---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-2-b21820d122aa> in <module>
      8 x = x.map_blocks(cupy.asarray)
      9 t = da.triu(x)
---> 10 t.compute()

~/.conda/envs/sgkit-gpu-new/lib/python3.8/site-packages/dask/base.py in compute(self, **kwargs)
    281         dask.base.compute
    282         """
--> 283         (result,) = compute(self, traverse=False, **kwargs)
    284         return result
    285 

~/.conda/envs/sgkit-gpu-new/lib/python3.8/site-packages/dask/base.py in compute(*args, **kwargs)
    563         postcomputes.append(x.__dask_postcompute__())
    564 
--> 565     results = schedule(dsk, keys, **kwargs)
    566     return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])
    567 

~/.conda/envs/sgkit-gpu-new/lib/python3.8/site-packages/dask/threaded.py in get(dsk, result, cache, num_workers, pool, **kwargs)
     74                 pools[thread][num_workers] = pool
     75 
---> 76     results = get_async(
     77         pool.apply_async,
     78         len(pool._pool),

~/.conda/envs/sgkit-gpu-new/lib/python3.8/site-packages/dask/local.py in get_async(apply_async, num_workers, dsk, result, cache, get_id, rerun_exceptions_locally, pack_exception, raise_exception, callbacks, dumps, loads, **kwargs)
    485                         _execute_task(task, data)  # Re-execute locally
    486                     else:
--> 487                         raise_exception(exc, tb)
    488                 res, worker_id = loads(res_info)
    489                 state["cache"][key] = res

~/.conda/envs/sgkit-gpu-new/lib/python3.8/site-packages/dask/local.py in reraise(exc, tb)
    315     if exc.__traceback__ is not tb:
    316         raise exc.with_traceback(tb)
--> 317     raise exc
    318 
    319 

~/.conda/envs/sgkit-gpu-new/lib/python3.8/site-packages/dask/local.py in execute_task(key, task_info, dumps, loads, get_id, pack_exception)
    220     try:
    221         task, data = loads(task_info)
--> 222         result = _execute_task(task, data)
    223         id = get_id()
    224         result = dumps((result, id))

~/.conda/envs/sgkit-gpu-new/lib/python3.8/site-packages/dask/core.py in _execute_task(arg, cache, dsk)
    119         # temporaries by their reference count and can execute certain
    120         # operations in-place.
--> 121         return func(*(_execute_task(a, cache) for a in args))
    122     elif not ishashable(arg):
    123         return arg

~/.conda/envs/sgkit-gpu-new/lib/python3.8/site-packages/dask/optimization.py in __call__(self, *args)
    961         if not len(args) == len(self.inkeys):
    962             raise ValueError("Expected %d args, got %d" % (len(self.inkeys), len(args)))
--> 963         return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args)))
    964 
    965     def __reduce__(self):

~/.conda/envs/sgkit-gpu-new/lib/python3.8/site-packages/dask/core.py in get(dsk, out, cache)
    149     for key in toposort(dsk):
    150         task = dsk[key]
--> 151         result = _execute_task(task, cache)
    152         cache[key] = result
    153     result = _execute_task(out, cache)

~/.conda/envs/sgkit-gpu-new/lib/python3.8/site-packages/dask/core.py in _execute_task(arg, cache, dsk)
    119         # temporaries by their reference count and can execute certain
    120         # operations in-place.
--> 121         return func(*(_execute_task(a, cache) for a in args))
    122     elif not ishashable(arg):
    123         return arg

<__array_function__ internals> in where(*args, **kwargs)

cupy/core/core.pyx in cupy.core.core.ndarray.__array_function__()

~/.conda/envs/sgkit-gpu-new/lib/python3.8/site-packages/cupy/_sorting/search.py in where(condition, x, y)
    209     if fusion._is_fusing():
    210         return fusion._call_ufunc(_where_ufunc, condition, x, y)
--> 211     return _where_ufunc(condition.astype('?'), x, y)
    212 
    213 

cupy/core/_kernel.pyx in cupy.core._kernel.ufunc.__call__()

cupy/core/_kernel.pyx in cupy.core._kernel._preprocess_args()

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