ReshapeLayer fixups for ND blobs

1 files changed, 15 insertions, 18 deletions

diff --git a/docs/tutorial/layers.md b/docs/tutorial/layers.md
index 422ee01f..c4529e6a 100644
--- a/docs/tutorial/layers.md
+++ b/docs/tutorial/layers.md
@@ -421,15 +421,11 @@ The `FLATTEN` layer is a utility layer that flattens an input of shape `n * c *
 
 #### Reshape
 
-* LayerType: `RESHAPE`
-* CPU implementation: `./src/caffe/layers/reshape_layer.cpp`
-* CUDA GPU implementation: `./src/caffe/layers/reshape_layer.cu`
+* Layer type: `Reshape`
+* Implementation: `./src/caffe/layers/reshape_layer.cpp`
 * Parameters (`ReshapeParameter reshape_param`)
     - Optional: (also see detailed description below)
-        - `num` [default 0]
-        - `channels` [default 0]
-        - `width` [default 0]
-        - `height` [default 0]
+        - `shape`
 
 * Input
     - a single blob with arbitrary dimensions
@@ -438,28 +434,29 @@ The `FLATTEN` layer is a utility layer that flattens an input of shape `n * c *
 
 * Sample
 
-        layers {
+        layer {
           name: "reshape"
-          type: RESHAPE
+          type: "Reshape"
           bottom: "input"
           top: "output"
-
           reshape_param {
-            num: 0  # copy the dimension from below
-            channels: 2
-            width: 3
-            height: -1 # infer it from the other dimensions
+            shape {
+              dim: 0  # copy the dimension from below
+              dim: 2
+              dim: 3
+              dim: -1 # infer it from the other dimensions
+            }
           }
         }
 
-The `RESHAPE` layer can be used to change the dimensions of its input, without changing its data. Just like the `FLATTEN` layer, only the dimensions are changed, no data is copied in the process.
+The `Reshape` layer can be used to change the dimensions of its input, without changing its data. Just like the `Flatten` layer, only the dimensions are changed; no data is copied in the process.
 
 Output dimensions are specified by the `ReshapeParam` proto. Positive numbers are used directly, setting the corresponding dimension of the output blob. In addition, two special values are accepted for any of the target dimension values:
 
-* **0** means "copy the respective dimension of the bottom layer". That is, if the bottom layer has 2 channels, the top one will have 2 channels too, given `channels: 0` as target dimension. Since the default value of all the target dimensions is 0, omitting any of the target dimensions will also cause it to be copied.
-* **-1** stands for "infer this from the other dimensions". This behavior is similar to that of -1 in *numpy*'s or `[]` for *MATLAB*'s reshape: this dimension is calculated to keep the overall element count the same as in the bottom layer. If this is not possible, an error is raised. Also, at most one -1 can be used in a reshape operation.
+* **0** means "copy the respective dimension of the bottom layer". That is, if the bottom has 2 as its 1st dimension, the top will have 2 as its 1st dimension as well, given `dim: 0` as the 1st target dimension.
+* **-1** stands for "infer this from the other dimensions". This behavior is similar to that of -1 in *numpy*'s or `[]` for *MATLAB*'s reshape: this dimension is calculated to keep the overall element count the same as in the bottom layer. At most one -1 can be used in a reshape operation.
 
-As another example, giving `num: 0, channels: -1, height: 1, width: 1` as parameters makes the layer behave in exactly the same way as the `FLATTEN` layer.
+As another example, specifying `reshape_param { shape { dim: 0 dim: -1 } }` makes the layer behave in exactly the same way as the `Flatten` layer.
 
 #### Concatenation