projects / platform / upstream / caffe.git / commitdiff
? search:
summary | shortlog | log | commit | commitdiff | tree
raw | patch | inline | side by side (parent: 2e6a82c)
restore test_upgrade_proto to dev version
authorJeff Donahue <jeff.donahue@gmail.com>
Thu, 15 Jan 2015 02:31:23 +0000 (18:31 -0800)
committerJeff Donahue <jeff.donahue@gmail.com>
Thu, 5 Feb 2015 22:49:22 +0000 (14:49 -0800)
src/caffe/test/test_upgrade_proto.cpp patch | blob | history

diff --git a/src/caffe/test/test_upgrade_proto.cpp b/src/caffe/test/test_upgrade_proto.cpp
index e520b85..52e7f1f 100644 (file)
--- a/src/caffe/test/test_upgrade_proto.cpp
+++ b/src/caffe/test/test_upgrade_proto.cpp
@@ -1184,7 +1184,7 @@ TEST_F(V0UpgradeTest, TestSimple) {
       "name: 'CaffeNet' "
       "layers { "
       "  name: 'data' "
-      "  type: 'Data' "
+      "  type: DATA "
       "  data_param { "
       "    source: '/home/jiayq/Data/ILSVRC12/train-leveldb' "
       "    batch_size: 256 "
@@ -1199,7 +1199,7 @@ TEST_F(V0UpgradeTest, TestSimple) {
       "} "
       "layers { "
       "  name: 'conv1' "
-      "  type: 'Convolution' "
+      "  type: CONVOLUTION "
       "  convolution_param { "
       "    num_output: 96 "
       "    kernel_size: 11 "
@@ -1223,7 +1223,7 @@ TEST_F(V0UpgradeTest, TestSimple) {
       "} "
       "layers { "
       "  name: 'fc8' "
-      "  type: 'InnerProduct' "
+      "  type: INNER_PRODUCT "
       "  inner_product_param { "
       "    num_output: 1000 "
       "    weight_filler { "
@@ -1244,7 +1244,7 @@ TEST_F(V0UpgradeTest, TestSimple) {
       "} "
       "layers { "
       "  name: 'loss' "
-      "  type: 'SoftmaxWithLoss' "
+      "  type: SOFTMAX_LOSS "
       "  bottom: 'fc8' "
       "  bottom: 'label' "
       "} ";
@@ -1520,7 +1520,7 @@ TEST_F(V0UpgradeTest, TestAllParams) {
       "input_dim: 32 "
       "layers { "
       "  name: 'data' "
-      "  type: 'Data' "
+      "  type: DATA "
       "  data_param { "
       "    source: '/home/jiayq/Data/ILSVRC12/train-leveldb' "
       "    batch_size: 256 "
@@ -1537,7 +1537,7 @@ TEST_F(V0UpgradeTest, TestAllParams) {
       "} "
       "layers { "
       "  name: 'images' "
-      "  type: 'ImageData' "
+      "  type: IMAGE_DATA "
       "  image_data_param { "
       "    source: '/home/jiayq/Data/ILSVRC12/train-images' "
       "    batch_size: 256 "
@@ -1557,7 +1557,7 @@ TEST_F(V0UpgradeTest, TestAllParams) {
       "} "
       "layers { "
       "  name: 'window_data' "
-      "  type: 'WindowData' "
+      "  type: WINDOW_DATA "
       "  window_data_param { "
       "    source: '/home/jiayq/Data/ILSVRC12/train-leveldb' "
       "    batch_size: 256 "
@@ -1577,7 +1577,7 @@ TEST_F(V0UpgradeTest, TestAllParams) {
       "} "
       "layers { "
       "  name: 'hdf5data' "
-      "  type: 'HDF5Data' "
+      "  type: HDF5_DATA "
       "  hdf5_data_param { "
       "    source: '/my/hdf5/data' "
       "    batch_size: 256 "
@@ -1586,7 +1586,7 @@ TEST_F(V0UpgradeTest, TestAllParams) {
       "} "
       "layers { "
       "  name: 'conv1' "
-      "  type: 'Convolution' "
+      "  type: CONVOLUTION "
       "  convolution_param { "
       "    num_output: 96 "
       "    bias_term: false "
@@ -1611,7 +1611,7 @@ TEST_F(V0UpgradeTest, TestAllParams) {
       "} "
       "layers { "
       "  name: 'pool1ave' "
-      "  type: 'Pooling' "
+      "  type: POOLING "
       "  pooling_param { "
       "    pool: AVE "
       "    kernel_size: 3 "
@@ -1622,7 +1622,7 @@ TEST_F(V0UpgradeTest, TestAllParams) {
       "} "
       "layers { "
       "  name: 'pool1stoch' "
-      "  type: 'Pooling' "
+      "  type: POOLING "
       "  pooling_param { "
       "    pool: STOCHASTIC "
       "    kernel_size: 4 "
@@ -1633,7 +1633,7 @@ TEST_F(V0UpgradeTest, TestAllParams) {
       "} "
       "layers { "
       "  name: 'concat' "
-      "  type: 'Concat' "
+      "  type: CONCAT "
       "  concat_param { "
       "    concat_dim: 2 "
