def _numerical_jacobian(self,
module,
input,
jacobian_input=True,
jacobian_parameters=True):
output = self._forward(module, input)
output_size = output.nelement()
if jacobian_parameters:
param, d_param = self._get_parameters(module)
def fw(input):
out = self._forward(module, input)
if isinstance(out, Variable):
return out.data
return out
res = tuple()
input = contiguous(input)
if jacobian_input:
res += get_numerical_jacobian(fw, input, input, eps=1e-6),
if jacobian_parameters:
res += torch.cat(
list(
get_numerical_jacobian(fw, input, p, eps=1e-6)
for p in param), 0),
return res
def _numerical_jacobian(self, module, input, jacobian_input=True, jacobian_parameters=True):
def fw(input):
return self._forward(module, input).detach()
res = tuple()
input = contiguous(input)
if jacobian_input:
res += get_numerical_jacobian(fw, input, input, eps=1e-6),
if jacobian_parameters:
param, _ = self._get_parameters(module)
res += torch.cat([get_numerical_jacobian(fw, input, p, eps=1e-6) for p in param], 0),
return res
def _numerical_jacobian(self, module, input, jacobian_input=True, jacobian_parameters=True):
def fw(input):
out = self._forward(module, input)
if isinstance(out, Variable):
return out.data
return out
res = tuple()
input = contiguous(input)
if jacobian_input:
res += get_numerical_jacobian(fw, input, input, eps=1e-6),
if jacobian_parameters:
param, _ = self._get_parameters(module)
res += torch.cat(list(get_numerical_jacobian(fw, input, p, eps=1e-6) for p in param), 0),
return res
