# Buggy code
def nanargmin(a, axis=None):
    fill_value = dtypes.get_pos_infinity(a.dtype)
    if a.dtype.kind == "O":
        return _nan_argminmax_object("argmin", fill_value, a, axis=axis)
    a, mask = _replace_nan(a, fill_value)
    if isinstance(a, dask_array_type):
        res = dask_array.argmin(a, axis=axis)
    else:
        res = np.argmin(a, axis=axis)

    if mask is not None:
        mask = mask.all(axis=axis)
        if mask.any():
            raise ValueError("All-NaN slice encountered")
    return res


# Traceback (RuntimeError)
In [1]: import numpy as np
...: import dask
...: import xarray as xr

In [2]: class Scheduler:
...:     """ From: https://stackoverflow.com/questions/53289286/ """
...:
...:     def __init__(self, max_computes=0):
...:         self.max_computes = max_computes
...:         self.total_computes = 0
...:
...:     def __call__(self, dsk, keys, **kwargs):
...:         self.total_computes += 1
...:         if self.total_computes > self.max_computes:
...:             raise RuntimeError(
...:                 "Too many dask computations were scheduled: {}".format(
...:                     self.total_computes
...:                 )
...:             )
...:         return dask.get(dsk, keys, **kwargs)
...:

In [3]: scheduler = Scheduler()

In [4]: with dask.config.set(scheduler=scheduler):
...:     da = xr.DataArray(
...:         np.random.rand(2*3*4).reshape((2, 3, 4)),
...:     ).chunk(dict(dim_0=1))
...:
...:     dim = da.dims[-1]
...:
...:     dask_idcs = da.data.argmax(axis=-1)  # Computes 0 times
...:     print("Total number of computes: %d" % scheduler.total_computes)
...:
...:     da.max(dim)  # Computes 0 times
...:     print("Total number of computes: %d" % scheduler.total_computes)
...:
...:     da.argmax(dim)  # Does compute
...:     print("Total number of computes: %d" % scheduler.total_computes)
...:
Total number of computes: 0
Total number of computes: 0
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-4-f95c8753dbe6> in <module>
12     print("Total number of computes: %d" % scheduler.total_computes)
13
---> 14     da.argmax(dim)  # Does compute
15     print("Total number of computes: %d" % scheduler.total_computes)
16

~/src/xarray/xarray/core/common.py in wrapped_func(self, dim, axis, skipna, **kwargs)
42             def wrapped_func(self, dim=None, axis=None, skipna=None, **kwargs):
43                 return self.reduce(
---> 44                     func, dim, axis, skipna=skipna, allow_lazy=True, **kwargs
45                 )
46

~/src/xarray/xarray/core/dataarray.py in reduce(self, func, dim, axis, keep_attrs, keepdims, **kwargs)
2120         """
2121
-> 2122         var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)
2123         return self._replace_maybe_drop_dims(var)
2124

~/src/xarray/xarray/core/variable.py in reduce(self, func, dim, axis, keep_attrs, keepdims, allow_lazy, **kwargs)
1456         input_data = self.data if allow_lazy else self.values
1457         if axis is not None:
-> 1458             data = func(input_data, axis=axis, **kwargs)
1459         else:
1460             data = func(input_data, **kwargs)

~/src/xarray/xarray/core/duck_array_ops.py in f(values, axis, skipna, **kwargs)
279
280         try:
--> 281             return func(values, axis=axis, **kwargs)
282         except AttributeError:
283             if isinstance(values, dask_array_type):

~/src/xarray/xarray/core/nanops.py in nanargmax(a, axis)
118     if mask is not None:
119         mask = mask.all(axis=axis)
--> 120         if mask.any():
121             raise ValueError("All-NaN slice encountered")
122     return res

/usr/lib/python3.7/site-packages/dask/array/core.py in __bool__(self)
1370             )
1371         else:
-> 1372             return bool(self.compute())
1373
1374     __nonzero__ = __bool__  # python 2

/usr/lib/python3.7/site-packages/dask/base.py in compute(self, **kwargs)
173         dask.base.compute
174         """
--> 175         (result,) = compute(self, traverse=False, **kwargs)
176         return result
177

/usr/lib/python3.7/site-packages/dask/base.py in compute(*args, **kwargs)
444     keys = [x.__dask_keys__() for x in collections]
445     postcomputes = [x.__dask_postcompute__() for x in collections]
--> 446     results = schedule(dsk, keys, **kwargs)
447     return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])
448

# Fixed code
def nanargmin(a, axis=None):
    if a.dtype.kind == "O":
        fill_value = dtypes.get_pos_infinity(a.dtype)
        return _nan_argminmax_object("argmin", fill_value, a, axis=axis)

    module = dask_array if isinstance(a, dask_array_type) else nputils
    return module.nanargmin(a, axis=axis)