def test_th_batch_map_offsets():
np.random.seed(42)
input = np.random.random((4, 100, 156))
offsets = (np.random.random((4, 100, 156, 2)) * 2)
sp_mapped_vals = sp_batch_map_offsets(input, offsets)
th_mapped_vals = th_batch_map_offsets(Variable(torch.from_numpy(input)),
Variable(torch.from_numpy(offsets)))
assert np.allclose(sp_mapped_vals, th_mapped_vals.data.numpy(), atol=1e-5)
def test_th_batch_map_offsets_grad():
np.random.seed(42)
input = np.random.random((4, 100, 156))
offsets = (np.random.random((4, 100, 156, 2)) * 2)
input = Variable(torch.from_numpy(input), requires_grad=True)
offsets = Variable(torch.from_numpy(offsets), requires_grad=True)
th_mapped_vals = th_batch_map_offsets(input, offsets)
e = torch.from_numpy(np.random.random((4, 100, 156)))
th_mapped_vals.backward(e)
assert not np.allclose(input.grad.data.numpy(), 0)
assert not np.allclose(offsets.grad.data.numpy(), 0)
def forward(self, x):
"""Return the deformed featured map"""
x_shape = x.size()
offsets = super(ConvOffset2D, self).forward(x)
# offsets: (b*c, h, w, 2)
offsets = self._to_bc_h_w_2(offsets, x_shape)
# x: (b*c, h, w)
x = self._to_bc_h_w(x, x_shape)
# X_offset: (b*c, h, w)
x_offset = th_batch_map_offsets(x, offsets)
# x_offset: (b, h, w, c)
x_offset = self._to_b_c_h_w(x_offset, x_shape)
return x_offset
def forward(self, x):
"""Return the deformed featured map"""
x_shape = x.size()
offsets = super(ConvOffset2D, self).forward(
x) #Gallus: perform normal convolution on 2D featuremap
# offsets: (b*c, h, w, 2) Gallus: why 2?
offsets = self._to_bc_h_w_2(offsets, x_shape)
# x: (b*c, h, w)
x = self._to_bc_h_w(x, x_shape)
# X_offset: (b*c, h, w)
x_offset = th_batch_map_offsets(x,
offsets,
grid=self._get_grid(self, x))
# x_offset: (b, h, w, c)
x_offset = self._to_b_c_h_w(x_offset, x_shape)
return x_offset
def forward(self, x):
"""Return the deformed featured map"""
x_shape = x.size()
offsets = F.conv2d(x, self.weight, self.bias, self.stride,
self.padding, self.dilation, self.groups)
# offsets: (b*c, h, w, 2)
offsets = self._to_bc_h_w_2(offsets, x_shape)
# x: (b*c, h, w)
x = self._to_bc_h_w(x, x_shape)
# X_offset: (b*c, h, w)
x_offset = th_batch_map_offsets(x,
offsets,
grid=self._get_grid(self, x))
# x_offset: (b, h, w, c)
x_offset = self._to_b_c_h_w(x_offset, x_shape)
return x_offset
