % 23) - 11).to(torch.float32) / 16.0).reshape(shape)
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