public override void Forward(SuperArray x)
{
base.Forward(x);
var(n, c, d, h, w) = x.GetConv3DShape();
int pad = 0;
if (Padding == PaddingType.Same)
{
pad = 1;
}
else if (Padding == PaddingType.Full)
{
pad = 2;
}
var d_out = (d - PoolSize.Item1) / Strides + 1;
var h_out = (h - PoolSize.Item2) / Strides + 1;
var w_out = (w - PoolSize.Item3) / Strides + 1;
var x_reshaped = x.Reshape(n * c, 1, d, h, w);
//xCols = ImUtil.Im2Col(x_reshaped, PoolSize, pad, Strides);
Output = Ops.ArgMax(xCols);
Output = Output.Reshape(d_out, h_out, w_out, n, c).Transpose(2, 3, 4, 0, 1);
}
/// <summary>
/// Calculates the metric with predicted and true values.
/// </summary>
/// <param name="preds">The predicted value.</param>
/// <param name="labels">The true value.</param>
/// <returns></returns>
public override SuperArray Calc(SuperArray preds, SuperArray labels)
{
preds = Ops.ArgMax(preds);
labels = Ops.ArgMax(labels);
var r = Ops.EqualTo(preds, labels);
return(r);
}
public override void Forward(SuperArray x)
{
base.Forward(x);
var(n, c, s) = x.GetConv1DShape();
int pad = 0;
if (Padding == PaddingType.Same)
{
pad = 1;
}
else if (Padding == PaddingType.Full)
{
pad = 2;
}
var s_out = (s - PoolSize) / Strides + 1;
var x_reshaped = x.Reshape(n * c, 1, s);
xCols = ImUtil.Im2Col(x_reshaped, Tuple.Create(PoolSize, PoolSize), pad, Strides);
Output = Ops.ArgMax(xCols);
Output = Output.Reshape(s_out, n, c).Transpose(2, 0, 1);
}
public void Argmax()
{
variable = Ops.ArgMax(variable);
}
