farshidsp commented on code in PR #13414:
URL: https://github.com/apache/tvm/pull/13414#discussion_r1036550184
##########
python/tvm/topi/nn/depthwise_conv2d.py:
##########
@@ -252,8 +253,18 @@ def depthwise_conv2d_nhwc(Input, Filter, stride, padding,
dilation, out_dtype=No
dilation_h, dilation_w = dilation
batch, in_height, in_width, in_channel = Input.shape
+
+ dim = len(Input.shape) - 2
+
# shape of dilated kernel
- filter_height, filter_width, filter_channel, channel_multiplier =
Filter.shape
+ if kernel_layout == "HWOI":
+ filter_height, filter_width, filter_channel, channel_multiplier =
Filter.shape
+ kernel_permutation_to = [0, 1] + list(range(2, dim + 2))
+ elif kernel_layout == "HWIO":
+ filter_height, filter_width, channel_multiplier, filter_channel =
Filter.shape
+ kernel_permutation_to = [dim + 1, dim] + list(range(dim))
+
+ kernel_permutation_from = np.argsort(kernel_permutation_to)
Review Comment:
I tried to follow
[this](https://github.com/apache/tvm/blob/6782a35018d5df63486569f17296737d75eedc55/python/tvm/topi/nn/conv2d.py#L837)
as much as possible so in the future we can add more features if needed. If
you think this is not the best way I could change it.
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