Function test_binary_minmax

tests/python/relax/test_op_gradient_numeric.py:256–264

(target, dev, binary_minmax_op_func)

@tvm.testing.parametrize_targets("llvm")
def test_binary_minmax(target, dev, binary_minmax_op_func):
    # Checking numerical gradient of min and max requires data1_numpy[i] != data2_numpy[i]
    # for all possible i.
    # If data1_numpy[i] == data2_numpy[i], the operator is not differentiable w.r.t. place i
    data1_numpy = np.random.uniform(1, 1.1, (3, 3)).astype(np.float32)
    delta = np.random.uniform(1, 1.1, (3, 3)).astype(np.float32)
    sign = np.random.randint(0, 2, (3, 3)).astype(np.float32) * 2 - 1
    data2_numpy = data1_numpy + delta * sign
    relax_check_gradients(binary_minmax_op_func, [data1_numpy, data2_numpy], target, dev)


(binary_cmp_op_func,) = tvm.testing.parameters(