ashutosh-arm commented on code in PR #12006:
URL: https://github.com/apache/tvm/pull/12006#discussion_r916040500
##########
tests/python/contrib/test_cmsisnn/test_conv2d.py:
##########
@@ -540,6 +542,111 @@ def test_depthwise_int8(
)
+@tvm.testing.requires_cmsisnn
+@pytest.mark.parametrize("padding", ["SAME", "VALID"])
+@pytest.mark.parametrize("strides, dilation", [((1, 1), (1, 1))])
+@pytest.mark.parametrize("relu_type", ["RELU", "NONE"])
+@pytest.mark.parametrize("depth_multiplier", [1, 3])
+@pytest.mark.parametrize(
+ "input_zero_point, input_scale, kernel_scale",
+ [
+ (
+ 10,
+ 0.0128,
+ [0.11, 0.22],
+ ),
+ (
+ -64,
+ 1,
+ [1, 0.0256, 1.37],
+ ),
+ ],
+)
+def test_relay_conv2d_cmsisnn_depthwise_int8(
+ padding,
+ strides,
+ dilation,
+ relu_type,
+ input_zero_point,
+ input_scale,
+ kernel_scale,
+ depth_multiplier,
+):
+ """Tests QNN Depthwise int8 op via CMSIS-NN"""
+ interface_api = "c"
+ use_unpacked_api = True
+ test_runner = AOT_USMP_CORSTONE300_RUNNER
+
+ dtype = "int8"
+ in_min, in_max = get_range_for_dtype_str(dtype)
+
+ ifm_shape = (1, 24, 24, 1)
+ groups = ifm_shape[3]
+ weight_format = "HWIO"
+ (kernel_h, kernel_w) = (3, 3)
+ kernel_shape = (kernel_h, kernel_w, ifm_shape[3], depth_multiplier)
+ out_channels = ifm_shape[3] * depth_multiplier
+ enable_bias = True
+ ks_len = len(kernel_scale)
+ kernel_zero_point = 0
+ kernel_scale = [kernel_scale[i % ks_len] for i in range(out_channels)]
+
+ output_scale, output_zero_point = get_conv2d_qnn_params(
+ kernel_shape,
+ input_scale,
+ input_zero_point,
+ kernel_scale,
+ kernel_zero_point,
+ dtype,
+ dtype,
+ dtype,
+ True,
+ )
+
+ model, params = make_model(
+ ifm_shape,
+ kernel_shape,
+ input_zero_point,
+ input_scale,
+ kernel_zero_point,
+ kernel_scale,
+ output_zero_point,
+ output_scale,
+ padding,
+ strides,
+ dilation,
+ groups,
+ dtype,
+ dtype,
+ out_channels,
+ weight_format,
+ enable_bias,
+ relu_type,
+ )
+ orig_mod = make_module(model)
+ cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod, params)
+
+ # validate pattern matching
+ assert_partitioned_function(orig_mod, cmsisnn_mod)
Review Comment:
I have added this check in the same test.
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