xsuite / xsuite Goto Github PK

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-4-a5a954f0bd97> in <module>
----> 1 s = MyStruct()

~/Desktop/20210303_xfields_gpudev/xobjects/xobjects/struct.py in __init__(self, _context, _buffer, _offset, *args, **kwags)
    326         args, kwargs = cls._pre_init(*args, **kwargs)
    327         # compute resources
--> 328         info = cls._inspect_args(*args, **kwargs)
    329         self._size = info.size
    330         # acquire buffer

[...]

~/Desktop/20210303_xfields_gpudev/xobjects/xobjects/array.py in _inspect_args(cls, *args)
    310                 value = args[0]
    311             else:  # complete dimensions
--> 312                 if not is_integer(args[0]):  # init with array
    313                     value = args[0]
    314                     shape = get_shape_from_array(value)

IndexError: tuple index out of range

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-5-d4e36c877d76> in <module>
      7 drift  = xt.Drift(_context=ctx2, length=1.)
      8
----> 9 drift.track(part)

~/Desktop/20210705_xsuite_dev/xtrack/xtrack/dress_element.py in track(self, particles)
     63
     64         self._track_kernel.description.n_threads = particles.num_particles
---> 65         self._track_kernel(el=self._xobject, particles=particles)
     66
     67     DressedElement.compile_track_kernel = compile_track_kernel

~/Desktop/20210705_xsuite_dev/xobjects/xobjects/context_cupy.py in __call__(self, **kwargs)
    376
    377         grid_size = int(np.ceil(n_threads / self.block_size))
--> 378         self.function((grid_size,), (self.block_size,), arg_list)
    379
    380

cupy/_core/raw.pyx in cupy._core.raw.RawKernel.__call__()

cupy/cuda/function.pyx in cupy.cuda.function.Function.__call__()

cupy/cuda/function.pyx in cupy.cuda.function._launch()

cupy/cuda/function.pyx in cupy.cuda.function._pointer()

TypeError: Unsupported type <class 'numpy.ndarray'>

 CMAKE_BUILD_TYPE                 Release                                                         
 CMAKE_INSTALL_PREFIX             /home/giadarol/Desktop/20210303_xfields_gpudev/bdsim_env/install/geant4
 GEANT4_BUILD_MULTITHREADED       OFF                                                             
 GEANT4_INSTALL_DATA              ON                                                              
 GEANT4_INSTALL_DATADIR                                                                           
 GEANT4_USE_G3TOG4                OFF                                                             
 GEANT4_USE_GDML                  OFF                                                              
 GEANT4_USE_INVENTOR              OFF                                                             
 GEANT4_USE_OPENGL_X11            ON                                                              
 GEANT4_USE_QT                    ON                                                              
 GEANT4_USE_RAYTRACER_X11         ON                                                              
 GEANT4_USE_SYSTEM_CLHEP          ON                                                              
 GEANT4_USE_SYSTEM_EXPAT          ON                                                              
 GEANT4_USE_SYSTEM_ZLIB           OFF                                                             
 GEANT4_USE_XM                    ON    

make -j 24 install
cd ../../

================================================================================================================================== FAILURES ===================================================================================================================================
___________________________________________________________________________________________________________________________ test_collective_tracker ___________________________________________________________________________________________________________________________

    def test_collective_tracker():
    
        for CTX in xo.ContextCpu, xo.ContextPyopencl, xo.ContextCupy:
            if CTX not in available:
                continue
        # ....
            
            print('Track a few turns...')
            n_turns = 10
>           tracker.track(particles, num_turns=n_turns,
                          turn_by_turn_monitor=True)

tests/test_collective_tracker.py:72: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xtrack/tracker.py:406: in _track_with_collective
    pp.track(particles)
../xfields/xfields/beam_elements/spacecharge.py:231: in track
    super().track(particles)
xtrack/base_element.py:119: in track
    self._track_kernel(el=self._xobject, particles=particles)
../xobjects/xobjects/context_pyopencl.py:462: in __call__
    arg_list.append(self.to_function_arg(arg, vv))
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <xobjects.context_pyopencl.KernelPyopencl object at 0x7fee0d22ce50>, arg = <xobjects.context.Arg object at 0x7fee033dc4c0>, value = SpaceChargeBiGaussianData(...)

    def to_function_arg(self, arg, value):
        if arg.pointer:
            if hasattr(arg.atype, "_dtype"):  # it is numerical scalar
                if isinstance(value, cl.Buffer):
                    return value
                elif hasattr(value, "dtype"):  # nparray
                    assert isinstance(value, cla.Array)
                    return value.base_data[value.offset :]
                elif hasattr(value, "_shape"):  # xobject array
                    raise NotImplementedError
                else:
                    raise NotImplementedError
            else:
                raise ValueError(
                    f"Invalid value {value} for argument {arg.name} "
                    f"of kernel {self.description.pyname}"
                )
        else:
            if hasattr(arg.atype, "_dtype"):  # it is numerical scalar
                return arg.atype(value)  # try to return a numpy scalar
            elif hasattr(arg.atype, "_size"):  # it is a compound xobject
>               return value._buffer.buffer[value._offset :]
E               pyopencl._cl.RuntimeError: clCreateSubBuffer failed: MISALIGNED_SUB_BUFFER_OFFSET

../xobjects/xobjects/context_pyopencl.py:447: RuntimeError

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-3-1fe53bc9bc1a> in <module>
     43 
     44 ## Try to access turn-by-turn data
---> 45 tracker.record_last_track.x

~/Desktop/20210303_xfields_gpudev/xtrack/xtrack/monitors.py in __get__(self, container, ContainerType)
     59 
     60     def __get__(self, container, ContainerType=None):
---> 61         vv = getattr(container.data, self.name)
     62         n_cols = container.stop_at_turn - container.start_at_turn
     63         n_rows = container.n_records // n_cols

~/Desktop/20210303_xfields_gpudev/xtrack/xtrack/dress.py in __get__(self, container, ContainerType)
     14     def __get__(self, container, ContainerType=None):
     15         if self.isnplikearray:
---> 16             return getattr(container._xobject, self.name).to_nplike()
     17         elif hasattr(container, '_dressed_'+self.name):
     18             return getattr(container, '_dressed_'+self.name)

~/Desktop/20210303_xfields_gpudev/xobjects/xobjects/array.py in to_nplike(self)
    573         cshape = [shape[ii] for ii in self._order]
    574         if hasattr(self._itemtype, "_dtype"):
--> 575             arr = self._buffer.to_nplike(
    576                 self._offset + self._data_offset, self._itemtype._dtype, cshape
    577             ).transpose(self._order)

~/Desktop/20210303_xfields_gpudev/xobjects/xobjects/context_cpu.py in to_nplike(self, offset, dtype, shape)
    445         # dtype=np.dtype(dtype)
    446         # return self.buffer[offset:].view(dtype)[:count].reshape(*shape)
--> 447         return np.frombuffer(
    448             self.buffer, dtype=dtype, count=count, offset=offset
    449         ).reshape(*shape)

ValueError: buffer is smaller than requested size