eltwise_layer.cpp:34] Check failed: bottom[0]->shape() == bottom[i]->shape() bottom[0]: 1 21 333 500 (3496500), bottom[1]: 1 21 375 500 (3937500)

[Hesansan]

I combin CRNasRNN to FCN，but this error that i can not deal with it,
the title is information of error

[Hesansan]

layer {
name: "fuse_pool3"
type: "Eltwise"
bottom: "score4"
bottom: "score-pool3c"
top: "score-final"
eltwise_param {
operation: SUM
}
}
layer {
name: "upsample"
type: "Deconvolution"
bottom: "score-final"
top: "bigscore"
param {
lr_mult: 0
}
convolution_param {
num_output: 21
bias_term: false
kernel_size: 16
stride: 8
weight_filler: { type: "bilinear" }
}
}
layer {
type: 'Crop'
name: 'crop'
bottom: 'bigscore'
bottom: 'data'
top: 'coarse'
crop_param {
axis: 2
offset: 31
}
}

layer {
type: 'Split'
name: 'splitting'
bottom: 'coarse'
top: 'unary'
top: 'Q0'
}

layer {
name: "inference1"#if you set name "inference1", code will load parameters from caffemodel.
type: "MultiStageMeanfield"
bottom: "unary"
bottom: "Q0"
bottom: "data"
top: "pred"
param {
lr_mult: 10000#learning rate for W_G
}
param {
lr_mult: 10000#learning rate for W_B
}
param {
lr_mult: 1000 #learning rate for compatiblity transform matrix
}
multi_stage_meanfield_param {
num_iterations: 10
compatibility_mode: POTTS#Initialize the compatilibity transform matrix with a matrix whose diagonal is -1.
threshold: 2
theta_alpha: 160
theta_beta: 3
theta_gamma: 3
spatial_filter_weights_str: "3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3"
bilateral_filter_weights_str: "5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5"
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "pred"
bottom: "label"
top: "loss"
loss_param {
ignore_label: 255
normalize: false
}
}

this is part of my code

[bittnt]

You need to pad the image as we did in the demo inference code. Otherwise, you would see this error.