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-rw-r--r--examples/cifar10/cifar10_full.prototxt11
-rw-r--r--examples/cifar10/cifar10_quick.prototxt11
-rw-r--r--examples/cpp_classification/classification.cpp2
-rw-r--r--examples/mnist/lenet.prototxt11
-rw-r--r--examples/net_surgery.ipynb43
-rw-r--r--examples/net_surgery/bvlc_caffenet_full_conv.prototxt15
-rw-r--r--examples/net_surgery/conv.prototxt11
-rw-r--r--examples/siamese/mnist_siamese.prototxt13
-rw-r--r--models/bvlc_alexnet/deploy.prototxt11
-rw-r--r--models/bvlc_googlenet/deploy.prototxt11
-rw-r--r--models/bvlc_reference_caffenet/deploy.prototxt11
-rw-r--r--models/bvlc_reference_rcnn_ilsvrc13/deploy.prototxt11
-rw-r--r--models/finetune_flickr_style/deploy.prototxt11
13 files changed, 83 insertions, 89 deletions
diff --git a/examples/cifar10/cifar10_full.prototxt b/examples/cifar10/cifar10_full.prototxt
index 446479d..83cf0d8 100644
--- a/examples/cifar10/cifar10_full.prototxt
+++ b/examples/cifar10/cifar10_full.prototxt
@@ -1,12 +1,11 @@
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_shape {
- dim: 1
- dim: 3
- dim: 32
- dim: 32
+layer {
+ name: "data"
+ type: "Input"
+ top: "data"
+ input_param { shape: { dim: 1 dim: 3 dim: 32 dim: 32 } }
}
layer {
name: "conv1"
diff --git a/examples/cifar10/cifar10_quick.prototxt b/examples/cifar10/cifar10_quick.prototxt
index 9352fbf..cf3b2a3 100644
--- a/examples/cifar10/cifar10_quick.prototxt
+++ b/examples/cifar10/cifar10_quick.prototxt
@@ -1,10 +1,9 @@
name: "CIFAR10_quick_test"
-input: "data"
-input_shape {
- dim: 1
- dim: 3
- dim: 32
- dim: 32
+layer {
+ name: "data"
+ type: "Input"
+ top: "data"
+ input_param { shape: { dim: 1 dim: 3 dim: 32 dim: 32 } }
}
layer {
name: "conv1"
diff --git a/examples/cpp_classification/classification.cpp b/examples/cpp_classification/classification.cpp
index 974662e..6b67c53 100644
--- a/examples/cpp_classification/classification.cpp
+++ b/examples/cpp_classification/classification.cpp
@@ -159,7 +159,7 @@ std::vector<float> Classifier::Predict(const cv::Mat& img) {
Preprocess(img, &input_channels);
- net_->ForwardPrefilled();
+ net_->Forward();
/* Copy the output layer to a std::vector */
Blob<float>* output_layer = net_->output_blobs()[0];
diff --git a/examples/mnist/lenet.prototxt b/examples/mnist/lenet.prototxt
index dff7123..8cf78e6 100644
--- a/examples/mnist/lenet.prototxt
+++ b/examples/mnist/lenet.prototxt
@@ -1,10 +1,9 @@
name: "LeNet"
-input: "data"
-input_shape {
- dim: 64
- dim: 1
- dim: 28
- dim: 28
+layer {
+ name: "data"
+ type: "Input"
+ top: "data"
+ input_param { shape: { dim: 64 dim: 1 dim: 28 dim: 28 } }
}
layer {
name: "conv1"
diff --git a/examples/net_surgery.ipynb b/examples/net_surgery.ipynb
index ff780fb..a6092db 100644
--- a/examples/net_surgery.ipynb
+++ b/examples/net_surgery.ipynb
@@ -5494,48 +5494,47 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "1,2c1\r\n",
+ "1,2c1,2\r\n",
"< # Fully convolutional network version of CaffeNet.\r\n",
