wehub-resource-sync
298 lines
9.6 KiB
Python
298 lines
9.6 KiB
Python
# 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 math
|
|
import sys
|
|
import unittest
|
|
from decimal import ROUND_HALF_UP, Decimal
|
|
|
|
import numpy as np
|
|
from op_test import OpTest, get_device_place, is_custom_device
|
|
|
|
import paddle
|
|
from paddle.base import core
|
|
|
|
|
|
def _round(x):
|
|
"""In Python3 round function rounds to the nearest even number,
|
|
we use this function to make the result always round up when the
|
|
remainder is 0.5. See more at:
|
|
https://stackoverflow.com/questions/33019698/how-to-properly-round-up-half-float-numbers
|
|
"""
|
|
return Decimal(x).to_integral_value(rounding=ROUND_HALF_UP)
|
|
|
|
|
|
class TestROIPoolOp(OpTest):
|
|
def set_data(self):
|
|
self.init_test_case()
|
|
self.make_rois()
|
|
self.calc_roi_pool()
|
|
|
|
self.inputs = {
|
|
'X': self.x,
|
|
'ROIs': (self.rois[:, 1:5], self.rois_lod),
|
|
'RoisNum': self.boxes_num,
|
|
}
|
|
|
|
self.attrs = {
|
|
'spatial_scale': self.spatial_scale,
|
|
'pooled_height': self.pooled_height,
|
|
'pooled_width': self.pooled_width,
|
|
}
|
|
|
|
self.outputs = {'Out': self.outs, 'Argmax': self.argmaxes}
|
|
|
|
def init_test_case(self):
|
|
self.batch_size = 3
|
|
self.channels = 3
|
|
self.height = 6
|
|
self.width = 4
|
|
|
|
# n, c, h, w
|
|
self.x_dim = (self.batch_size, self.channels, self.height, self.width)
|
|
|
|
self.spatial_scale = 1.0 / 4.0
|
|
self.pooled_height = 2
|
|
self.pooled_width = 2
|
|
|
|
self.x = np.random.random(self.x_dim).astype('float64')
|
|
|
|
def calc_roi_pool(self):
|
|
out_data = np.zeros(
|
|
(
|
|
self.rois_num,
|
|
self.channels,
|
|
self.pooled_height,
|
|
self.pooled_width,
|
|
)
|
|
)
|
|
argmax_data = np.zeros(
|
|
(
|
|
self.rois_num,
|
|
self.channels,
|
|
self.pooled_height,
|
|
self.pooled_width,
|
|
)
|
|
)
|
|
|
|
for i in range(self.rois_num):
|
|
roi = self.rois[i]
|
|
roi_batch_id = int(roi[0])
|
|
roi_start_w = int(_round(roi[1] * self.spatial_scale))
|
|
roi_start_h = int(_round(roi[2] * self.spatial_scale))
|
|
roi_end_w = int(_round(roi[3] * self.spatial_scale))
|
|
roi_end_h = int(_round(roi[4] * self.spatial_scale))
|
|
|
|
roi_height = int(max(roi_end_h - roi_start_h + 1, 1))
|
|
roi_width = int(max(roi_end_w - roi_start_w + 1, 1))
|
|
|
|
x_i = self.x[roi_batch_id]
|
|
|
|
bin_size_h = float(roi_height) / float(self.pooled_height)
|
|
bin_size_w = float(roi_width) / float(self.pooled_width)
|
|
|
|
for c in range(self.channels):
|
|
for ph in range(self.pooled_height):
|
|
for pw in range(self.pooled_width):
|
|
hstart = int(math.floor(ph * bin_size_h))
|
|
wstart = int(math.floor(pw * bin_size_w))
|
|
hend = int(math.ceil((ph + 1) * bin_size_h))
|
|
wend = int(math.ceil((pw + 1) * bin_size_w))
|
|
|
|
hstart = min(max(hstart + roi_start_h, 0), self.height)
|
|
hend = min(max(hend + roi_start_h, 0), self.height)
|
|
wstart = min(max(wstart + roi_start_w, 0), self.width)
|
|
wend = min(max(wend + roi_start_w, 0), self.width)
|
|
|
|
is_empty = (hend <= hstart) or (wend <= wstart)
|
|
if is_empty:
|
|
out_data[i, c, ph, pw] = 0
|
|
else:
|
|
out_data[i, c, ph, pw] = -sys.float_info.max
|
|
|
|
argmax_data[i, c, ph, pw] = -1
|
|
|
|
for h in range(hstart, hend):
|
|
for w in range(wstart, wend):
|
|
if x_i[c, h, w] > out_data[i, c, ph, pw]:
|
|
out_data[i, c, ph, pw] = x_i[c, h, w]
|
|
argmax_data[i, c, ph, pw] = (
|
|
h * self.width + w
|
|
)
|
|
|
|
self.outs = out_data.astype('float64')
|
|
self.argmaxes = argmax_data.astype('int64')
|
|
|
|
def make_rois(self):
|
|
rois = []
|
|
self.rois_lod = [[]]
|
|
for bno in range(self.batch_size):
|
|
self.rois_lod[0].append(bno + 1)
|
|
for i in range(bno + 1):
|
|
x1 = np.random.randint(
|
|
0, self.width // self.spatial_scale - self.pooled_width
