masahi commented on issue #4771: [Relay] Added Merge Composite pass URL: https://github.com/apache/incubator-tvm/pull/4771#issuecomment-578057856 ok I already have a working test case for detecting conv + bias + relu (Note the "Composite" attribute). Now I really want to hook this up with dnnl "compiler" attribute to enable codegen. ``` def @main(%data: Tensor[(1, 3, 224, 224), float32]) -> Tensor[(1, 16, 224, 224), float32] { %2 = fn (%data1: Tensor[(1, 3, 224, 224), float32], %weight: Tensor[(16, 3, 3, 3), float32], %bias: Tensor[(16, 1, 1), float32], Primitive=1, Composite="dnnl.conv_bias_relu") -> Tensor[(1, 16, 224, 224), float32] { %0 = nn.conv2d(%data1, %weight, padding=[1, 1], channels=16, kernel_size=[3, 3]) /* ty=Tensor[(1, 16, 224, 224), float32] */; %1 = add(%0, %bias) /* ty=Tensor[(1, 16, 224, 224), float32] */; nn.relu(%1) /* ty=Tensor[(1, 16, 224, 224), float32] */ }; %3 = %2(%data, meta[relay.Constant][0] /* ty=Tensor[(16, 3, 3, 3), float32] */ /* ty=Tensor[(16, 3, 3, 3), float32] */, meta[relay.Constant][1] /* ty=Tensor[(16, 1, 1), float32] */ /* ty=Tensor[(16, 1, 1), float32] */) /* ty=Tensor[(1, 16, 224, 224), float32] */; %6 = fn (%data2: Tensor[(1, 16, 224, 224), float32], %weight1: Tensor[(16, 16, 3, 3), float32], %bias1: Tensor[(16, 1, 1), float32], Primitive=1, Composite="dnnl.conv_bias_relu") -> Tensor[(1, 16, 224, 224), float32] { %4 = nn.conv2d(%data2, %weight1, padding=[1, 1], channels=16, kernel_size=[3, 3]) /* ty=Tensor[(1, 16, 224, 224), float32] */; %5 = add(%4, %bias1) /* ty=Tensor[(1, 16, 224, 224), float32] */; nn.relu(%5) /* ty=Tensor[(1, 16, 224, 224), float32] */ }; %6(%3, meta[relay.Constant][2] /* ty=Tensor[(16, 16, 3, 3), float32] */ /* ty=Tensor[(16, 16, 3, 3), float32] */, meta[relay.Constant][3] /* ty=Tensor[(16, 1, 1), float32] */ /* ty=Tensor[(16, 1, 1), float32] */) /* ty=Tensor[(1, 16, 224, 224), float32] */ } ```
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