/// <summary>
/// Evaluates the specified write target.
/// </summary>
/// <param name="writeTarget">The write target.</param>
/// <returns>Tensor.</returns>
public override NDArray Evaluate(NDArray writeTarget)
{
using (var s = src.Evaluate(null))
using (var i = indices.Evaluate(null))
{
if (!writeTarget.Equals(s))
{
Ops.Copy(writeTarget, s);
}
Ops.ScatterFill(writeTarget, value.Evaluate(), dimension, i);
}
return(writeTarget);
}
/// <summary>
/// Lerps the specified a.
/// </summary>
/// <param name="a">a.</param>
/// <param name="b">The b.</param>
/// <param name="weight">The weight.</param>
/// <returns>SVar.</returns>
public static ScalarVar Lerp(ScalarVar a, ScalarVar b, ScalarVar weight)
{
return(new ScalarVar(new DelegateScalarExpression(() => (float)LerpFloat(a.Evaluate(), b.Evaluate(), weight.Evaluate()))));
}
/// <summary>
/// Atan2s the specified y.
/// </summary>
/// <param name="y">The y.</param>
/// <param name="x">The x.</param>
/// <returns>SVar.</returns>
public static ScalarVar Atan2(ScalarVar y, ScalarVar x)
{
return(new ScalarVar(new DelegateScalarExpression(() => (float)Math.Atan2(y.Evaluate(), x.Evaluate()))));
}
/// <summary>
/// Randoms the cauchy.
/// </summary>
/// <param name="seedSource">The seed source.</param>
/// <param name="median">The median.</param>
/// <param name="sigma">The sigma.</param>
/// <param name="allocator">The allocator.</param>
/// <param name="type">The type.</param>
/// <param name="sizes">The sizes.</param>
/// <returns>TVar.</returns>
public static Variable RandomCauchy(SeedSource seedSource, ScalarVar median, ScalarVar sigma, IAllocator allocator, DType type, params long[] sizes)
{
return(new Variable(new FillExpression(allocator, type, sizes, res => Ops.RandomCauchy(res, seedSource, median.Evaluate(), sigma.Evaluate()))));
}
/// <summary>
/// Randoms the exponential.
/// </summary>
/// <param name="seedSource">The seed source.</param>
/// <param name="lambda">The lambda.</param>
/// <param name="allocator">The allocator.</param>
/// <param name="type">The type.</param>
/// <param name="sizes">The sizes.</param>
/// <returns>TVar.</returns>
public static Variable RandomExponential(SeedSource seedSource, ScalarVar lambda, IAllocator allocator, DType type, params long[] sizes)
{
return(new Variable(new FillExpression(allocator, type, sizes, res => Ops.RandomExponential(res, seedSource, lambda.Evaluate()))));
}
/// <summary>
/// Randoms the normal.
/// </summary>
/// <param name="seedSource">The seed source.</param>
/// <param name="mean">The mean.</param>
/// <param name="stdv">The STDV.</param>
/// <param name="allocator">The allocator.</param>
/// <param name="type">The type.</param>
/// <param name="sizes">The sizes.</param>
/// <returns>TVar.</returns>
public static Variable RandomNormal(SeedSource seedSource, ScalarVar mean, ScalarVar stdv, IAllocator allocator, DType type, params long[] sizes)
{
return(new Variable(new FillExpression(allocator, type, sizes, res => Ops.RandomNormal(res, seedSource, mean.Evaluate(), stdv.Evaluate()))));
}
/// <summary>
/// Randoms the uniform.
/// </summary>
/// <param name="seedSource">The seed source.</param>
/// <param name="min">The minimum.</param>
/// <param name="max">The maximum.</param>
/// <param name="allocator">The allocator.</param>
/// <param name="type">The type.</param>
/// <param name="sizes">The sizes.</param>
/// <returns>TVar.</returns>
public static Variable RandomUniform(SeedSource seedSource, ScalarVar min, ScalarVar max, IAllocator allocator, DType type, params long[] sizes)
{
return(new Variable(new FillExpression(allocator, type, sizes, res => Ops.RandomUniform(res, seedSource, min.Evaluate(), max.Evaluate()))));
}
/// <summary>
/// Lerps the specified a.
/// </summary>
/// <param name="a">a.</param>
/// <param name="b">The b.</param>
/// <param name="weight">The weight.</param>
/// <returns>TVar.</returns>
public static Variable Lerp(Variable a, Variable b, ScalarVar weight)
{
return(new Variable(new BinaryTensorTensorExpression(a.Expression, b.Expression, (res, aVal, bVal) => Ops.Lerp(res, aVal, bVal, weight.Evaluate()))));
}
/// <summary>
/// Clamps the specified minimum.
/// </summary>
/// <param name="min">The minimum.</param>
/// <param name="max">The maximum.</param>
/// <returns>TVar.</returns>
public Variable Clamp(ScalarVar min, ScalarVar max)
{
return(new Variable(new UnaryTensorExpression(this.Expression, (res, src) => Ops.Clamp(res, src, min.Evaluate(), max.Evaluate()))));
}
/// <summary>
/// Fills the specified value.
/// </summary>
/// <param name="value">The value.</param>
/// <param name="allocator">The allocator.</param>
/// <param name="type">The type.</param>
/// <param name="sizes">The sizes.</param>
/// <returns>TVar.</returns>
public static Variable Fill(ScalarVar value, IAllocator allocator, DType type, params long[] sizes)
{
return(new Variable(new FillExpression(allocator, type, sizes, res => Ops.Fill(res, value.Evaluate()))));
}
/// <summary>
/// Randoms the bernoulli.
/// </summary>
/// <param name="seedSource">The seed source.</param>
/// <param name="p">The p.</param>
/// <param name="allocator">The allocator.</param>
/// <param name="type">The type.</param>
/// <param name="sizes">The sizes.</param>
/// <returns>TVar.</returns>
public static Variable RandomBernoulli(SeedSource seedSource, ScalarVar p, IAllocator allocator, DType type, params long[] sizes)
{
return(new Variable(new FillExpression(allocator, type, sizes, res => Ops.RandomBernoulli(res, seedSource, p.Evaluate()))));
}