       "  } "
@@ -1643,7 +1643,7 @@ TEST_F(V0UpgradeTest, TestAllParams) {
       "} "
       "layers { "
       "  name: 'norm1' "
-      "  type: 'LRN' "
+      "  type: LRN "
       "  lrn_param { "
       "    local_size: 5 "
       "    alpha: 0.0001 "
@@ -1654,7 +1654,7 @@ TEST_F(V0UpgradeTest, TestAllParams) {
       "} "
       "layers { "
       "  name: 'fc6' "
-      "  type: 'InnerProduct' "
+      "  type: INNER_PRODUCT "
       "  inner_product_param { "
       "    num_output: 4096 "
       "    bias_term: false "
@@ -1676,13 +1676,13 @@ TEST_F(V0UpgradeTest, TestAllParams) {
       "} "
       "layers { "
       "  name: 'relu6' "
-      "  type: 'ReLU' "
+      "  type: RELU "
       "  bottom: 'fc6' "
       "  top: 'fc6' "
       "} "
       "layers { "
       "  name: 'drop6' "
-      "  type: 'Dropout' "
+      "  type: DROPOUT "
       "  dropout_param { "
       "    dropout_ratio: 0.2 "
       "  } "
@@ -1691,7 +1691,7 @@ TEST_F(V0UpgradeTest, TestAllParams) {
       "} "
       "layers { "
       "  name: 'loss' "
-      "  type: 'InfogainLoss' "
+      "  type: INFOGAIN_LOSS "
       "  infogain_loss_param { "
       "    source: '/my/infogain/matrix' "
       "  } "
@@ -1700,54 +1700,54 @@ TEST_F(V0UpgradeTest, TestAllParams) {
       "} "
       "layers { "
       "  name: 'accuracy' "
-      "  type: 'Accuracy' "
+      "  type: ACCURACY "
       "} "
       "layers { "
       "  name: 'bnll' "
-      "  type: 'BNLL' "
+      "  type: BNLL "
       "} "
       "layers { "
       "  name: 'euclidean_loss' "
-      "  type: 'EuclideanLoss' "
+      "  type: EUCLIDEAN_LOSS "
       "} "
       "layers { "
       "  name: 'flatten' "
-      "  type: 'Flatten' "
+      "  type: FLATTEN "
       "} "
       "layers { "
       "  name: 'hdf5_output' "
-      "  type: 'HDF5Output' "
+      "  type: HDF5_OUTPUT "
       "  hdf5_output_param { "
       "    file_name: '/my/hdf5/output/file' "
       "  } "
       "} "
       "layers { "
       "  name: 'im2col' "
-      "  type: 'Im2Col' "
+      "  type: IM2COL "
       "} "
       "layers { "
       "  name: 'images' "
-      "  type: 'ImageData' "
+      "  type: IMAGE_DATA "
       "} "
       "layers { "
       "  name: 'multinomial_logistic_loss' "
-      "  type: 'MultinomialLogisticLoss' "
+      "  type: MULTINOMIAL_LOGISTIC_LOSS "
       "} "
       "layers { "
       "  name: 'sigmoid' "
-      "  type: 'Sigmoid' "
+      "  type: SIGMOID "
       "} "
       "layers { "
       "  name: 'softmax' "
-      "  type: 'Softmax' "
+      "  type: SOFTMAX "
       "} "
       "layers { "
       "  name: 'split' "
-      "  type: 'Split' "
+      "  type: SPLIT "
       "} "
       "layers { "
       "  name: 'tanh' "
-      "  type: 'TanH' "
+      "  type: TANH "
       "} ";
   this->RunV0UpgradeTest(input_proto, expected_output_proto);
 }
@@ -2122,7 +2122,7 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "name: 'CaffeNet' "
       "layers { "
       "  name: 'data' "
-      "  type: 'Data' "
+      "  type: DATA "
       "  data_param { "
       "    source: '/home/jiayq/Data/ILSVRC12/train-leveldb' "
       "    batch_size: 256 "
@@ -2137,7 +2137,7 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'conv1' "
-      "  type: 'Convolution' "
+      "  type: CONVOLUTION "
       "  convolution_param { "
       "    num_output: 96 "
       "    kernel_size: 11 "
@@ -2160,13 +2160,13 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'relu1' "
-      "  type: 'ReLU' "
+      "  type: RELU "
       "  bottom: 'conv1' "
       "  top: 'conv1' "
       "} "
       "layers { "
       "  name: 'pool1' "
-      "  type: 'Pooling' "
+      "  type: POOLING "
       "  pooling_param { "
       "    pool: MAX "
       "    kernel_size: 3 "
@@ -2177,7 +2177,7 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'norm1' "
-      "  type: 'LRN' "
+      "  type: LRN "
       "  lrn_param { "
       "    local_size: 5 "
