import unittest import numpy as np from op_test import OpTest def max_pool2D_forward_naive(x, ksize, strides, paddings=[0, 0], global_pool=0): N, C, H, W = x.shape if global_pool == 1: ksize = [H, W] 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)) for i in xrange(H_out): for j in xrange(W_out): r_start = np.max((i * strides[0] - paddings[0], 0)) r_end = np.min((i * strides[0] + ksize[0] - paddings[0], H)) c_start = np.max((j * strides[1] - paddings[1], 0)) c_end = np.min((j * strides[1] + ksize[1] - paddings[1], W)) x_masked = x[:, :, r_start:r_end, c_start:c_end] out[:, :, i, j] = np.max(x_masked, axis=(2, 3)) return out def avg_pool2D_forward_naive(x, ksize, strides, paddings=[0, 0], global_pool=0): N, C, H, W = x.shape if global_pool == 1: ksize = [H, W] 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)) for i in xrange(H_out): for j in xrange(W_out): r_start = np.max((i * strides[0] - paddings[0], 0)) r_end = np.min((i * strides[0] + ksize[0] - paddings[0], H)) c_start = np.max((j * strides[1] - paddings[1], 0)) c_end = np.min((j * strides[1] + ksize[1] - paddings[1], W)) x_masked = x[:, :, r_start:r_end, c_start:c_end] out[:, :, i, j] = np.sum(x_masked, axis=(2, 3)) / ( (r_end - r_start) * (c_end - c_start)) return out class TestPool2d_cudnn_Op(OpTest): def setUp(self): self.initTestCase() input = np.random.random(self.shape).astype("float32") output = self.pool2D_forward_naive(input, self.ksize, self.strides, self.paddings, self.global_pool) self.inputs = {'X': input} self.attrs = { 'strides': self.strides, 'paddings': self.paddings, 'ksize': self.ksize, 'poolingType': self.pool_type, 'globalPooling': self.global_pool, } self.outputs = {'Out': output} def test_check_output(self): self.check_output() def test_check_grad(self): if self.pool_type != "max": self.check_grad(set(['X']), 'Out', max_relative_error=0.07) def initTestCase(self): self.global_pool = True self.op_type = "pool2d_cudnn" self.pool_type = "avg" self.pool2D_forward_naive = avg_pool2D_forward_naive self.shape = [2, 3, 5, 5] self.ksize = [3, 3] self.strides = [1, 1] self.paddings = [0, 0] class TestCase1(TestPool2d_cudnn_Op): def initTestCase(self): self.global_pool = False self.op_type = "pool2d_cudnn" self.pool_type = "avg" self.pool2D_forward_naive = avg_pool2D_forward_naive self.shape = [2, 3, 7, 7] self.ksize = [3, 3] self.strides = [1, 1] self.paddings = [0, 0] class TestCase2(TestPool2d_cudnn_Op): def initTestCase(self): self.global_pool = False self.op_type = "pool2d_cudnn" self.pool_type = "avg" self.pool2D_forward_naive = avg_pool2D_forward_naive self.shape = [2, 3, 7, 7] self.ksize = [3, 3] self.strides = [1, 1] self.paddings = [1, 1] class TestCase3(TestPool2d_cudnn_Op): def initTestCase(self): self.global_pool = True self.op_type = "pool2d_cudnn" self.pool_type = "max" self.pool2D_forward_naive = max_pool2D_forward_naive self.shape = [2, 3, 5, 5] self.ksize = [3, 3] self.strides = [1, 1] self.paddings = [0, 0] class TestCase4(TestPool2d_cudnn_Op): def initTestCase(self): self.global_pool = False self.op_type = "pool2d_cudnn" self.pool_type = "max" self.pool2D_forward_naive = max_pool2D_forward_naive self.shape = [2, 3, 7, 7] self.ksize = [3, 3] self.strides = [1, 1] self.paddings = [0, 0] class TestCase5(TestPool2d_cudnn_Op): def initTestCase(self): self.global_pool = False self.op_type = "pool2d_cudnn" self.pool_type = "max" self.pool2D_forward_naive = max_pool2D_forward_naive self.shape = [2, 3, 7, 7] self.ksize = [3, 3] self.strides = [1, 1] self.paddings = [1, 1] if __name__ == '__main__': unittest.main()