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From kaip...@apache.org
Subject svn commit: r1708286 - in /incubator/singa/site/trunk/content/markdown/docs: cnn.md mlp.md
Date Tue, 13 Oct 2015 05:12:53 GMT
Author: kaiping
Date: Tue Oct 13 05:12:53 2015
New Revision: 1708286

URL: http://svn.apache.org/viewvc?rev=1708286&view=rev
Log:
Modify input layer configuration info for MLP and CNN

Modified:
    incubator/singa/site/trunk/content/markdown/docs/cnn.md
    incubator/singa/site/trunk/content/markdown/docs/mlp.md

Modified: incubator/singa/site/trunk/content/markdown/docs/cnn.md
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/content/markdown/docs/cnn.md?rev=1708286&r1=1708285&r2=1708286&view=diff
==============================================================================
--- incubator/singa/site/trunk/content/markdown/docs/cnn.md (original)
+++ incubator/singa/site/trunk/content/markdown/docs/cnn.md Tue Oct 13 05:12:53 2015
@@ -82,38 +82,34 @@ the training/testing `Records` from `Dat
 
         layer{
           name: "data"
-          type: kShardData
-          sharddata_conf {
-            path: "examples/cifar10/cifar10_train_shard"
-            batchsize: 16
+          type: kRecordInput
+          store_conf {
+            backend: "kvfile"
+            path: "examples/cifar10/train_data.bin"
+            mean_file: "examples/cifar10/image_mean.bin"
+            batchsize: 64
             random_skip: 5000
-          }
-          exclude: kTest  # exclude this layer for the testing net
+            shape: 3
+            shape: 32
+            shape: 32
+           }
+           exclude: kTest  # exclude this layer for the testing net
         }
         layer{
           name: "data"
-          type: kShardData
-          sharddata_conf {
-            path: "examples/cifar10/cifar10_test_shard"
+          type: kRecordInput
+          store_conf {
+            backend: "kvfile"
+            path: "examples/cifar10/test_data.bin"
+            mean_file: "examples/cifar10/image_mean.bin"
             batchsize: 100
-          }
-          exclude: kTrain # exclude this layer for the training net
+            shape: 3
+            shape: 32
+            shape: 32
+           }
+         exclude: kTrain # exclude this layer for the training net
         }
 
-* We configure two [parser layers](layer.html#parser-layers)
-to extract the image feature and label from `Records`s loaded by the *data* layer.
-
-        layer{
-          name:"rgb"
-          type: kRGBImage
-          srclayers: "data"
-          rgbimage_conf {...}
-        }
-        layer{
-          name: "label"
-          type: kLabel
-          srclayers: "data"
-        }
 
 * We configure layers for the feature transformation as follows
 (all layers are built-in layers in SINGA; hyper-parameters of these layers are set according
to
@@ -122,7 +118,7 @@ to extract the image feature and label f
         layer {
           name: "conv1"
           type: kConvolution
-          srclayers: "rgb"
+          srclayers: "data"
           convolution_conf {... }
           ...
         }
@@ -176,7 +172,7 @@ matrix Param is configured with a large
           type: kSoftmaxLoss
           softmaxloss_conf{ topk:1 }
           srclayers:"ip1"
-          srclayers: "label"
+          srclayers: "data"
         }
 
 ### Updater

Modified: incubator/singa/site/trunk/content/markdown/docs/mlp.md
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/content/markdown/docs/mlp.md?rev=1708286&r1=1708285&r2=1708286&view=diff
==============================================================================
--- incubator/singa/site/trunk/content/markdown/docs/mlp.md (original)
+++ incubator/singa/site/trunk/content/markdown/docs/mlp.md Tue Oct 13 05:12:53 2015
@@ -89,51 +89,40 @@ the training/testing `Records` from `Dat
 
         layer {
             name: "data"
-            type: kShardData
-            sharddata_conf {
-              path: "examples/mnist/mnist_train_shard"
-              batchsize: 1000
-            }
-            exclude: kTest
+            type: kRecordInput
+            store_conf {
+              backend: "kvfile"
+              path: "examples/mnist/train_data.bin"
+              random_skip: 5000
+              batchsize: 64
+              shape: 784
+              std_value: 127.5
+              mean_value: 127.5
+             }
+             exclude: kTest
           }
 
         layer {
             name: "data"
-            type: kShardData
-            sharddata_conf {
-              path: "examples/mnist/mnist_test_shard"
-              batchsize: 1000
-            }
-            exclude: kTrain
-          }
-
-* We configure two [parser layers](layer.html#parser-layers)
-to extract the image feature and label from `Records`s loaded by the *data* layer.
-The [MnistLayer](layer.html#mnistlayer) will normalize the pixel
-values into [-1,1].
-
-        layer{
-            name:"mnist"
-            type: kMnist
-            srclayers: "data"
-            mnist_conf {
-              norm_a: 127.5
-              norm_b: 1
-            }
-          }
-
-        layer{
-            name: "label"
-            type: kLabel
-            srclayers: "data"
+            type: kRecordInput
+            store_conf {
+              backend: "kvfile"
+              path: "examples/mnist/test_data.bin"
+              batchsize: 100
+              shape: 784
+              std_value: 127.5
+              mean_value: 127.5
+             }
+             exclude: kTrain
           }
+          
 
 * All [InnerProductLayer](layer.html#innerproductlayer)s are configured similarly as,
 
         layer{
           name: "fc1"
           type: kInnerProduct
-          srclayers:"mnist"
+          srclayers:"data"
           innerproduct_conf{
             num_output: 2500
           }
@@ -166,7 +155,7 @@ to LabelLayer and the last STanhLayer.
           type:kSoftmaxLoss
           softmaxloss_conf{ topk:1 }
           srclayers:"fc6"
-          srclayers:"label"
+          srclayers:"data"
         }
 
 ### Updater



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