- Layer type: Reshape
- 头文件位置：./include/caffe/layers/reshape_layer.hpp
- CPU 执行源文件位置: ./src/caffe/layers/reshape_layer.cpp
- Reshape层的功能：根据给定参数改变输入blob的维度，仅仅改变数据的维度，但内容不变。
参数解读
layer {
name: "reshape"
type: "Reshape"
bottom: "input"
top: "output"
reshape_param {
shape {
dim: 0 # copy the dimension from below
dim: 2
dim: 3
dim: -1 # infer it from the other dimensions
}
}
}如上图中的dim，具体还以如下：
#有一个可选的参数组shape, 用于指定blob数据的各维的值（blob是一个四维的数据：n*c*w*h）。
#dim:0 表示维度不变，即输入和输出是相同的维度。
#dim:2 或 dim:3 将原来的维度变成2或3
#dim:-1 表示由系统自动计算维度。数据的总量不变，系统会根据blob数据的其它三维来自动计算当前维的维度值 。
#假设原数据为：32*3*28*28， 表示32张3通道的28*28的彩色图片
# shape {
# dim: 0 32-32
# dim: 0 3-3
# dim: 14 28-14
# dim: -1 #让其推断出此数值
# }
#输出数据为：32*3*14*56 参数定义
参数(ReshapeParameter reshape_param)
定义位置 ./src/caffe/proto/caffe.proto:
可选参数组：shape
message ReshapeParameter {
// Specify the output dimensions. If some of the dimensions are set to 0,
// the corresponding dimension from the bottom layer is used (unchanged).
// Exactly one dimension may be set to -1, in which case its value is
// inferred from the count of the bottom blob and the remaining dimensions.
// For example, suppose we want to reshape a 2D blob "input" with shape 2 x 8:
//
// layer {
// type: "Reshape" bottom: "input" top: "output"
// reshape_param { ... }
// }
//
// If "input" is 2D with shape 2 x 8, then the following reshape_param
// specifications are all equivalent, producing a 3D blob "output" with shape
// 2 x 2 x 4:
//
// reshape_param { shape { dim: 2 dim: 2 dim: 4 } }
// reshape_param { shape { dim: 0 dim: 2 dim: 4 } }
// reshape_param { shape { dim: 0 dim: 2 dim: -1 } }
// reshape_param { shape { dim: 0 dim:-1 dim: 4 } }
//
optional BlobShape shape = 1;
// axis and num_axes control the portion of the bottom blob's shape that are
// replaced by (included in) the reshape. By default (axis == 0 and
// num_axes == -1), the entire bottom blob shape is included in the reshape,
// and hence the shape field must specify the entire output shape.
//
// axis may be non-zero to retain some portion of the beginning of the input
// shape (and may be negative to index from the end; e.g., -1 to begin the
// reshape after the last axis, including nothing in the reshape,
// -2 to include only the last axis, etc.).
//
// For example, suppose "input" is a 2D blob with shape 2 x 8.
// Then the following ReshapeLayer specifications are all equivalent,
// producing a blob "output" with shape 2 x 2 x 4:
//
// reshape_param { shape { dim: 2 dim: 2 dim: 4 } }
// reshape_param { shape { dim: 2 dim: 4 } axis: 1 }
// reshape_param { shape { dim: 2 dim: 4 } axis: -3 }
//
// num_axes specifies the extent of the reshape.
// If num_axes >= 0 (and axis >= 0), the reshape will be performed only on
// input axes in the range [axis, axis+num_axes].
// num_axes may also be -1, the default, to include all remaining axes
// (starting from axis).
//
// For example, suppose "input" is a 2D blob with shape 2 x 8.
// Then the following ReshapeLayer specifications are equivalent,
// producing a blob "output" with shape 1 x 2 x 8.
//
// reshape_param { shape { dim: 1 dim: 2 dim: 8 } }
// reshape_param { shape { dim: 1 dim: 2 } num_axes: 1 }
// reshape_param { shape { dim: 1 } num_axes: 0 }
//
// On the other hand, these would produce output blob shape 2 x 1 x 8:
//
// reshape_param { shape { dim: 2 dim: 1 dim: 8 } }
// reshape_param { shape { dim: 1 } axis: 1 num_axes: 0 }
//
optional int32 axis = 2 [default = 0];
optional int32 num_axes = 3 [default = -1];
}番外篇
Reshape layer只改变输入数据的维度，但内容不变，也没有数据复制的过程，与Flatten layer类似。
输出维度由reshape_param 指定，正整数直接指定维度大小，下面两个特殊的值：
0 => 表示copy the respective dimension of the bottom layer，复制输入相应维度的值。
-1 => 表示infer this from the other dimensions，根据其他维度自动推测维度大小。reshape_param中至多只能有一个-1。
再举一个例子：如果指定reshape_param参数为：{ shape { dim: 0 dim: -1 } } ，那么输出和Flattening layer的输出是完全一样的。
Flatten层的操作详见：【caffe】Layer解读之：Flatten