def test_clear_output_grad_argument(self, grad):
x1 = nn.Variable([1], need_grad=True)
xx1 = F.identity(x1)
y1 = F.add_scalar(xx1)
answer_grad = []
if grad is None or isinstance(grad, nn.NdArray):
answer_grad.append([False]) # y1
else:
answer_grad.append([True]) # y1
answer_grad.append([True]) # xx1
y1.forward(clear_no_need_grad=True)
clear_called_flag_recorder.deactivate_clear_called_flag_recorder()
clear_called_flag_recorder.activate_clear_called_flag_recorder()
y1.backward(clear_buffer=True, grad=grad)
self.check_grad_cleared_flags(answer_grad)
assert y1.grad.clear_called == False
def test_clear_no_need_grad_during_recomputation(self):
x0 = nn.Variable((2, 3), need_grad=True)
x1 = F.identity(x0).apply(recompute=True)
# x2.data must be cleared just after recomputation because they are not need for backward propagation.
x2 = F.sin(x1).apply(recompute=True)
x3 = F.identity(x2).apply(recompute=True)
x4 = F.sin(x3)
# Forward
clear_called_flag_recorder.activate_clear_called_flag_recorder()
x4.forward(clear_no_need_grad=True)
# All intermediate data must be cleared.
expected = [
[False], # x0
[True], # x1
[True], # x2
[True], # x3
]
self.check_input_data_clear_called_flags(expected)
clear_called_flag_recorder.deactivate_clear_called_flag_recorder()
# Backward
clear_called_flag_recorder.activate_clear_called_flag_recorder()
x4.backward(clear_buffer=True)
expected = [
# Recomputation
[False], # x0
[False], # x1
[True], # x2: not need for grad calculation
# Backward propagation
[False], # x3
[True], # x2
[False], # x1
[False], # x0
]
self.check_input_data_clear_called_flags(expected)
clear_called_flag_recorder.deactivate_clear_called_flag_recorder()
def setup_method(self):
clear_called_flag_recorder.activate_clear_called_flag_recorder()