|
|
)
|
|
y1 = np.random.randint(
|
|
0, self.height // self.spatial_scale - self.pooled_height
|
|
)
|
|
|
|
x2 = np.random.randint(
|
|
x1 + self.pooled_width, self.width // self.spatial_scale
|
|
)
|
|
y2 = np.random.randint(
|
|
y1 + self.pooled_height, self.height // self.spatial_scale
|
|
)
|
|
|
|
roi = [bno, x1, y1, x2, y2]
|
|
rois.append(roi)
|
|
self.rois_num = len(rois)
|
|
self.rois = np.array(rois).astype("float64")
|
|
self.boxes_num = np.array(
|
|
[bno + 1 for bno in range(self.batch_size)]
|
|
).astype('int32')
|
|
|
|
def setUp(self):
|
|
self.op_type = "roi_pool"
|
|
self.python_api = (
|
|
lambda x, boxes, boxes_num, pooled_height, pooled_width, spatial_scale: (
|
|
paddle.vision.ops.roi_pool(
|
|
x,
|
|
boxes,
|
|
boxes_num,
|
|
(pooled_height, pooled_width),
|
|
spatial_scale,
|
|
)
|
|
)
|
|
)
|
|
self.python_out_sig = ["Out"]
|
|
self.set_data()
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(['X'], 'Out')
|
|
|
|
|
|
class TestROIPoolInLodOp(TestROIPoolOp):
|
|
def set_data(self):
|
|
self.init_test_case()
|
|
self.make_rois()
|
|
self.calc_roi_pool()
|
|
|
|
seq_len = self.rois_lod[0]
|
|
|
|
self.inputs = {
|
|
'X': self.x,
|
|
'ROIs': (self.rois[:, 1:5], self.rois_lod),
|
|
'RoisNum': np.asarray(seq_len).astype('int32'),
|
|
}
|
|
|
|
self.attrs = {
|
|
'spatial_scale': self.spatial_scale,
|
|
'pooled_height': self.pooled_height,
|
|
'pooled_width': self.pooled_width,
|
|
}
|
|
|
|
self.outputs = {'Out': self.outs, 'Argmax': self.argmaxes}
|
|
|
|
|
|
class TestROIPoolInLodOp_ZeroSize(TestROIPoolOp):
|
|
def init_test_case(self):
|
|
self.batch_size = 3
|
|
self.channels = 0
|
|
self.height = 6
|
|
self.width = 4
|
|
|
|
# n, c, h, w
|
|
self.x_dim = (self.batch_size, self.channels, self.height, self.width)
|
|
|
|
self.spatial_scale = 1.0 / 4.0
|
|
self.pooled_height = 2
|
|
self.pooled_width = 2
|
|
|
|
self.x = np.random.random(self.x_dim).astype('float64')
|
|
|
|
def make_rois(self):
|
|
rois = []
|
|
self.rois_lod = [[]]
|
|
for bno in range(self.batch_size):
|
|
self.rois_lod[0].append(bno + 1)
|
|
for i in range(bno + 1):
|
|
x1 = np.random.randint(
|
|
0, self.width // self.spatial_scale - self.pooled_width
|
|
)
|
|
x2 = np.random.randint(
|
|
x1 + self.pooled_width, self.width // self.spatial_scale
|
|
)
|
|
if self.height == 0:
|
|
y1 = 0
|
|
y2 = 0
|
|
else:
|
|
y1 = np.random.random_integers(
|
|
0,
|
|
self.height // self.spatial_scale - self.pooled_height,
|
|
)
|
|
y2 = np.random.random_integers(
|
|
y1 + self.pooled_height,
|
|
self.height // self.spatial_scale,
|
|
)
|
|
|
|
roi = [bno, x1, y1, x2, y2]
|
|
rois.append(roi)
|
|
self.rois_num = len(rois)
|
|
self.rois = np.array(rois).astype("float64")
|
|
self.boxes_num = np.array(
|
|
[bno + 1 for bno in range(self.batch_size)]
|
|
).astype('int32')
|
|
|
|
def set_data(self):
|
|
self.init_test_case()
|
|
self.make_rois()
|
|
self.calc_roi_pool()
|
|
|
|
seq_len = self.rois_lod[0]
|
|
|
|
self.inputs = {
|
|
'X': self.x,
|
|
'ROIs': (self.rois[:, 1:5], self.rois_lod),
|
|
'RoisNum': np.asarray(seq_len).astype('int32'),
|
|
}
|
|
|
|
self.attrs = {
|
|
'spatial_scale': self.spatial_scale,
|
|
'pooled_height': self.pooled_height,
|
|
'pooled_width': self.pooled_width,
|
|
}
|
|
|
|
self.outputs = {'Out': self.outs, 'Argmax': self.argmaxes}
|
|
|
|
def test_check_output(self):
|
|
self.check_output_with_place(
|
|
core.CPUPlace(),
|
|
)
|
|
if paddle.is_compiled_with_cuda() or is_custom_device():
|
|
self.check_output_with_place(
|
|
get_device_place(),
|
|
)
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad_with_place(core.CPUPlace(), ['X'], 'Out')
|
|
if paddle.is_compiled_with_cuda() or is_custom_device():
|
|
self.check_grad_with_place(get_device_place(), ['X'], 'Out')
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|