M
Modular•16mo ago
Stijn

cannot be copied into its destination

Hi 👋 , I want to extend my matrix class with the transpose functionality 
alias dtype = DType.float32
alias type = Float32


struct Matrix:
    var data: DTypePointer[dtype]
    var rows: Int
    var cols: Int

    fn __init__(inout self, rows: Int, cols: Int):
        self.data = DTypePointer[dtype].alloc(rows * cols)
        rand(self.data, rows * cols)
        self.rows = rows
        self.cols = cols

    fn __del__(owned self):
        self.data.free()

    fn zero(inout self):
        memset_zero(self.data, self.rows * self.cols)

    @always_inline
    fn __getitem__(self, y: Int, x: Int) -> type:
        return self.load[1](y, x)

    @always_inline
    fn __setitem__(self, y: Int, x: Int, val: type):
        return self.store[1](y, x, val)

    @always_inline
    fn load[nelts: Int](self, y: Int, x: Int) -> SIMD[dtype, nelts]:
        return self.data.simd_load[nelts](y * self.cols + x)

    @always_inline
    fn store[nelts: Int](self, y: Int, x: Int, val: SIMD[dtype, nelts]):
        return self.data.simd_store[nelts](y * self.cols + x, val)

    fn __str__(inout self) -> StringLiteral:
        let matrix_str: StringLiteral = ""
        """
        TODO
        """
        return matrix_str

    @always_inline
    fn T(inout self) -> Matrix:
        let transposed = Matrix(self.cols, self.rows)
        for i in range(self.rows):
            for j in range(self.cols):
                transposed[j, i] = self[i, j]
        return transposed
alias dtype = DType.float32
alias type = Float32


struct Matrix:
    var data: DTypePointer[dtype]
    var rows: Int
    var cols: Int

    fn __init__(inout self, rows: Int, cols: Int):
        self.data = DTypePointer[dtype].alloc(rows * cols)
        rand(self.data, rows * cols)
        self.rows = rows
        self.cols = cols

    fn __del__(owned self):
        self.data.free()

    fn zero(inout self):
        memset_zero(self.data, self.rows * self.cols)

    @always_inline
    fn __getitem__(self, y: Int, x: Int) -> type:
        return self.load[1](y, x)

    @always_inline
    fn __setitem__(self, y: Int, x: Int, val: type):
        return self.store[1](y, x, val)

    @always_inline
    fn load[nelts: Int](self, y: Int, x: Int) -> SIMD[dtype, nelts]:
        return self.data.simd_load[nelts](y * self.cols + x)

    @always_inline
    fn store[nelts: Int](self, y: Int, x: Int, val: SIMD[dtype, nelts]):
        return self.data.simd_store[nelts](y * self.cols + x, val)

    fn __str__(inout self) -> StringLiteral:
        let matrix_str: StringLiteral = ""
        """
        TODO
        """
        return matrix_str

