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Use input_shape instead of input_dim in examples
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lukeyeager committed Aug 20, 2015
1 parent 833b334 commit 2f5889c
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Showing 11 changed files with 66 additions and 44 deletions.
10 changes: 6 additions & 4 deletions examples/cifar10/cifar10_full.prototxt
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Expand Up @@ -2,10 +2,12 @@ name: "CIFAR10_full_deploy"
# N.B. input image must be in CIFAR-10 format
# as described at http://www.cs.toronto.edu/~kriz/cifar.html
input: "data"
input_dim: 1
input_dim: 3
input_dim: 32
input_dim: 32
input_shape {
dim: 1
dim: 3
dim: 32
dim: 32
}
layer {
name: "conv1"
type: "Convolution"
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10 changes: 6 additions & 4 deletions examples/cifar10/cifar10_quick.prototxt
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@@ -1,9 +1,11 @@
name: "CIFAR10_quick_test"
input: "data"
input_dim: 1
input_dim: 3
input_dim: 32
input_dim: 32
input_shape {
dim: 1
dim: 3
dim: 32
dim: 32
}
layer {
name: "conv1"
type: "Convolution"
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10 changes: 6 additions & 4 deletions examples/mnist/lenet.prototxt
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@@ -1,9 +1,11 @@
name: "LeNet"
input: "data"
input_dim: 64
input_dim: 1
input_dim: 28
input_dim: 28
input_shape {
dim: 64
dim: 1
dim: 28
dim: 28
}
layer {
name: "conv1"
type: "Convolution"
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10 changes: 6 additions & 4 deletions examples/net_surgery/bvlc_caffenet_full_conv.prototxt
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@@ -1,10 +1,12 @@
# Fully convolutional network version of CaffeNet.
name: "CaffeNetConv"
input: "data"
input_dim: 1
input_dim: 3
input_dim: 451
input_dim: 451
input_shape {
dim: 1
dim: 3
dim: 451
dim: 451
}
layer {
name: "conv1"
type: "Convolution"
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10 changes: 6 additions & 4 deletions examples/net_surgery/conv.prototxt
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@@ -1,10 +1,12 @@
# Simple single-layer network to showcase editing model parameters.
name: "convolution"
input: "data"
input_dim: 1
input_dim: 1
input_dim: 100
input_dim: 100
input_shape {
dim: 1
dim: 1
dim: 100
dim: 100
}
layer {
name: "conv"
type: "Convolution"
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10 changes: 6 additions & 4 deletions examples/siamese/mnist_siamese.prototxt
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@@ -1,9 +1,11 @@
name: "mnist_siamese"
input: "data"
input_dim: 10000
input_dim: 1
input_dim: 28
input_dim: 28
input_shape {
dim: 10000
dim: 1
dim: 28
dim: 28
}
layer {
name: "conv1"
type: "Convolution"
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10 changes: 6 additions & 4 deletions models/bvlc_alexnet/deploy.prototxt
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@@ -1,9 +1,11 @@
name: "AlexNet"
input: "data"
input_dim: 10
input_dim: 3
input_dim: 227
input_dim: 227
input_shape {
dim: 10
dim: 3
dim: 227
dim: 227
}
layer {
name: "conv1"
type: "Convolution"
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10 changes: 6 additions & 4 deletions models/bvlc_googlenet/deploy.prototxt
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@@ -1,9 +1,11 @@
name: "GoogleNet"
input: "data"
input_dim: 10
input_dim: 3
input_dim: 224
input_dim: 224
input_shape {
dim: 10
dim: 3
dim: 224
dim: 224
}
layer {
name: "conv1/7x7_s2"
type: "Convolution"
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10 changes: 6 additions & 4 deletions models/bvlc_reference_caffenet/deploy.prototxt
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@@ -1,9 +1,11 @@
name: "CaffeNet"
input: "data"
input_dim: 10
input_dim: 3
input_dim: 227
input_dim: 227
input_shape {
dim: 10
dim: 3
dim: 227
dim: 227
}
layer {
name: "conv1"
type: "Convolution"
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10 changes: 6 additions & 4 deletions models/bvlc_reference_rcnn_ilsvrc13/deploy.prototxt
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@@ -1,9 +1,11 @@
name: "R-CNN-ilsvrc13"
input: "data"
input_dim: 10
input_dim: 3
input_dim: 227
input_dim: 227
input_shape {
dim: 10
dim: 3
dim: 227
dim: 227
}
layer {
name: "conv1"
type: "Convolution"
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10 changes: 6 additions & 4 deletions models/finetune_flickr_style/deploy.prototxt
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@@ -1,9 +1,11 @@
name: "FlickrStyleCaffeNet"
input: "data"
input_dim: 10
input_dim: 3
input_dim: 227
input_dim: 227
input_shape {
dim: 10
dim: 3
dim: 227
dim: 227
}
layer {
name: "conv1"
type: "Convolution"
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