"< name: \"CaffeNetConv\"\r\n",
"---\r\n",
"> name: \"CaffeNet\"\r\n",
- "4c3\r\n",
- "< input_dim: 1\r\n",
+ "> input: \"data\"\r\n",
+ "7,11c7\r\n",
+ "< input_param {\r\n",
+ "< # initial shape for a fully convolutional network:\r\n",
+ "< # the shape can be set for each input by reshape.\r\n",
+ "< shape: { dim: 1 dim: 3 dim: 451 dim: 451 }\r\n",
+ "< }\r\n",
"---\r\n",
- "> input_dim: 10\r\n",
- "6,7c5,6\r\n",
- "< input_dim: 451\r\n",
- "< input_dim: 451\r\n",
- "---\r\n",
- "> input_dim: 227\r\n",
- "> input_dim: 227\r\n",
- "152,153c151,152\r\n",
+ "> input_param { shape: { dim: 10 dim: 3 dim: 227 dim: 227 } }\r\n",
+ "157,158c153,154\r\n",
"< name: \"fc6-conv\"\r\n",
"< type: \"Convolution\"\r\n",
"---\r\n",
"> name: \"fc6\"\r\n",
"> type: \"InnerProduct\"\r\n",
- "155,156c154,155\r\n",
+ "160,161c156,157\r\n",
"< top: \"fc6-conv\"\r\n",
"< convolution_param {\r\n",
"---\r\n",
"> top: \"fc6\"\r\n",
"> inner_product_param {\r\n",
- "158d156\r\n",
+ "163d158\r\n",
"< kernel_size: 6\r\n",
- "164,165c162,163\r\n",
+ "169,170c164,165\r\n",
"< bottom: \"fc6-conv\"\r\n",
"< top: \"fc6-conv\"\r\n",
"---\r\n",
"> bottom: \"fc6\"\r\n",
"> top: \"fc6\"\r\n",
- "170,171c168,169\r\n",
+ "175,176c170,171\r\n",
"< bottom: \"fc6-conv\"\r\n",
"< top: \"fc6-conv\"\r\n",
"---\r\n",
"> bottom: \"fc6\"\r\n",
"> top: \"fc6\"\r\n",
- "177,181c175,179\r\n",
+ "182,186c177,181\r\n",
"< name: \"fc7-conv\"\r\n",
"< type: \"Convolution\"\r\n",
"< bottom: \"fc6-conv\"\r\n",
@@ -5547,21 +5546,21 @@
"> bottom: \"fc6\"\r\n",
"> top: \"fc7\"\r\n",
"> inner_product_param {\r\n",
- "183d180\r\n",
+ "188d182\r\n",
"< kernel_size: 1\r\n",
- "189,190c186,187\r\n",
+ "194,195c188,189\r\n",
"< bottom: \"fc7-conv\"\r\n",
"< top: \"fc7-conv\"\r\n",
"---\r\n",
"> bottom: \"fc7\"\r\n",
"> top: \"fc7\"\r\n",
- "195,196c192,193\r\n",
+ "200,201c194,195\r\n",
"< bottom: \"fc7-conv\"\r\n",
"< top: \"fc7-conv\"\r\n",
"---\r\n",
"> bottom: \"fc7\"\r\n",
"> top: \"fc7\"\r\n",
- "202,206c199,203\r\n",
+ "207,211c201,205\r\n",
"< name: \"fc8-conv\"\r\n",
"< type: \"Convolution\"\r\n",
"< bottom: \"fc7-conv\"\r\n",
@@ -5573,9 +5572,9 @@
"> bottom: \"fc7\"\r\n",
"> top: \"fc8\"\r\n",
"> inner_product_param {\r\n",
- "208d204\r\n",
+ "213d206\r\n",
"< kernel_size: 1\r\n",
- "214c210\r\n",
+ "219c212\r\n",
"< bottom: \"fc8-conv\"\r\n",
"---\r\n",
"> bottom: \"fc8\"\r\n"
diff --git a/examples/net_surgery/bvlc_caffenet_full_conv.prototxt b/examples/net_surgery/bvlc_caffenet_full_conv.prototxt
index 0cadde9..f8f5c3c 100644
--- a/examples/net_surgery/bvlc_caffenet_full_conv.prototxt
+++ b/examples/net_surgery/bvlc_caffenet_full_conv.prototxt
@@ -1,11 +1,14 @@
# Fully convolutional network version of CaffeNet.
name: "CaffeNetConv"
-input: "data"
-input_shape {
- dim: 1
- dim: 3
- dim: 451
- dim: 451
+layer {
+ name: "data"
+ type: "Input"
+ top: "data"
+ input_param {
+ # initial shape for a fully convolutional network:
+ # the shape can be set for each input by reshape.
