masahi commented on a change in pull request #9996:
URL: https://github.com/apache/tvm/pull/9996#discussion_r810773245
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File path: python/tvm/topi/x86/conv2d_alter_op.py
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@@ -164,25 +164,12 @@ def _alter_conv2d_layout(attrs, inputs, tinfos, out_type):
batch_size, in_channel, height, width =
get_const_tuple(data_tensor.shape)
out_channel, channel_multiplier, kh, kw =
get_const_tuple(kernel_tensor.shape)
ic_bn, oc_bn = cfg["tile_ic"].size[-1], cfg["tile_oc"].size[-1]
- n_elems = 4
-
- # convert kernel data layout from 4D to 7D
- data_expr, kernel_expr = inputs
- kernel_IHWO = relay.transpose(kernel_expr, axes=(1, 2, 3, 0))
- kernel_IHWOo = relay.reshape(kernel_IHWO, (in_channel, kh, kw,
out_channel // oc_bn, oc_bn))
- kernel_OHWoI = relay.transpose(kernel_IHWOo, axes=(3, 1, 2, 4, 0))
- kernel_OHWoIi = relay.reshape(
- kernel_OHWoI, (out_channel // oc_bn, kh, kw, oc_bn, in_channel //
ic_bn, ic_bn)
- )
- kernel_OHWoIie = relay.reshape(
- kernel_OHWoIi,
- (out_channel // oc_bn, kh, kw, oc_bn, in_channel // ic_bn, ic_bn
// n_elems, n_elems),
- )
- kernel_OIHWioe = relay.transpose(kernel_OHWoIie, axes=(0, 4, 1, 2, 5,
3, 6))
# update new attrs
+ n_elems = 4
new_attrs["channels"] = out_channel
new_attrs["data_layout"] = "NCHW%dc" % ic_bn
+ new_attrs["kernel_layout"] = "OIHW{:n}i{:n}o{:n}i".format(ic_bn //
n_elems, oc_bn, n_elems)
Review comment:
Great!
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