def test_backward1(self):
n, c, h, w = 1, 1, 3, 3
x = np.arange(n * c * h * w).reshape((n, c, h, w))
# y = F.im2col(x, 3, 3, 0)
f = lambda x: F.im2col(x, 3, 3, 0)
self.assertTrue(check_backward(f, x))
def test_forward1(self):
n, c, h, w = 1, 1, 3, 3
x = np.arange(n * c * h * w).reshape((n, c, h, w))
y = F.im2col(x, 3, 3, 0, to_matrix=True)
expected = np.array([[0, 1, 2, 3, 4, 5, 6, 7, 8]])
res = np.array_equal(y.data, expected)
self.assertTrue(res)
#!/usr/bin/python3
# coding: utf-8
if '__file__' in globals():
import os, sys
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
import numpy as np
from dezero import Variable
import dezero.functions as F
x1 = np.random.rand(1, 3, 7, 7)
col1 = F.im2col(x1, kernel_size=5, stride=1, pad=0, to_matrix=True)
print(col1.shape)
x2 = np.random.rand(10, 3, 7, 7)
kernel_size = (5, 5)
stride = (1, 1)
pad = (0, 0)
col2 = F.im2col(x2, kernel_size, stride, pad, to_matrix=True)
print(col2.shape)
print()
N, C, H, W = 1, 5, 15, 15
OC, (KH, KW) = 8, (3, 3)
x = Variable(np.random.randn(N, C, H, W))
W = np.random.randn(OC, C, KH, KW)
# y = F.conv2d_simple(x, W, b=None, stride=1, pad=1) ## こっちだと動かない
y = F.conv2d(x, W, b=None, stride=1, pad=1)
def test_backward2(self):
n, c, h, w = 1, 1, 3, 3
x = np.arange(n * c * h * w).reshape((n, c, h, w))
f = lambda x: F.im2col(x, 3, 3, 0, to_matrix=False)
self.assertTrue(check_backward(f, x))
def test_backward1(self):
n, c, h, w = 1, 1, 3, 3
x = np.arange(n * c * h * w).reshape((n, c, h, w))
f = lambda x: F.im2col(x, 3, 3, 0, to_matrix=True)
self.assertTrue(gradient_check(f, x))
