diff --git a/python/tvm/relay/op/contrib/cmsisnn.py b/python/tvm/relay/op/contrib/cmsisnn.py index 9ca9b979a44d..7af47c3a81a1 100644 --- a/python/tvm/relay/op/contrib/cmsisnn.py +++ b/python/tvm/relay/op/contrib/cmsisnn.py @@ -135,8 +135,6 @@ def check_qnn_conv2d(pattern): return ( conv2d.attrs.out_dtype == "int32" - and int(conv2d.attrs.padding[0]) == int(conv2d.attrs.padding[2]) - and int(conv2d.attrs.padding[1]) == int(conv2d.attrs.padding[3]) and conv2d_input.checked_type.dtype == "int8" and conv2d_weight.checked_type.dtype == "int8" and pattern.checked_type.dtype == "int8" diff --git a/tests/python/contrib/test_cmsisnn/test_conv2d.py b/tests/python/contrib/test_cmsisnn/test_conv2d.py index 7bbbc810894e..d8c559cec6e0 100644 --- a/tests/python/contrib/test_cmsisnn/test_conv2d.py +++ b/tests/python/contrib/test_cmsisnn/test_conv2d.py @@ -69,8 +69,6 @@ def make_model( kernel_w = kernel_shape[w_index] invar = relay.var("input", shape=shape, dtype=dtype) p = (0, 0, 0, 0) - if padding == "INVALID": - p = [1, 2, 2, 1] if padding == "SAME": p = get_same_padding((shape[1], shape[2]), (kernel_h, kernel_w), dilation, strides) invar = relay.nn.pad( @@ -126,10 +124,10 @@ def make_model( @tvm.testing.requires_cmsisnn -@pytest.mark.parametrize("ifm_shape", [(1, 28, 28, 12), (1, 64, 100, 4)]) -@pytest.mark.parametrize("kernel_size", [(3, 3)]) +@pytest.mark.parametrize("ifm_shape", [(1, 25, 25, 12), (1, 64, 100, 4)]) +@pytest.mark.parametrize("kernel_size", [(5, 5)]) @pytest.mark.parametrize("padding", ["SAME", "VALID"]) -@pytest.mark.parametrize("strides, dilation", [((1, 1), (1, 1))]) +@pytest.mark.parametrize("strides, dilation", [((2, 2), (1, 1))]) @pytest.mark.parametrize("relu_type", ["RELU"]) @pytest.mark.parametrize("enable_bias", [True, False]) @pytest.mark.parametrize( @@ -353,19 +351,15 @@ def parameterize_for_invalid_model(test): in_dtype = ["uint8", "int8"] kernel_dtype = ["uint8", "int8"] kernel_zero_point = [-33, 10, 0] - padding = ["SAME", "INVALID"] - all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point, padding) + all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point) all_combinations = filter( lambda parameters: not ( - parameters[0] == "int8" - and parameters[1] == "int8" - and parameters[2] == 0 - and parameters[3] == "SAME" + parameters[0] == "int8" and parameters[1] == "int8" and parameters[2] == 0 ), all_combinations, ) return pytest.mark.parametrize( - ["in_dtype", "kernel_dtype", "kernel_zero_point", "padding"], + ["in_dtype", "kernel_dtype", "kernel_zero_point"], all_combinations, )(test) @@ -376,7 +370,6 @@ def test_invalid_parameters( in_dtype, kernel_dtype, kernel_zero_point, - padding, ): ifm_shape = (1, 28, 28, 12) out_channels = 2 @@ -407,7 +400,7 @@ def test_invalid_parameters( kernel_scale=kernel_scale, output_zero_point=output_zero_point, output_scale=output_scale, - padding=padding, + padding="SAME", strides=(1, 1), dilation=(1, 1), groups=1,