Eltwise Layer clobbers the first bottom blob

[venkai]

The Eltwise Layer seems to clobber the first bottom blob. This is usually not a problem, since the inputs to Eltwise layers are typically not used again in most nets. However, for some rare cases like hyper-residual nets or symmetric skip-connection based ResNets, this causes a problem.

[drnikolaev]

Hi @venkai thanks for the tip. Could you please attach a sample model prototxt having this issue?

[venkai]

Hi @drnikolaev , here is a minimal prototxt that should reproduce the bug:

layer {
  name: "L_input"  type: "Input"  top: "data"
  input_param { shape { dim: 1 dim: 3 dim: 4 dim: 5 } }
}

layer {
  name: "L0"  type: "Convolution"  bottom: "data"  top: "B0"
  convolution_param {
    num_output: 8  pad: 1  kernel_size: 3
    weight_filler { type: "gaussian"  std: 0.001 }
    bias_filler { type: "gaussian"  mean: 0.1  std: 1 }
  }
}

layer {
  name: "L1"  type: "Convolution"  bottom: "B0"  top: "B1"
  convolution_param {
    num_output: 8  pad: 1  kernel_size: 3
    weight_filler { type: "gaussian"  std: 0.001 }
    bias_filler { type: "gaussian"  mean: 0.1  std: 1 }
  }
}

layer {
  name: "L2"  type: "Eltwise"
  bottom: "B0"  bottom: "B1"  top: "B2"
  eltwise_param { operation: SUM }
}

layer {
  name: "L3"  type: "Convolution"  bottom: "B2"  top: "B3"
  convolution_param {
    num_output: 8  pad: 1  kernel_size: 3
    weight_filler { type: "gaussian"  std: 0.001 }
    bias_filler { type: "gaussian"  mean: 0.1  std: 1 }
  }
}

layer {
  name: "L4"  type: "Eltwise"
  bottom: "B0"  bottom: "B2"  bottom: "B3"  top: "B4"
  eltwise_param { operation: SUM }
}

The network looks like this:

Here, blob B0 is input to both layers L2 and L4, but is clobbered by L2. The output B4 should ideally equal B0 + B2 + B3, but it ends up being equal to *2B2 + B3**. For now, I replaced the Eltwise layers with those from borisgin/nvcaffe-0.16, and the output is as expected.

[mathmanu]

Try commenting out the following lines in the Reshape function of Eltwise layer and see if the issue is resolved.

if (op_ == EltwiseParameter_EltwiseOp_SUM && nocoeffs) { for (int i = 0; i < bottom.size(); ++i) { bottom[i]->ShareDiff(top[0]); } top[0]->ShareData(bottom[0]); }

[drnikolaev]

@venkai could you verify https://github.com/drnikolaev/caffe/tree/caffe-0.17 release candidate?

[drnikolaev]

@venkai Please verify https://github.com/NVIDIA/caffe/tree/v0.17.1 release and reopen the issue if needed.