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133 lines
4.1 KiB
133 lines
4.1 KiB
import unittest
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import numpy as np
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from op_test import OpTest
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def max_pool2D_forward_naive(x, ksize, strides, paddings=[0, 0], global_pool=0):
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N, C, H, W = x.shape
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if global_pool == 1:
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ksize = [H, W]
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H_out = (H - ksize[0] + 2 * paddings[0]) / strides[0] + 1
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W_out = (W - ksize[1] + 2 * paddings[1]) / strides[1] + 1
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out = np.zeros((N, C, H_out, W_out))
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for i in xrange(H_out):
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for j in xrange(W_out):
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r_start = np.max((i * strides[0] - paddings[0], 0))
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r_end = np.min((i * strides[0] + ksize[0] - paddings[0], H))
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c_start = np.max((j * strides[1] - paddings[1], 0))
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c_end = np.min((j * strides[1] + ksize[1] - paddings[1], W))
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x_masked = x[:, :, r_start:r_end, c_start:c_end]
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out[:, :, i, j] = np.max(x_masked, axis=(2, 3))
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return out
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def avg_pool2D_forward_naive(x, ksize, strides, paddings=[0, 0], global_pool=0):
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N, C, H, W = x.shape
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if global_pool == 1:
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ksize = [H, W]
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H_out = (H - ksize[0] + 2 * paddings[0]) / strides[0] + 1
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W_out = (W - ksize[1] + 2 * paddings[1]) / strides[1] + 1
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out = np.zeros((N, C, H_out, W_out))
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for i in xrange(H_out):
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for j in xrange(W_out):
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r_start = np.max((i * strides[0] - paddings[0], 0))
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r_end = np.min((i * strides[0] + ksize[0] - paddings[0], H))
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c_start = np.max((j * strides[1] - paddings[1], 0))
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c_end = np.min((j * strides[1] + ksize[1] - paddings[1], W))
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x_masked = x[:, :, r_start:r_end, c_start:c_end]
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out[:, :, i, j] = np.sum(x_masked, axis=(2, 3)) / (
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(r_end - r_start) * (c_end - c_start))
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return out
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class TestPool2d_Op(OpTest):
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def setUp(self):
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self.initTestCase()
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self.op_type = "pool2d"
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input = np.random.random(self.shape).astype("float32")
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output = self.pool2D_forward_naive(input, self.ksize, self.strides,
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self.paddings, self.global_pool)
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self.inputs = {'X': input}
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self.attrs = {
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'strides': self.strides,
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'paddings': self.paddings,
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'ksize': self.ksize,
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'poolingType': self.pool_type,
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'globalPooling': self.global_pool,
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}
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self.outputs = {'Out': output}
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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if self.pool_type != "max":
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self.check_grad(set(['X']), 'Out', max_relative_error=0.07)
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def initTestCase(self):
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self.global_pool = 0
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self.pool_type = "avg"
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self.pool2D_forward_naive = avg_pool2D_forward_naive
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self.shape = [2, 3, 5, 5]
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self.ksize = [3, 3]
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self.strides = [1, 1]
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self.paddings = [0, 0]
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class TestCase1(TestPool2d_Op):
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def initTestCase(self):
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self.global_pool = 0
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self.op_type = "pool2d"
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self.pool_type = "avg"
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self.pool2D_forward_naive = avg_pool2D_forward_naive
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self.shape = [2, 3, 5, 5]
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self.ksize = [3, 3]
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self.strides = [1, 1]
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self.paddings = [1, 1]
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class TestCase2(TestPool2d_Op):
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def initTestCase(self):
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self.global_pool = 1
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self.op_type = "pool2d"
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self.pool_type = "avg"
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self.pool2D_forward_naive = avg_pool2D_forward_naive
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self.shape = [2, 3, 5, 5]
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self.ksize = [3, 3]
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self.strides = [1, 1]
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self.paddings = [1, 1]
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class TestCase3(TestPool2d_Op):
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def initTestCase(self):
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self.global_pool = 0
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self.op_type = "pool2d"
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self.pool_type = "max"
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self.pool2D_forward_naive = max_pool2D_forward_naive
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self.shape = [2, 3, 5, 5]
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self.ksize = [3, 3]
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self.strides = [1, 1]
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self.paddings = [1, 1]
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class TestCase4(TestPool2d_Op):
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def initTestCase(self):
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self.global_pool = 1
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self.op_type = "pool2d"
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self.pool_type = "max"
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self.pool2D_forward_naive = max_pool2D_forward_naive
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self.shape = [2, 3, 5, 5]
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self.ksize = [3, 3]
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self.strides = [1, 1]
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self.paddings = [1, 1]
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if __name__ == '__main__':
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unittest.main()
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