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[HEXAGON] Add op resize2d for hexagon (apache#11834)
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* [HEXAGON] Add op resize2d for hexagon

* Reformat

* Change to v69
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trahman-quic authored and blackkker committed Jul 7, 2022
1 parent 64f1b57 commit 5a6ef13
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1 change: 1 addition & 0 deletions python/tvm/topi/hexagon/__init__.py
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from .injective import *
from .pooling import *
from .reduce import *
from .resize2d import *
81 changes: 81 additions & 0 deletions python/tvm/topi/hexagon/resize2d.py
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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
# pylint: disable=invalid-name

"""Compute and schedule for resize2d
Please note the following assumptions made by the implementation:
1) The input and output data will be multiple of crouton layout
2) And the supported layout is NHWC"""

from tvm import te
from tvm import tir
from tvm import topi
from .utils import get_layout_transform_fn


def resize2d_compute(
data,
roi,
size,
layout,
method="linear",
coordinate_transformation_mode="half_pixel",
rounding_method="",
bicubic_alpha=-0.5,
bicubic_exclude=0,
extrapolation_value=0.0,
out_dtype=None,
output_shape=None,
):
"""Call resize2d op from topi.image"""
return topi.image.resize2d(
data,
roi,
size,
layout,
method,
coordinate_transformation_mode,
rounding_method,
bicubic_alpha,
bicubic_exclude,
extrapolation_value,
out_dtype,
output_shape,
)


def tir_broadcast_schedule(
out_m,
input_a,
input_layout: str,
output_layout: str,
):
"""Schedule for input and output layout nhwc-8h2w32c2w-2d"""
func = te.create_prim_func([input_a, out_m])

s = tir.Schedule(func)

block = s.get_block("resize")

if input_layout == "nhwc-8h2w32c2w-2d":
input_transformed_layout = get_layout_transform_fn(input_layout)
s.transform_layout(block, buffer=("read", 0), index_map=input_transformed_layout)

output_transformed_layout = get_layout_transform_fn(output_layout)
s.transform_layout(block, buffer=("write", 0), index_map=output_transformed_layout)

return s
169 changes: 169 additions & 0 deletions tests/python/contrib/test_hexagon/topi/test_resize2d.py
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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.


import pytest
import numpy as np

from tvm import te, topi

import tvm.testing
from tvm.topi import testing
from tvm.contrib.hexagon.build import HexagonLauncher
import tvm.topi.hexagon as s1
from ..infrastructure import allocate_hexagon_array, transform_numpy


@tvm.testing.fixture
def expected_output_np(
input_np, in_height, in_width, out_height, out_width, layout, method, coord_trans
):
scale_h = out_height / in_height
scale_w = out_width / in_width
return tvm.topi.testing.resize2d_python(
input_np, (scale_h, scale_w), layout, method, coord_trans
)


@tvm.testing.fixture
def input_np(input_shape, dtype):
return np.random.random(input_shape).astype(dtype)


@tvm.testing.fixture
def transformed_input_np(input_np, layout, input_crouton_layout):
return transform_numpy(input_np, layout.lower(), input_crouton_layout)


@tvm.testing.fixture
def transformed_expected_output_np(expected_output_np, layout, output_layout):
return transform_numpy(expected_output_np, layout.lower(), output_layout)


@tvm.testing.fixture
def input_shape(batch, channel, in_height, in_width):
return (batch, in_height, in_width, channel)


@tvm.testing.fixture
def output_shape(batch, channel, out_height, out_width):
return (batch, out_height, out_width, channel)


class TestResize2d:
(batch, channel, in_height, in_width, out_height, out_width,) = tvm.testing.parameters(
(
1,
32,
8,
8,
16,
16,
),
(
1,
32,
48,
48,
8,
8,
),
)

(layout, input_crouton_layout, output_layout, dtype,) = tvm.testing.parameters(
("NHWC", "nhwc-8h2w32c2w-2d", "nhwc-8h2w32c2w-2d", "float16"),
)

coord_trans = tvm.testing.parameter("asymmetric", "align_corners", "half_pixel")
method = tvm.testing.parameter("nearest_neighbor", "linear", "cubic")

@tvm.testing.requires_hexagon
def test_resize2d(
self,
dtype,
input_np,
transformed_input_np,
input_shape,
output_shape,
expected_output_np,
transformed_expected_output_np,
layout,
input_crouton_layout,
output_layout,
coord_trans,
method,
hexagon_session,
):
target_hexagon = tvm.target.hexagon("v69")
A = te.placeholder(input_shape, name="A", dtype=dtype)

M = s1.resize2d_compute(
A,
[0.0] * 4,
(output_shape[1], output_shape[2]),
layout=layout,
coordinate_transformation_mode=coord_trans,
method=method,
)

tir_schedule = s1.tir_broadcast_schedule(M, A, input_crouton_layout, output_layout)

sch = tir_schedule.mod

input_axis_separator = [4]
if output_layout == "nhwc-8h2w32c2w-2d":
output_axis_separator = [4]
else:
raise RuntimeError(f"Unexpected layout '{output_layout}'")

with tvm.transform.PassContext(opt_level=3):
func = tvm.build(
sch,
[A, M],
tvm.target.Target(target_hexagon, host=target_hexagon),
name="resize2d",
)

A_data_nd = allocate_hexagon_array(
hexagon_session.device,
data=transformed_input_np,
dtype=dtype,
axis_separators=input_axis_separator,
mem_scope="global.vtcm",
)

M_data_nd = allocate_hexagon_array(
hexagon_session.device,
transformed_expected_output_np.shape,
dtype=dtype,
axis_separators=output_axis_separator,
mem_scope="global.vtcm",
)

mod = hexagon_session.load_module(func)
mod(A_data_nd, M_data_nd)

b, h, w, c = output_shape
# convert nd to np and reshape to fixed chunk size layout
if output_layout == "nhwc-8h2w32c2w-2d":
M_data_np = M_data_nd.numpy().reshape([b, h // 8, w // 4, c // 32, 8, 2, 32, 2])

np.testing.assert_allclose(transformed_expected_output_np, M_data_np, rtol=1e-3, atol=1e-3)


if __name__ == "__main__":
tvm.testing.main()

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