public static Tensor[] _MulGrad(EagerOperation op, IntPtr[] grads)
{
var x = op.InputHandles[0];
var y = op.InputHandles[1];
var grad = grads[0];
if (op.SkipInputIndices.Contains(1) &&
EagerTensor.GetRank(grad) == 0)
{
return(new Tensor[]
{
null,//gen_math_ops.mul(grad, math_ops.conj(y)),
null
});
}
if (_ShapesFullySpecifiedAndEqual(x, y, grad))
{
return(new Tensor[]
{
gen_math_ops.mul(grad, y),
gen_math_ops.mul(grad, x)
});
}
throw new NotImplementedException("");
}
public static Func <EagerOperation, IntPtr[], EagerTensor[]> get_gradient_function_eager(EagerOperation op)
{
if (op.inputs == null)
{
return(null);
}
RegisterFromAssemblyEager();
if (!gradientFunctionsEager.ContainsKey(op.type))
{
throw new LookupError($"can't get graident function through get_gradient_function {op.type}");
}
return(gradientFunctionsEager[op.type]);
}
