ashutosh-arm commented on a change in pull request #9409:
URL: https://github.com/apache/tvm/pull/9409#discussion_r752179676
##########
File path: tests/python/contrib/test_cmsisnn/test_conv2d.py
##########
@@ -147,40 +149,45 @@ def test_op_int8(
input_scale,
kernel_scale,
out_channels,
+ conv_type,
+ depth_multiplier,
):
interface_api = "c"
use_unpacked_api = True
test_runner = AOT_CORSTONE300_RUNNER
- kernel_zero_point = 0
+ dtype = "int8"
groups = 1
weight_format = "HWIO"
kernel_h = kernel_size[0]
kernel_w = kernel_size[1]
- dtype = "int8"
+ kernel_shape = (kernel_h, kernel_w, ifm_shape[3] // groups, out_channels)
+ kernel_zero_point = 0
in_min, in_max = get_range_for_dtype_str(dtype)
- weight_shape = None
- if weight_format == "HWIO":
- weight_shape = (kernel_h, kernel_w, ifm_shape[3] // groups,
out_channels)
- else:
- weight_shape = (kernel_h, kernel_w, ifm_shape[3], out_channels)
+ if conv_type == "depthwise":
+ groups = ifm_shape[3]
+ weight_format = "HWOI"
+ kernel_shape = (kernel_h, kernel_w, ifm_shape[3], depth_multiplier)
+ out_channels = ifm_shape[3] * depth_multiplier
+ ks_len = len(kernel_scale)
+ kernel_scale = [kernel_scale[i % ks_len] for i in range(out_channels)]
Review comment:
Since depthwise uses convolution everywhere, does it not make sense to
keep them combined? In Relay only few attrs differ. Although, CMSIS-NN apis are
different for them.
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