+ shape: { dim: 1 dim: 3 dim: 451 dim: 451 }
+ }
}
layer {
name: "conv1"
diff --git a/examples/net_surgery/conv.prototxt b/examples/net_surgery/conv.prototxt
index 6b3e5c7..8671bb5 100644
--- a/examples/net_surgery/conv.prototxt
+++ b/examples/net_surgery/conv.prototxt
@@ -1,11 +1,10 @@
# Simple single-layer network to showcase editing model parameters.
name: "convolution"
-input: "data"
-input_shape {
- dim: 1
- dim: 1
- dim: 100
- dim: 100
+layer {
+ name: "data"
+ type: "Input"
+ top: "data"
+ input_param { shape: { dim: 1 dim: 1 dim: 100 dim: 100 } }
}
layer {
name: "conv"
diff --git a/examples/siamese/mnist_siamese.prototxt b/examples/siamese/mnist_siamese.prototxt
index 332731b..5d783ba 100644
--- a/examples/siamese/mnist_siamese.prototxt
+++ b/examples/siamese/mnist_siamese.prototxt
@@ -1,10 +1,11 @@
name: "mnist_siamese"
-input: "data"
-input_shape {
- dim: 10000
- dim: 1
- dim: 28
- dim: 28
+layer {
+ name: "data"
+ type: "Input"
+ top: "data"
+ input_param {
+ shape: { dim: 10000 dim: 1 dim: 28 dim: 28 }
+ }
}
layer {
name: "conv1"
diff --git a/models/bvlc_alexnet/deploy.prototxt b/models/bvlc_alexnet/deploy.prototxt
index ff10daa..45b2b0e 100644
--- a/models/bvlc_alexnet/deploy.prototxt
+++ b/models/bvlc_alexnet/deploy.prototxt
@@ -1,10 +1,9 @@
name: "AlexNet"
-input: "data"
-input_shape {
- dim: 10
- dim: 3
- dim: 227
- dim: 227
+layer {
+ name: "data"
+ type: "Input"
+ top: "data"
+ input_param { shape: { dim: 10 dim: 3 dim: 227 dim: 227 } }
}
layer {
name: "conv1"
diff --git a/models/bvlc_googlenet/deploy.prototxt b/models/bvlc_googlenet/deploy.prototxt
index 1f90ee2..50b54a9 100644
--- a/models/bvlc_googlenet/deploy.prototxt
+++ b/models/bvlc_googlenet/deploy.prototxt
@@ -1,10 +1,9 @@
name: "GoogleNet"
-input: "data"
-input_shape {
- dim: 10
- dim: 3
- dim: 224
- dim: 224
+layer {
+ name: "data"
+ type: "Input"
+ top: "data"
+ input_param { shape: { dim: 10 dim: 3 dim: 224 dim: 224 } }
}
layer {
name: "conv1/7x7_s2"
diff --git a/models/bvlc_reference_caffenet/deploy.prototxt b/models/bvlc_reference_caffenet/deploy.prototxt
index 127f1e2..907116e 100644
--- a/models/bvlc_reference_caffenet/deploy.prototxt
+++ b/models/bvlc_reference_caffenet/deploy.prototxt
@@ -1,10 +1,9 @@
name: "CaffeNet"
-input: "data"
-input_shape {
- dim: 10
- dim: 3
- dim: 227
- dim: 227
+layer {
+ name: "data"
+ type: "Input"
+ top: "data"
+ input_param { shape: { dim: 10 dim: 3 dim: 227 dim: 227 } }
}
layer {
name: "conv1"
diff --git a/models/bvlc_reference_rcnn_ilsvrc13/deploy.prototxt b/models/bvlc_reference_rcnn_ilsvrc13/deploy.prototxt
index ae1df96..e330a77 100644
--- a/models/bvlc_reference_rcnn_ilsvrc13/deploy.prototxt
+++ b/models/bvlc_reference_rcnn_ilsvrc13/deploy.prototxt
@@ -1,10 +1,9 @@
name: "R-CNN-ilsvrc13"
-input: "data"
-input_shape {
- dim: 10
- dim: 3
- dim: 227
- dim: 227
+layer {
+ name: "data"
+ type: "Input"
+ top: "data"
+ input_param { shape: { dim: 10 dim: 3 dim: 227 dim: 227 } }
}
layer {
name: "conv1"
diff --git a/models/finetune_flickr_style/deploy.prototxt b/models/finetune_flickr_style/deploy.prototxt
index 0f07e47..b8f99c7 100644
--- a/models/finetune_flickr_style/deploy.prototxt
+++ b/models/finetune_flickr_style/deploy.prototxt
@@ -1,10 +1,9 @@
name: "FlickrStyleCaffeNet"
-input: "data"
-input_shape {
- dim: 10
- dim: 3
- dim: 227
- dim: 227
+layer {
+ name: "data"
+ type: "Input"
+ top: "data"
+ input_param { shape: { dim: 10 dim: 3 dim: 227 dim: 227 } }
}
layer {
name: "conv1"