def input_func():
inputs = prepare_chainerx_inputs(
1, config1, True) + prepare_chainerx_inputs(
1, config2, True)
result = func(*inputs)
result.grad = chainerx.ones_like(result)
return result
def test_ones_like_with_device(shape, device):
t = chainerx.empty((2,), 'float32')
a = chainerx.ones_like(t, device)
b = chainerx.ones_like(t)
array_utils.check_device(a, device)
chainerx.testing.assert_array_equal_ex(a, b)
def test_ones_like_with_device(shape, device):
t = chainerx.empty((2,), 'float32')
a = chainerx.ones_like(t, device)
b = chainerx.ones_like(t)
array_utils.check_device(a, device)
chainerx.testing.assert_array_equal_ex(a, b)
def input_func():
inputs = prepare_chainerx_inputs(num_input, tensor_config,
True)
result = func(*inputs)
result.grad = chainerx.ones_like(result)
return result