Shawn-Inspur commented on a change in pull request #6121:
URL: https://github.com/apache/incubator-tvm/pull/6121#discussion_r467373356
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File path: python/tvm/relay/op/strategy/cuda.py
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@@ -172,6 +172,21 @@ def conv2d_strategy_cuda(attrs, inputs, out_type, target):
wrap_topi_schedule(topi.cuda.schedule_conv2d_nhwc_tensorcore),
name="conv2d_nhwc_tensorcore.cuda",
plevel=20)
+ elif layout == "HWNC":
+ assert kernel_layout in ["HWOI", "HWOI16o16i", "HWOI8o32i",
"HWOI32o16i"]
+ _, _, N, in_channels = get_const_tuple(data.shape)
+ pre_computed = len(kernel.shape) == 6
+ if pre_computed:
+ _, _, oc_chunk, _, oc_block_factor, _ =
get_const_tuple(kernel.shape)
+ out_channels = oc_chunk * oc_block_factor
+ else:
+ _, _, out_channels, _ = get_const_tuple(kernel.shape)
+ if topi.cuda.is_shape_tensorcore_direct_qualified(batch=N,
in_channels=in_channels, num_filter=out_channels, in_dtype=data.dtype):
+ strategy.add_implementation(
+ wrap_compute_conv2d(topi.cuda.conv2d_hwnc_tensorcore),
+
wrap_topi_schedule(topi.cuda.schedule_conv2d_hwnc_tensorcore),
+ name="conv2d_hwnc_tensorcore_direct.cuda",
+ plevel=20)
Review comment:
Because there is only tensor core implementation of HWNC layout, how to
deal the cases when the shapes are not satisfied by tensor core?
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