def _test_eq_float(test_case, shape, device):
arr = np.random.randn(*shape)
input = flow.Tensor(arr, dtype=flow.float32, device=flow.device(device))
num = 1
of_out = flow.eq(input, num)
np_out = np.equal(arr, num)
test_case.assertTrue(np.array_equal(of_out.numpy(), np_out))
def _test_eq(test_case, shape, device):
arr1 = np.random.randn(*shape)
arr2 = np.random.randn(*shape)
input = flow.Tensor(arr1, dtype=flow.float32, device=flow.device(device))
other = flow.Tensor(arr2, dtype=flow.float32, device=flow.device(device))
of_out = flow.eq(input, other)
of_out2 = flow.equal(input, other)
np_out = np.equal(arr1, arr2)
test_case.assertTrue(np.array_equal(of_out.numpy(), np_out))
test_case.assertTrue(np.array_equal(of_out2.numpy(), np_out))
def test_eq(test_case):
arr1 = np.array([
2,
3,
4,
5,
])
arr2 = np.array([2, 3, 4, 1])
input = flow.Tensor(arr1, dtype=flow.float32)
other = flow.Tensor(arr2, dtype=flow.float32)
of_out = flow.eq(input, other)
of_out2 = flow.equal(input, other)
np_out = np.equal(arr1, arr2)
test_case.assertTrue(np.array_equal(of_out.numpy(), np_out))
test_case.assertTrue(np.array_equal(of_out2.numpy(), np_out))