>>> import torch
>>> import numpy as np
>>> a = np.random.random(1239*25).reshape(-1, 25).astype(np.float16)
>>> torch.tensor(a[:40])

tensor([[0.7393, 0.1298, 0.9209, 0.3218, 0.0799, 0.0392, 0.3503, 0.8389, 0.5161,
         0.4705, 0.3870, 0.8120, 0.7759, 0.3667, 0.9966, 0.4863, 0.9233, 0.4229,
         0.8965, 0.8398, 0.8677, 0.7915, 0.5654, 0.3433, 0.3972],
...

>>> torch.tensor(a[:41])

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
/usr/anaconda3/lib/python3.6/site-packages/IPython/core/formatters.py in __call__(self, obj)
    700                 type_pprinters=self.type_printers,
    701                 deferred_pprinters=self.deferred_printers)
--> 702             printer.pretty(obj)
    703             printer.flush()
    704             return stream.getvalue()

/usr/anaconda3/lib/python3.6/site-packages/IPython/lib/pretty.py in pretty(self, obj)
    393                             if callable(meth):
    394                                 return meth(obj, self, cycle)
--> 395             return _default_pprint(obj, self, cycle)
    396         finally:
    397             self.end_group()

/usr/anaconda3/lib/python3.6/site-packages/IPython/lib/pretty.py in _default_pprint(obj, p, cycle)
    508     if _safe_getattr(klass, '__repr__', None) is not object.__repr__:
    509         # A user-provided repr. Find newlines and replace them with p.break_()
--> 510         _repr_pprint(obj, p, cycle)
    511         return
    512     p.begin_group(1, '<')

/usr/anaconda3/lib/python3.6/site-packages/IPython/lib/pretty.py in _repr_pprint(obj, p, cycle)
    699     """A pprint that just redirects to the normal repr function."""
    700     # Find newlines and replace them with p.break_()
--> 701     output = repr(obj)
    702     for idx,output_line in enumerate(output.splitlines()):
    703         if idx:

/usr/anaconda3/lib/python3.6/site-packages/torch/tensor.py in __repr__(self)
     55         # characters to replace unicode characters with.
     56         if sys.version_info > (3,):
---> 57             return torch._tensor_str._str(self)
     58         else:
     59             if hasattr(sys.stdout, 'encoding'):

/usr/anaconda3/lib/python3.6/site-packages/torch/_tensor_str.py in _str(self)
    254             suffix += ', dtype=' + str(self.dtype)
    255 
--> 256         formatter = _Formatter(get_summarized_data(self) if summarize else self)
    257         tensor_str = _tensor_str(self, indent, formatter, summarize)
    258 

/usr/anaconda3/lib/python3.6/site-packages/torch/_tensor_str.py in get_summarized_data(self)
    214             return self
    215     if self.size(0) > 2 * PRINT_OPTS.edgeitems:
--> 216         start = [get_summarized_data(self[i]).view(-1) for i in range(0, PRINT_OPTS.edgeitems)]
    217         end = ([get_summarized_data(self[i]).view(-1)
    218                for i in range(len(self) - PRINT_OPTS.edgeitems, len(self))])

/usr/anaconda3/lib/python3.6/site-packages/torch/_tensor_str.py in <listcomp>(.0)
    214             return self
    215     if self.size(0) > 2 * PRINT_OPTS.edgeitems:
--> 216         start = [get_summarized_data(self[i]).view(-1) for i in range(0, PRINT_OPTS.edgeitems)]
    217         end = ([get_summarized_data(self[i]).view(-1)
    218                for i in range(len(self) - PRINT_OPTS.edgeitems, len(self))])

/usr/anaconda3/lib/python3.6/site-packages/torch/_tensor_str.py in get_summarized_data(self)
    210     if dim == 1:
    211         if self.size(0) > 2 * PRINT_OPTS.edgeitems:
--> 212             return torch.cat((self[:PRINT_OPTS.edgeitems], self[-PRINT_OPTS.edgeitems:]))
    213         else:
    214             return self

RuntimeError: _cat is not implemented for type torch.HalfTensor

# conda list pytorch
# packages in environment at /usr/anaconda3:
#
# Name                    Version                   Build  Channel
pytorch                   0.4.1            py36ha74772b_0