public static KerasSymbol Selu(KerasSymbol x)
{
var alpha = 1.6732632423543772f;
var scale = 1.0507009873554805f;
return(scale * K.Elu(x, alpha));
}
public static KerasSymbol Logcosh(KerasSymbol y_true, KerasSymbol y_pred)
{
var x = y_pred - y_true;
var _logcosh = x + K.Softplus(-2 * x) - (float)Math.Log(2);
return(K.Mean(_logcosh, axis: -1));
}
public static KerasSymbol CategorialHinge(KerasSymbol y_true, KerasSymbol y_pred)
{
var pos = K.Sum(y_true * y_pred, axis: -1);
var neg = K.Max((1 - y_true) * y_pred, axis: -1);
return(K.Maximum(0, neg - pos + 1));
}
public static KerasSymbol MeanSquaredLogrithmicError(KerasSymbol y_true, KerasSymbol y_pred)
{
var first_log = K.Log(K.Clip(y_pred, K.Epsilon(), null) + 1);
var second_log = K.Log(K.Clip(y_true, K.Epsilon(), null) + 1);
return(K.Mean(K.Square(first_log - second_log), axis: -1));
}
public static KerasSymbol operator %(KerasSymbol lhs, KerasSymbol rhs)
{
KerasSymbol ret = null;
using (var op = new Operator("_mod"))
{
ret = op.Set(lhs, rhs).CreateSymbol("mod");
}
return(ret);
}
public static KerasSymbol operator %(KerasSymbol lhs, float scalar)
{
KerasSymbol ret = null;
using (var op = new Operator("_mod_scalar"))
{
ret = op.Set(lhs, scalar).CreateSymbol("mod");
}
return(ret);
}
public static KerasSymbol Softmax(KerasSymbol x, int axis = -1)
{
var ndim = K.NDim(x);
if (ndim == 2)
{
return(K.Softmax(x));
}
else if (ndim > 2)
{
var e = K.Exp(x - K.Max(x, axis: axis, keepdims: true));
var s = K.Sum(e, axis: axis, keepdims: true);
return(e / s);
}
else if (ndim == 0)
{
// x dim is not inferred yet
return(K.Softmax(x));
}
else
{
throw new Exception($"Cannot apply softmax to a tensor that is 1D. Received input: {x}");
}
}
public static KerasSymbol OnesLike(KerasSymbol x, DType dtype = null, string name = "")
{
throw new NotImplementedException();
}
public static KerasSymbol Softplus(KerasSymbol x)
{
return(K.Softplus(x));
}
public static KerasSymbol Cast(KerasSymbol x, DType dtype)
{
throw new NotImplementedException();
}
public static KerasSymbol Elu(KerasSymbol x, float alpha = 1)
{
return(K.Elu(x, alpha));
}
public static KerasSymbol HardSigmoid(KerasSymbol x)
{
return(K.HardSigmoid(x));
}
public static KerasSymbol Linear(KerasSymbol x)
{
return(x);
}
public static KerasSymbol Gather(KerasSymbol reference, KerasSymbol indices)
{
throw new NotImplementedException();
}
public static KerasSymbol Tanh(KerasSymbol x)
{
return(K.Tanh(x));
}
public static KerasSymbol BatchDot(KerasSymbol x, KerasSymbol y, Shape axes = null)
{
throw new NotImplementedException();
}
public static KerasSymbol Transpose(KerasSymbol x)
{
throw new NotImplementedException();
}
public static KerasSymbol Dot(KerasSymbol x, KerasSymbol y)
{
throw new NotImplementedException();
}
public static KerasSymbol MovingAverageUpdate(KerasSymbol x, NDArray value, float momentum)
{
throw new NotImplementedException();
}
public static KerasSymbol UpdateSub(KerasSymbol x, NDArray new_x)
{
throw new NotSupportedException("MXNet Backend: Update operations are not supported yet.");
}
public static KerasSymbol Softsign(KerasSymbol x)
{
return(K.Softsign(x));
}
public static KerasSymbol Identity(KerasSymbol x)
{
throw new NotImplementedException();
}
public static KerasSymbol Relu(KerasSymbol x, float alpha = 0, float?max_value = null, float threshold = 0)
{
return(K.Relu(x, alpha: alpha, max_value: max_value, threshold: threshold));
}
public static KerasSymbol Prod(KerasSymbol x, int axis, bool keepdims = false)
{
throw new NotImplementedException();
}
public static KerasSymbol Sigmoid(KerasSymbol x)
{
return(K.Sigmoid(x));
}
public static KerasSymbol CumProd(KerasSymbol x, int axis = 0)
{
throw new NotSupportedException("MXNet Backend: CumProd operations are not supported yet.");
}
public static KerasSymbol Exponential(KerasSymbol x)
{
return(K.Exp(x));
}
public static KerasSymbol ToDense(KerasSymbol tensor)
{
throw new NotImplementedException();
}
public static KerasSymbol Embedding(KerasSymbol data, KerasSymbol weight, int input_dim, int output_dim, bool sparse_grad = false)
{
throw new NotImplementedException();
}
public static int CountParams(KerasSymbol x)
{
throw new NotImplementedException();
}
