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Slightly extend discussions on auto and move the content of the Pit falls wiki page here.
http://eigen.tuxfamily.org/index.php?title=Pit_Falls
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@ -7,14 +7,30 @@ namespace Eigen {
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See this \link TopicTemplateKeyword page \endlink.
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\section TopicPitfalls_aliasing Aliasing
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Don't miss this \link TopicAliasing page \endlink on aliasing,
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especially if you got wrong results in statements where the destination appears on the right hand side of the expression.
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\section TopicPitfalls_alignment_issue Alignment Issues (runtime assertion)
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%Eigen does explicit vectorization, and while that is appreciated by many users, that also leads to some issues in special situations where data alignment is compromised.
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Indeed, since C++17, C++ does not have quite good enough support for explicit data alignment.
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In that case your program hits an assertion failure (that is, a "controlled crash") with a message that tells you to consult this page:
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\code
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http://eigen.tuxfamily.org/dox/group__TopicUnalignedArrayAssert.html
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\endcode
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Have a look at \link TopicUnalignedArrayAssert it \endlink and see for yourself if that's something that you can cope with.
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It contains detailed information about how to deal with each known cause for that issue.
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Now what if you don't care about vectorization and so don't want to be annoyed with these alignment issues? Then read \link getrid how to get rid of them \endlink.
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\section TopicPitfalls_auto_keyword C++11 and the auto keyword
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In short: do not use the auto keywords with Eigen's expressions, unless you are 100% sure about what you are doing. In particular, do not use the auto keyword as a replacement for a Matrix<> type. Here is an example:
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In short: do not use the auto keywords with %Eigen's expressions, unless you are 100% sure about what you are doing. In particular, do not use the auto keyword as a replacement for a \c Matrix<> type. Here is an example:
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\code
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MatrixXd A, B;
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@ -22,23 +38,81 @@ auto C = A*B;
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for(...) { ... w = C * v; ...}
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\endcode
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In this example, the type of C is not a MatrixXd but an abstract expression representing a matrix product and storing references to A and B. Therefore, the product of A*B will be carried out multiple times, once per iteration of the for loop. Moreover, if the coefficients of A or B change during the iteration, then C will evaluate to different values.
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In this example, the type of C is not a \c MatrixXd but an abstract expression representing a matrix product and storing references to \c A and \c B.
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Therefore, the product of \c A*B will be carried out multiple times, once per iteration of the for loop.
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Moreover, if the coefficients of A or B change during the iteration, then C will evaluate to different values.
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Here is another example leading to a segfault:
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\code
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auto C = ((A+B).eval()).transpose();
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// do something with C
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\endcode
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The problem is that eval() returns a temporary object (in this case a MatrixXd) which is then referenced by the Transpose<> expression. However, this temporary is deleted right after the first line, and there the C expression reference a dead object. The same issue might occur when sub expressions are automatically evaluated by Eigen as in the following example:
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The problem is that \c eval() returns a temporary object (in this case a \c MatrixXd) which is then referenced by the \c Transpose<> expression.
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However, this temporary is deleted right after the first line, and then the \c C expression references a dead object.
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One possible fix consists in applying \c eval() on the whole expression:
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\code
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auto C = (A+B).transpose().eval();
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\endcode
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The same issue might occur when sub expressions are automatically evaluated by %Eigen as in the following example:
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\code
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VectorXd u, v;
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auto C = u + (A*v).normalized();
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// do something with C
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\endcode
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where the normalized() method has to evaluate the expensive product A*v to avoid evaluating it twice. On the other hand, the following example is perfectly fine:
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Here the \c normalized() method has to evaluate the expensive product \c A*v to avoid evaluating it twice.
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Again, one possible fix is to call \c .eval() on the whole expression:
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\code
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auto C = (u + (A*v).normalized()).eval();
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\endcode
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In this case, C will be a regular VectorXd object.
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In this case, \c C will be a regular \c VectorXd object.
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Note that DenseBase::eval() is smart enough to avoid copies when the underlying expression is already a plain \c Matrix<>.
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\section TopicPitfalls_header_issues Header Issues (failure to compile)
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With all libraries, one must check the documentation for which header to include.
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The same is true with %Eigen, but slightly worse: with %Eigen, a method in a class may require an additional <code>#include</code> over what the class itself requires!
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For example, if you want to use the \c cross() method on a vector (it computes a cross-product) then you need to:
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\code
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#include<Eigen/Geometry>
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\endcode
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We try to always document this, but do tell us if we forgot an occurrence.
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\section TopicPitfalls_ternary_operator Ternary operator
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In short: avoid the use of the ternary operator <code>(COND ? THEN : ELSE)</code> with %Eigen's expressions for the \c THEN and \c ELSE statements.
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To see why, let's consider the following example:
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\code
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Vector3f A;
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A << 1, 2, 3;
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Vector3f B = ((1 < 0) ? (A.reverse()) : A);
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\endcode
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This example will return <code>B = 3, 2, 1</code>. Do you see why?
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The reason is that in c++ the type of the \c ELSE statement is inferred from the type of the \c THEN expression such that both match.
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Since \c THEN is a <code>Reverse<Vector3f></code>, the \c ELSE statement A is converted to a <code>Reverse<Vector3f></code>, and the compiler thus generates:
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\code
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Vector3f B = ((1 < 0) ? (A.reverse()) : Reverse<Vector3f>(A));
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\endcode
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In this very particular case, a workaround would be to call A.reverse().eval() for the \c THEN statement, but the safest and fastest is really to avoid this ternary operator with %Eigen's expressions and use a if/else construct.
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\section TopicPitfalls_pass_by_value Pass-by-value
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If you don't know why passing-by-value is wrong with %Eigen, read this \link TopicPassingByValue page \endlink first.
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While you may be extremely careful and use care to make sure that all of your code that explicitly uses %Eigen types is pass-by-reference you have to watch out for templates which define the argument types at compile time.
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If a template has a function that takes arguments pass-by-value, and the relevant template parameter ends up being an %Eigen type, then you will of course have the same alignment problems that you would in an explicitly defined function passing %Eigen types by reference.
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Using %Eigen types with other third party libraries or even the STL can present the same problem.
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<code>boost::bind</code> for example uses pass-by-value to store arguments in the returned functor.
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This will of course be a problem.
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There are at least two ways around this:
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- If the value you are passing is guaranteed to be around for the life of the functor, you can use boost::ref() to wrap the value as you pass it to boost::bind. Generally this is not a solution for values on the stack as if the functor ever gets passed to a lower or independent scope, the object may be gone by the time it's attempted to be used.
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- The other option is to make your functions take a reference counted pointer like boost::shared_ptr as the argument. This avoids needing to worry about managing the lifetime of the object being passed.
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*/
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}
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