    @always_inline
    fn T(inout self) -> Matrix:
        let transposed = Matrix(self.cols, self.rows)
        for i in range(self.rows):
            for j in range(self.cols):
                transposed[j, i] = self[i, j]
        return transposed
But i get: 
error: value of type 'Matrix' cannot be copied into its destination
        return transposed
error: value of type 'Matrix' cannot be copied into its destination
        return transposed
I experience similar behaviour when trying to return something of type Matrix, in other functions as well. Any idea on how to overcome this?
2 Replies
Jack Clayton
Jack Clayton•16mo ago
Just add a __copyinit__ to your struct: 
    ...
    fn __copyinit__(inout self, other: Self):
        self.data = other.data        
        self.rows = other.rows
        self.cols = other.cols
    ...
    fn __copyinit__(inout self, other: Self):
        self.data = other.data        
        self.rows = other.rows
        self.cols = other.cols
Stijn
StijnOP•16mo ago
As soon as I start using the copies I'm getting: 
free(): double free detected in tcache 2
Please submit a bug report to https://github.com/modularml/mojo/issues and include the crash backtrace along with all the relevant source codes.
Stack dump:
0.      Program arguments: mojo run main.mojo
 #0 0x00005602b1ba3797 (mojo+0x5bc797)
 #1 0x00005602b1ba136e (mojo+0x5ba36e)
 #2 0x00005602b1ba3e6f (mojo+0x5bce6f)
 #3 0x00007f7086242520 (/lib/x86_64-linux-gnu/libc.so.6+0x42520)
 #4 0x00007f7086296a7c __pthread_kill_implementation ./nptl/./nptl/pthread_kill.c:44:76
 #5 0x00007f7086296a7c __pthread_kill_internal ./nptl/./nptl/pthread_kill.c:78:10
 #6 0x00007f7086296a7c pthread_kill ./nptl/./nptl/pthread_kill.c:89:10
 #7 0x00007f7086242476 gsignal ./signal/../sysdeps/posix/raise.c:27:6
 #8 0x00007f70862287f3 abort ./stdlib/./stdlib/abort.c:81:7
 #9 0x00007f70862896f6 __libc_message ./libio/../sysdeps/posix/libc_fatal.c:155:5
#10 0x00007f70862a0d7c ./malloc/./malloc/malloc.c:5668:3
#11 0x00007f70862a312b _int_free ./malloc/./malloc/malloc.c:4687:2
#12 0x00007f70862a54d3 __libc_free ./malloc/./malloc/malloc.c:3394:3
#13 0x00007f6fc400150f 
Aborted
free(): double free detected in tcache 2
Please submit a bug report to https://github.com/modularml/mojo/issues and include the crash backtrace along with all the relevant source codes.
Stack dump:
0.      Program arguments: mojo run main.mojo
 #0 0x00005602b1ba3797 (mojo+0x5bc797)
 #1 0x00005602b1ba136e (mojo+0x5ba36e)
 #2 0x00005602b1ba3e6f (mojo+0x5bce6f)
 #3 0x00007f7086242520 (/lib/x86_64-linux-gnu/libc.so.6+0x42520)
 #4 0x00007f7086296a7c __pthread_kill_implementation ./nptl/./nptl/pthread_kill.c:44:76
 #5 0x00007f7086296a7c __pthread_kill_internal ./nptl/./nptl/pthread_kill.c:78:10
 #6 0x00007f7086296a7c pthread_kill ./nptl/./nptl/pthread_kill.c:89:10
 #7 0x00007f7086242476 gsignal ./signal/../sysdeps/posix/raise.c:27:6
 #8 0x00007f70862287f3 abort ./stdlib/./stdlib/abort.c:81:7
 #9 0x00007f70862896f6 __libc_message ./libio/../sysdeps/posix/libc_fatal.c:155:5
#10 0x00007f70862a0d7c ./malloc/./malloc/malloc.c:5668:3
#11 0x00007f70862a312b _int_free ./malloc/./malloc/malloc.c:4687:2
#12 0x00007f70862a54d3 __libc_free ./malloc/./malloc/malloc.c:3394:3
#13 0x00007f6fc400150f 
Aborted
Any idea? Solved it: 
    @always_inline
    fn __copyinit__(inout self, other: Matrix[dtype, n_rows, n_cols]):
        self.data = DTypePointer[dtype].alloc(n_rows * n_cols)
        for y in range(n_rows):
            for x in range(n_cols):
                self.data.simd_store[1](y * n_cols + x, other.data.simd_load[1](y * n_cols + x))
        self.rows = other.rows
        self.cols = other.cols
    @always_inline
    fn __copyinit__(inout self, other: Matrix[dtype, n_rows, n_cols]):
        self.data = DTypePointer[dtype].alloc(n_rows * n_cols)
        for y in range(n_rows):
            for x in range(n_cols):
                self.data.simd_store[1](y * n_cols + x, other.data.simd_load[1](y * n_cols + x))
        self.rows = other.rows
        self.cols = other.cols

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