       "    alpha: 0.0001 "
@@ -2188,7 +2188,7 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'conv2' "
-      "  type: 'Convolution' "
+      "  type: CONVOLUTION "
       "  convolution_param { "
       "    num_output: 256 "
       "    group: 2 "
@@ -2212,13 +2212,13 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'relu2' "
-      "  type: 'ReLU' "
+      "  type: RELU "
       "  bottom: 'conv2' "
       "  top: 'conv2' "
       "} "
       "layers { "
       "  name: 'pool2' "
-      "  type: 'Pooling' "
+      "  type: POOLING "
       "  pooling_param { "
       "    pool: MAX "
       "    kernel_size: 3 "
@@ -2229,7 +2229,7 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'norm2' "
-      "  type: 'LRN' "
+      "  type: LRN "
       "  lrn_param { "
       "    local_size: 5 "
       "    alpha: 0.0001 "
@@ -2240,7 +2240,7 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'conv3' "
-      "  type: 'Convolution' "
+      "  type: CONVOLUTION "
       "  convolution_param { "
       "    num_output: 384 "
       "    kernel_size: 3 "
@@ -2263,13 +2263,13 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'relu3' "
-      "  type: 'ReLU' "
+      "  type: RELU "
       "  bottom: 'conv3' "
       "  top: 'conv3' "
       "} "
       "layers { "
       "  name: 'conv4' "
-      "  type: 'Convolution' "
+      "  type: CONVOLUTION "
       "  convolution_param { "
       "    num_output: 384 "
       "    group: 2 "
@@ -2293,13 +2293,13 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'relu4' "
-      "  type: 'ReLU' "
+      "  type: RELU "
       "  bottom: 'conv4' "
       "  top: 'conv4' "
       "} "
       "layers { "
       "  name: 'conv5' "
-      "  type: 'Convolution' "
+      "  type: CONVOLUTION "
       "  convolution_param { "
       "    num_output: 256 "
       "    group: 2 "
@@ -2323,13 +2323,13 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'relu5' "
-      "  type: 'ReLU' "
+      "  type: RELU "
       "  bottom: 'conv5' "
       "  top: 'conv5' "
       "} "
       "layers { "
       "  name: 'pool5' "
-      "  type: 'Pooling' "
+      "  type: POOLING "
       "  pooling_param { "
       "    kernel_size: 3 "
       "    pool: MAX "
@@ -2340,7 +2340,7 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'fc6' "
-      "  type: 'InnerProduct' "
+      "  type: INNER_PRODUCT "
       "  inner_product_param { "
       "    num_output: 4096 "
       "    weight_filler { "
@@ -2361,13 +2361,13 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'relu6' "
-      "  type: 'ReLU' "
+      "  type: RELU "
       "  bottom: 'fc6' "
       "  top: 'fc6' "
       "} "
       "layers { "
       "  name: 'drop6' "
-      "  type: 'Dropout' "
+      "  type: DROPOUT "
       "  dropout_param { "
       "    dropout_ratio: 0.5 "
       "  } "
@@ -2376,7 +2376,7 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'fc7' "
-      "  type: 'InnerProduct' "
+      "  type: INNER_PRODUCT "
       "  inner_product_param { "
       "    num_output: 4096 "
       "    weight_filler { "
@@ -2397,13 +2397,13 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'relu7' "
-      "  type: 'ReLU' "
+      "  type: RELU "
       "  bottom: 'fc7' "
       "  top: 'fc7' "
       "} "
       "layers { "
       "  name: 'drop7' "
-      "  type: 'Dropout' "
+      "  type: DROPOUT "
       "  dropout_param { "
       "    dropout_ratio: 0.5 "
       "  } "
@@ -2412,7 +2412,7 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'fc8' "
-      "  type: 'InnerProduct' "
+      "  type: INNER_PRODUCT "
       "  inner_product_param { "
       "    num_output: 1000 "
       "    weight_filler { "
@@ -2433,7 +2433,7 @@ TEST_F(V0UpgradeTest, TestImageNet) {
       "} "
       "layers { "
       "  name: 'loss' "
-      "  type: 'SoftmaxWithLoss' "
+      "  type: SOFTMAX_LOSS "
       "  bottom: 'fc8' "
       "  bottom: 'label' "
       "} ";
Domain: Machine Learning / ML Framework;