Remove the redundant index_array GPU tests from test_operator_gpu.py

tests/python/gpu/test_operator_gpu.py

@@ -2130,68 +2130,6 @@ def test_bilinear_sampler_versions():
                 if req_dict['grid'] is 'write':
                     assert_almost_equal(exe.grad_dict['grid'].asnumpy(), exe_list[ref_idx].grad_dict['grid'].asnumpy(), rtol=1e-3, atol=1e-5)
 
-@with_seed()
-def test_index_array_default():
-    for shape in [(10,), (7, 5, 29), (5, 7, 11, 13, 17, 19)]:
-        data  = mx.symbol.Variable("data")
-        index_array = mx.sym.contrib.index_array(data)
-
-        input_array = np.ones(shape)
-        mgrid = np.mgrid[tuple(slice(0, x) for x in shape)]
-        expected = np.stack(mgrid, axis=-1)
-
-        check_symbolic_forward(index_array, [input_array], [expected])
-        check_symbolic_backward(index_array, [input_array], [np.ones(expected.shape)], [np.zeros_like(input_array)])
-
-@with_seed()
-def test_index_array_default_zero_dim():
-    with mx.np_compat(active=True):
-        data  = mx.symbol.Variable("data")
-        index_array = mx.sym.contrib.index_array(data)
-
-        input_array = np.ones(())
-        expected = np.zeros((0,))
-
-        check_symbolic_forward(index_array, [input_array], [expected])
-        check_symbolic_backward(index_array, [input_array], [np.ones(expected.shape)], [np.zeros_like(input_array)])
-
-@with_seed()
-def test_index_array_default_zero_size():
-    with mx.np_compat(active=True):
-        data  = mx.symbol.Variable("data")
-        index_array = mx.sym.contrib.index_array(data)
-
-        input_array = np.ones((0, 0, 0))
-        expected = np.zeros((0, 0, 0, 3))
-
-        check_symbolic_forward(index_array, [input_array], [expected])
-        check_symbolic_backward(index_array, [input_array], [np.ones(expected.shape)], [np.zeros_like(input_array)])
-
-@with_seed()
-def test_index_array_select_axes():
-    shape = (5, 7, 11, 13, 17, 19)
-    for axes in [(3,), (4, 1), (5, 1, 3), (-1,), (-5, -1, -3)]:
-        data  = mx.symbol.Variable("data")
-        index_array = mx.sym.contrib.index_array(data, axes=axes)
-
-        input_array = np.ones(shape)
-        mgrid = np.mgrid[tuple(slice(0, x) for x in shape)]
-        expected = np.stack(mgrid, axis=-1)[..., axes]
-
-        check_symbolic_forward(index_array, [input_array], [expected])
-        check_symbolic_backward(index_array, [input_array], [np.ones(expected.shape)], [np.zeros_like(input_array)])
-
-@with_seed()
-def test_index_array_select_axes_zero_size():
-    with mx.np_compat(active=True):
-        data  = mx.symbol.Variable("data")
-        index_array = mx.sym.contrib.index_array(data, axes=(2, 1))
-
-        input_array = np.ones((0, 0, 0, 0))
-        expected = np.zeros((0, 0, 2))
-
-        check_symbolic_forward(index_array, [input_array], [expected])
-        check_symbolic_backward(index_array, [input_array], [np.ones(expected.shape)], [np.zeros_like(input_array)])
 
 # isolated execution bulking test function to be invoked with different env var settings
 def _test_bulking_in_process(seed, time_per_iteration):