pycaffe output layers is zero

[mbasij1]

i create a prototype like this
input: "data" input_shape { dim: 1 # batchsize dim: 3 # number of colour channels - rgb dim: 55 # width dim: 110 # height } layer { name: "conv1" type: "Convolution" bottom: "data" top: "conv1" param { lr_mult: 1 } param { lr_mult: 2 } convolution_param { num_output: 20 kernel_size: 4 stride: 1 } } layer { name: "conv2" type: "Convolution" bottom: "conv1" top: "conv2" param { lr_mult: 1 } param { lr_mult: 2 } convolution_param { num_output: 20 kernel_size: 4 stride: 1 } } layer { name: "pool1" type: "Pooling" bottom: "conv2" top: "pool1" pooling_param { pool: MAX kernel_size: 2 stride: 2 } } layer { name: "conv3" type: "Convolution" bottom: "pool1" top: "conv3" param { lr_mult: 1 } param { lr_mult: 2 } convolution_param { num_output: 40 kernel_size: 3 stride: 1 } } layer { name: "conv4" type: "Convolution" bottom: "conv3" top: "conv4" param { lr_mult: 1 } param { lr_mult: 2 } convolution_param { num_output: 40 kernel_size: 3 stride: 1 } } layer { name: "pool2" type: "Pooling" bottom: "conv4" top: "pool2" pooling_param { pool: MAX kernel_size: 2 stride: 2 } } layer { name: "conv5" type: "Convolution" bottom: "pool2" top: "conv5" param { lr_mult: 1 } param { lr_mult: 2 } convolution_param { num_output: 60 kernel_size: 3 stride: 1 } } layer { name: "conv6" type: "Convolution" bottom: "conv5" top: "conv6" param { lr_mult: 1 } param { lr_mult: 2 } convolution_param { num_output: 60 kernel_size: 3 stride: 1 } } layer { name: "pool3" type: "Pooling" bottom: "conv6" top: "pool3" pooling_param { pool: MAX kernel_size: 2 stride: 2 } } layer { name: "ip1" type: "InnerProduct" bottom: "pool3" top: "ip1" inner_product_param { num_output: 160 } }
and write pycaffe code like this
`caffe.set_mode_cpu()

net1

net = caffe.Net('/root/deepid3/deploy.prototxt', caffe.TRAIN)
transformer = caffe.io.Transformer({'data': net.blobs['data'].data.shape})
transformer.set_transpose('data', (2,0,1))

transformer.set_channel_swap('data', (2,1,0))

transformer.set_raw_scale('data', 255.0)

im = caffe.io.load_image(y)
net.blobs['data'].data[...] = transformer.preprocess('data', im)
out = net.forward()
print outallways out is {'ip1': array([[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0.]], dtype=float32)}`
i think is my problem but i found that conv1 produce just zero when i remove other layers, i start update that bust still all of output is zero, i check data layer and print data and is have true value,
how can sole that?

[mbasij1]

no one can't help me?

[shelhamer]

Please ask usage and modeling questions on the mailing list. Your model has no weight initialization, and the weights default to zero, and so all of the outputs are zero.

From https://github.com/BVLC/caffe/blob/master/CONTRIBUTING.md:

Please do not post usage, installation, or modeling questions, or other requests for help to Issues.
Use the caffe-users list instead. This helps developers maintain a clear, uncluttered, and efficient view of the state of Caffe.

[aanwark]

@mbasij1 were you able to solve this issue? I have a similar problem.