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author | Evan Shelhamer <shelhamer@imaginarynumber.net> | 2014-06-12 16:00:49 -0700 |
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committer | Evan Shelhamer <shelhamer@imaginarynumber.net> | 2014-06-12 16:00:49 -0700 |
commit | 506e476047a3b246e57cc4c0cb4d702e686f2009 (patch) | |
tree | da02727053a2c6d0666262008d51afd9b83344da /examples/imagenet | |
parent | 8f8aa9a95dfdd5e6660d6f3205b38e97c979394b (diff) | |
parent | c3440fa48b651159ab41d96d8a6c4efdeeb4ffb2 (diff) | |
download | caffeonacl-506e476047a3b246e57cc4c0cb4d702e686f2009.tar.gz caffeonacl-506e476047a3b246e57cc4c0cb4d702e686f2009.tar.bz2 caffeonacl-506e476047a3b246e57cc4c0cb4d702e686f2009.zip |
Merge pull request #455 from shelhamer/pycaffe-save
Save from python for net surgery
Diffstat (limited to 'examples/imagenet')
-rw-r--r-- | examples/imagenet/imagenet_full_conv.prototxt | 215 |
1 files changed, 215 insertions, 0 deletions
diff --git a/examples/imagenet/imagenet_full_conv.prototxt b/examples/imagenet/imagenet_full_conv.prototxt new file mode 100644 index 00000000..6473c1f7 --- /dev/null +++ b/examples/imagenet/imagenet_full_conv.prototxt @@ -0,0 +1,215 @@ +name: "CaffeNetConv" +input: "data" +input_dim: 1 +input_dim: 3 +input_dim: 454 +input_dim: 454 +layers { + name: "conv1" + type: CONVOLUTION + bottom: "data" + top: "conv1" + convolution_param { + num_output: 96 + kernel_size: 11 + stride: 4 + } +} +layers { + name: "relu1" + type: RELU + bottom: "conv1" + top: "conv1" +} +layers { + name: "pool1" + type: POOLING + bottom: "conv1" + top: "pool1" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layers { + name: "norm1" + type: LRN + bottom: "pool1" + top: "norm1" + lrn_param { + local_size: 5 + alpha: 0.0001 + beta: 0.75 + } +} +layers { + name: "conv2" + type: CONVOLUTION + bottom: "norm1" + top: "conv2" + convolution_param { + num_output: 256 + pad: 2 + kernel_size: 5 + group: 2 + } +} +layers { + name: "relu2" + type: RELU + bottom: "conv2" + top: "conv2" +} +layers { + name: "pool2" + type: POOLING + bottom: "conv2" + top: "pool2" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layers { + name: "norm2" + type: LRN + bottom: "pool2" + top: "norm2" + lrn_param { + local_size: 5 + alpha: 0.0001 + beta: 0.75 + } +} +layers { + name: "conv3" + type: CONVOLUTION + bottom: "norm2" + top: "conv3" + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + } +} +layers { + name: "relu3" + type: RELU + bottom: "conv3" + top: "conv3" +} +layers { + name: "conv4" + type: CONVOLUTION + bottom: "conv3" + top: "conv4" + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + group: 2 + } +} +layers { + name: "relu4" + type: RELU + bottom: "conv4" + top: "conv4" +} +layers { + name: "conv5" + type: CONVOLUTION + bottom: "conv4" + top: "conv5" + convolution_param { + num_output: 256 + pad: 1 + kernel_size: 3 + group: 2 + } +} +layers { + name: "relu5" + type: RELU + bottom: "conv5" + top: "conv5" +} +layers { + name: "pool5" + type: POOLING + bottom: "conv5" + top: "pool5" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layers { + name: "fc6-conv" + type: CONVOLUTION + bottom: "pool5" + top: "fc6-conv" + convolution_param { + num_output: 4096 + kernel_size: 6 + } +} +layers { + name: "relu6" + type: RELU + bottom: "fc6-conv" + top: "fc6-conv" +} +layers { + name: "drop6" + type: DROPOUT + bottom: "fc6-conv" + top: "fc6-conv" + dropout_param { + dropout_ratio: 0.5 + } +} +layers { + name: "fc7-conv" + type: CONVOLUTION + bottom: "fc6-conv" + top: "fc7-conv" + convolution_param { + num_output: 4096 + kernel_size: 1 + } +} +layers { + name: "relu7" + type: RELU + bottom: "fc7-conv" + top: "fc7-conv" +} +layers { + name: "drop7" + type: DROPOUT + bottom: "fc7-conv" + top: "fc7-conv" + dropout_param { + dropout_ratio: 0.5 + } +} +layers { + name: "fc8-conv" + type: CONVOLUTION + bottom: "fc7-conv" + top: "fc8-conv" + convolution_param { + num_output: 1000 + kernel_size: 1 + } +} +layers { + name: "prob" + type: SOFTMAX + bottom: "fc8-conv" + top: "prob" +} |