/// <summary>
/// 全結合
/// </summary>
/// <param name="input"></param>
/// <param name="outputDim"></param>
/// <param name="withBias"></param>
/// <param name="device"></param>
/// <returns></returns>
public static Function Dense(this Function function, int outputDim, bool withBias = true, string name = "")
{
Variable input = (Variable)function;
if (input.Shape.Rank != 1)
{
// 一次元でないとき、一次元に並び替える
int newDim = input.Shape.Dimensions.Aggregate((d1, d2) => d1 * d2);
input = CNTKLib.Reshape(input, new int[] { newDim });
}
var weightParam = new CNTK.Parameter(
new int[] { outputDim, input.Shape.TotalSize },
CNTK.DataType.Float,
CNTK.CNTKLib.GlorotUniformInitializer(
CNTK.CNTKLib.DefaultParamInitScale,
CNTK.CNTKLib.SentinelValueForInferParamInitRank,
CNTK.CNTKLib.SentinelValueForInferParamInitRank,
1),
//CNTK.CNTKLib.XavierInitializer(),
_device,
name + "_w"
);
// input * weightParam + biasParam
if (withBias == true)
{
var biasParam = new Parameter(new int[] { outputDim }, DataType.Float, 0, _device, name + "_b");
return(CNTKLib.Plus(CNTKLib.Times(weightParam, input, name + "_times"), biasParam, name));
}
else
{
return(CNTKLib.Times(weightParam, input, name));
}
}
C.Function create_capsule_layer(C.Function inputs, int num_capsule, int dim_capsule, int routings, string name)
{
var inputs_shape = inputs.Output.Shape.Dimensions;
var input_num_capsule = inputs_shape[0];
var input_dim_capsule = inputs_shape[1];
var W = new C.Parameter(
new int[] { num_capsule, dim_capsule, input_num_capsule, input_dim_capsule },
C.DataType.Float,
CC.GlorotUniformInitializer(),
computeDevice,
name: "W");
inputs = CC.Reshape(inputs, new int[] { 1, 1, input_num_capsule, input_dim_capsule }); // [1, 1, 1152, 8])
var inputs_hat = CC.ElementTimes(W, inputs);
inputs_hat = CC.ReduceSum(inputs_hat, new C.Axis(3));
inputs_hat = CC.Squeeze(inputs_hat);
C.Function outputs = null;
var zeros = new C.Constant(new int[] { num_capsule, 1, input_num_capsule }, C.DataType.Float, 0, computeDevice);
var b = CC.Combine(new C.VariableVector()
{
zeros
});
for (int i = 0; i < routings; i++)
{
var c = CC.Softmax(b, new C.Axis(0));
var batch_dot_result = CC.ElementTimes(c, inputs_hat);
batch_dot_result = CC.ReduceSum(batch_dot_result, new C.Axis(2));
batch_dot_result = CC.Squeeze(batch_dot_result);
outputs = squash(batch_dot_result, name: $"squashed_{i}", axis: 1);
if (i < (routings - 1))
{
outputs = CC.Reshape(outputs, new int[] { num_capsule, dim_capsule, 1 });
batch_dot_result = CC.ElementTimes(outputs, inputs_hat);
batch_dot_result = CC.ReduceSum(batch_dot_result, new C.Axis(1));
b = CC.Plus(b, batch_dot_result);
}
}
outputs = CC.Combine(new C.VariableVector()
{
outputs
}, name);
return(outputs);
}
internal Parameter(CNTK.Parameter constant) : base(constant)
{
UnderlyingParameter = constant;
}
