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author | Evan Shelhamer <shelhamer@imaginarynumber.net> | 2014-03-18 13:54:17 -0700 |
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committer | Evan Shelhamer <shelhamer@imaginarynumber.net> | 2014-03-18 14:03:05 -0700 |
commit | d124b8ffe8b9680fa4e0339a0a698622472a0610 (patch) | |
tree | e96297bf8ce03667b8a8e96d1c9e2d50fca18717 /examples/imagenet/imagenet_deploy.prototxt | |
parent | c5ab83781fa136ffc77be0bbabc4a55a60b2285d (diff) | |
download | caffeonacl-d124b8ffe8b9680fa4e0339a0a698622472a0610.tar.gz caffeonacl-d124b8ffe8b9680fa4e0339a0a698622472a0610.tar.bz2 caffeonacl-d124b8ffe8b9680fa4e0339a0a698622472a0610.zip |
drop models/ in favor of examples/
Move the Caffe reference imagenet model and script to fetch it to
examples/imagenet.
Caffe bundles reference models, but it makes more sense to keep them
close to examples.
Diffstat (limited to 'examples/imagenet/imagenet_deploy.prototxt')
-rw-r--r-- | examples/imagenet/imagenet_deploy.prototxt | 324 |
1 files changed, 324 insertions, 0 deletions
diff --git a/examples/imagenet/imagenet_deploy.prototxt b/examples/imagenet/imagenet_deploy.prototxt new file mode 100644 index 00000000..0b1f41ab --- /dev/null +++ b/examples/imagenet/imagenet_deploy.prototxt @@ -0,0 +1,324 @@ +name: "CaffeNet" +input: "data" +input_dim: 10 +input_dim: 3 +input_dim: 227 +input_dim: 227 +layers { + layer { + name: "conv1" + type: "conv" + num_output: 96 + kernelsize: 11 + stride: 4 + weight_filler { + type: "gaussian" + std: 0.01 + } + bias_filler { + type: "constant" + value: 0. + } + blobs_lr: 1. + blobs_lr: 2. + weight_decay: 1. + weight_decay: 0. + } + bottom: "data" + top: "conv1" +} +layers { + layer { + name: "relu1" + type: "relu" + } + bottom: "conv1" + top: "conv1" +} +layers { + layer { + name: "pool1" + type: "pool" + pool: MAX + kernelsize: 3 + stride: 2 + } + bottom: "conv1" + top: "pool1" +} +layers { + layer { + name: "norm1" + type: "lrn" + local_size: 5 + alpha: 0.0001 + beta: 0.75 + } + bottom: "pool1" + top: "norm1" +} +layers { + layer { + name: "conv2" + type: "conv" + num_output: 256 + group: 2 + kernelsize: 5 + pad: 2 + weight_filler { + type: "gaussian" + std: 0.01 + } + bias_filler { + type: "constant" + value: 1. + } + blobs_lr: 1. + blobs_lr: 2. + weight_decay: 1. + weight_decay: 0. + } + bottom: "norm1" + top: "conv2" +} +layers { + layer { + name: "relu2" + type: "relu" + } + bottom: "conv2" + top: "conv2" +} +layers { + layer { + name: "pool2" + type: "pool" + pool: MAX + kernelsize: 3 + stride: 2 + } + bottom: "conv2" + top: "pool2" +} +layers { + layer { + name: "norm2" + type: "lrn" + local_size: 5 + alpha: 0.0001 + beta: 0.75 + } + bottom: "pool2" + top: "norm2" +} +layers { + layer { + name: "conv3" + type: "conv" + num_output: 384 + kernelsize: 3 + pad: 1 + weight_filler { + type: "gaussian" + std: 0.01 + } + bias_filler { + type: "constant" + value: 0. + } + blobs_lr: 1. + blobs_lr: 2. + weight_decay: 1. + weight_decay: 0. + } + bottom: "norm2" + top: "conv3" +} +layers { + layer { + name: "relu3" + type: "relu" + } + bottom: "conv3" + top: "conv3" +} +layers { + layer { + name: "conv4" + type: "conv" + num_output: 384 + group: 2 + kernelsize: 3 + pad: 1 + weight_filler { + type: "gaussian" + std: 0.01 + } + bias_filler { + type: "constant" + value: 1. + } + blobs_lr: 1. + blobs_lr: 2. + weight_decay: 1. + weight_decay: 0. + } + bottom: "conv3" + top: "conv4" +} +layers { + layer { + name: "relu4" + type: "relu" + } + bottom: "conv4" + top: "conv4" +} +layers { + layer { + name: "conv5" + type: "conv" + num_output: 256 + group: 2 + kernelsize: 3 + pad: 1 + weight_filler { + type: "gaussian" + std: 0.01 + } + bias_filler { + type: "constant" + value: 1. + } + blobs_lr: 1. + blobs_lr: 2. + weight_decay: 1. + weight_decay: 0. + } + bottom: "conv4" + top: "conv5" +} +layers { + layer { + name: "relu5" + type: "relu" + } + bottom: "conv5" + top: "conv5" +} +layers { + layer { + name: "pool5" + type: "pool" + kernelsize: 3 + pool: MAX + stride: 2 + } + bottom: "conv5" + top: "pool5" +} +layers { + layer { + name: "fc6" + type: "innerproduct" + num_output: 4096 + weight_filler { + type: "gaussian" + std: 0.005 + } + bias_filler { + type: "constant" + value: 1. + } + blobs_lr: 1. + blobs_lr: 2. + weight_decay: 1. + weight_decay: 0. + } + bottom: "pool5" + top: "fc6" +} +layers { + layer { + name: "relu6" + type: "relu" + } + bottom: "fc6" + top: "fc6" +} +layers { + layer { + name: "drop6" + type: "dropout" + dropout_ratio: 0.5 + } + bottom: "fc6" + top: "fc6" +} +layers { + layer { + name: "fc7" + type: "innerproduct" + num_output: 4096 + weight_filler { + type: "gaussian" + std: 0.005 + } + bias_filler { + type: "constant" + value: 1. + } + blobs_lr: 1. + blobs_lr: 2. + weight_decay: 1. + weight_decay: 0. + } + bottom: "fc6" + top: "fc7" +} +layers { + layer { + name: "relu7" + type: "relu" + } + bottom: "fc7" + top: "fc7" +} +layers { + layer { + name: "drop7" + type: "dropout" + dropout_ratio: 0.5 + } + bottom: "fc7" + top: "fc7" +} +layers { + layer { + name: "fc8" + type: "innerproduct" + num_output: 1000 + weight_filler { + type: "gaussian" + std: 0.01 + } + bias_filler { + type: "constant" + value: 0 + } + blobs_lr: 1. + blobs_lr: 2. + weight_decay: 1. + weight_decay: 0. + } + bottom: "fc7" + top: "fc8" +} +layers { + layer { + name: "prob" + type: "softmax" + } + bottom: "fc8" + top: "prob" +} |