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- # Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
- #
- # Licensed 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 unittest
-
- import numpy as np
- from get_test_cover_info import (
- XPUOpTestWrapper,
- create_test_class,
- get_xpu_op_support_types,
- )
- from op_test_xpu import XPUOpTest
-
- import paddle
-
- paddle.enable_static()
-
-
- def max_pool2D_forward_naive(
- x, ksize, strides, paddings, global_pool=False, adaptive=False
- ):
- N, C, H, W = x.shape
- global_pool = global_pool or (adaptive or (ksize[0] * ksize[1] == 1))
- if global_pool:
- ksize = [H, W]
- paddings = [0, 0]
-
- H_out = (H - ksize[0] + 2 * paddings[0]) // strides[0] + 1
- W_out = (W - ksize[1] + 2 * paddings[1]) // strides[1] + 1
- out = np.zeros((N, C, H_out, W_out))
- mask = np.zeros((N, C, H_out, W_out))
- for i in range(H_out):
- for j in range(W_out):
- r0 = i * strides[0] - paddings[0]
- r1 = r0 + ksize[0]
- c0 = j * strides[1] - paddings[1]
- c1 = c0 + ksize[1]
- r_start = np.max((r0, 0))
- r_end = np.min((r1, H))
- c_start = np.max((c0, 0))
- c_end = np.min((c1, W))
- x_masked = x[:, :, r_start:r_end, c_start:c_end]
-
- out[:, :, i, j] = np.max(x_masked, axis=(2, 3))
-
- for n in range(N):
- for c in range(C):
- arr = x_masked[n, c, :, :]
- index = np.where(arr == np.max(arr))
- sub_row = index[0][-1] - r0 if r0 < 0 else index[0][-1]
- sub_col = index[1][-1] - c0 if c0 < 0 else index[1][-1]
- index = sub_row * (r1 - r0) + sub_col
- mask[n, c, i, j] = index
-
- return out, mask
-
-
- class XPUTestPoolWithIndex_op(XPUOpTestWrapper):
- def __init__(self):
- self.op_name = 'max_pool2d_with_index'
- self.use_dynamic_create_class = False
-
- class TestMaxPoolWithIndex_Op(XPUOpTest):
- def setUp(self):
- self.op_type = 'max_pool2d_with_index'
- self.dtype = self.in_type
- self.place = paddle.XPUPlace(0)
- self.init_test_case()
- self.init_global()
- self.init_adaptive()
-
- input = np.random.random(self.shape).astype(self.dtype)
- input = np.round(input * 100.0, 2)
- output, mask = self.pool_forward_naive(
- input,
- self.ksize,
- self.strides,
- self.paddings,
- self.global_pool,
- self.adaptive,
- )
- output = output.astype(self.dtype)
- mask = mask.astype("int32")
-
- self.attrs = {
- 'strides': self.strides,
- 'paddings': self.paddings,
- 'ksize': self.ksize,
- 'global_pooling': self.global_pool,
- 'adaptive': self.adaptive,
- }
-
- self.inputs = {'X': input}
- self.outputs = {'Out': output, "Mask": mask}
-
- def test_check_output(self):
- self.check_output_with_place(self.place)
-
- def test_check_grad(self):
- self.check_grad_with_place(self.place, {'X'}, ['Out'])
-
- def init_test_case(self):
- self.pool_forward_naive = max_pool2D_forward_naive
- self.shape = [2, 3, 7, 7]
- self.ksize = [3, 3]
- self.strides = [2, 2]
- self.paddings = [1, 1]
-
- def init_global(self):
- self.global_pool = False
-
- def init_adaptive(self):
- self.adaptive = False
-
- # TODO pool3d is not supported for now
- # ----------------max_pool2d_with_index----------------
- class TestCase4(TestMaxPoolWithIndex_Op):
- def init_test_case(self):
- self.op_type = "max_pool2d_with_index"
- self.pool_forward_naive = max_pool2D_forward_naive
- self.shape = [2, 3, 7, 7]
- self.ksize = [3, 3]
- self.strides = [1, 1]
- self.paddings = [1, 1]
-
- def init_global(self):
- self.global_pool = True
-
- class TestCase5(TestCase4):
- def init_global(self):
- self.global_pool = False
-
- class TestCase6(TestMaxPoolWithIndex_Op):
- def init_test_case(self):
- self.op_type = "max_pool2d_with_index"
- self.pool_forward_naive = max_pool2D_forward_naive
- self.shape = [2, 3, 7, 7]
- self.ksize = [3, 3]
- self.strides = [2, 2]
- self.paddings = [0, 0]
-
- def init_global(self):
- self.global_pool = True
-
- class TestCase7(TestCase6):
- def init_global(self):
- self.global_pool = False
-
-
- support_types = get_xpu_op_support_types('max_pool2d_with_index')
- for stype in support_types:
- create_test_class(globals(), XPUTestPoolWithIndex_op, stype)
-
-
- if __name__ == '__main__':
- unittest.main()
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