diff --git a/examples/cifar10/cifar10_full.prototxt b/examples/cifar10/cifar10_full.prototxt index 446479da961..83cf0d86b35 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 9352fbf65df..cf3b2a358be 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 974662e59da..6b67c537a47 100644 --- a/examples/cpp_classification/classification.cpp +++ b/examples/cpp_classification/classification.cpp @@ -159,7 +159,7 @@ std::vector Classifier::Predict(const cv::Mat& img) { Preprocess(img, &input_channels); - net_->ForwardPrefilled(); + net_->Forward(); /* Copy the output layer to a std::vector */ Blob* output_layer = net_->output_blobs()[0]; diff --git a/examples/mnist/lenet.prototxt b/examples/mnist/lenet.prototxt index dff7123bf73..8cf78e62c89 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 ff780fbb9f7..a6092db0c40 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 0cadde9b58b..f8f5c3c325a 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 6b3e5c768d5..8671bb5bf0a 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 332731bd75f..5d783ba02ca 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 ff10daa9399..45b2b0e361a 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 1f90ee21630..50b54a9f3c1 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 127f1e265fd..907116ef91c 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 ae1df967742..e330a770676 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 0f07e47acab..b8f99c74453 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"