[BUG]Cannot query dataframes with categorical columns

[taureandyernv]

Describe the bug
if i do a simple query on a categorical column, i get an error stating that This error is usually caused by passing an argument of a type that is unsupported by the named function.

Steps/Code to reproduce bug

import cudf
import pandas as pd

fn = 'test.csv'
lines = """id1,id2
1,45
2,3
3, 7
1, 25
"""
with open(fn, 'w') as fp:
    fp.write(lines)
pdf = pd.read_csv(fn, header=0, dtype={"id1":"category", "id2":"int32"})
cdf = cudf.read_csv(fn, header=0, dtype={"id1":"int32", "id2":"int32"}) #see #3960 for why i have to do this
cdf['id1'] = cdf['id1'].astype("category")
pdf.query("id1 == ['1'] and id2 == 45")
cdf.query("id1 == ['1'] and id2 == 45")

The cdf query outputs a rather large error

---------------------------------------------------------------------------
TypingError                               Traceback (most recent call last)
<ipython-input-27-28a794912e6e> in <module>
----> 1 cdf2.query("id1 == ['1'] and id2 == 45")

/opt/conda/envs/rapids/lib/python3.7/site-packages/cudf/core/dataframe.py in query(self, expr, local_dict)
   2893         }
   2894         # Run query
-> 2895         boolmask = queryutils.query_execute(self, expr, callenv)
   2896 
   2897         selected = Series(boolmask)

/opt/conda/envs/rapids/lib/python3.7/site-packages/cudf/utils/queryutils.py in query_execute(df, expr, callenv)
    223     # run kernel
    224     args = [out] + colarrays + envargs
--> 225     kernel.forall(nrows)(*args)
    226     out_mask = applyutils.make_aggregate_nullmask(df, columns=columns)
    227     if out_mask is not None:

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/cuda/compiler.py in __call__(self, *args)
    264     def __call__(self, *args):
    265         if isinstance(self.kernel, AutoJitCUDAKernel):
--> 266             kernel = self.kernel.specialize(*args)
    267         else:
    268             kernel = self.kernel

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/cuda/compiler.py in specialize(self, *args)
    808         argtypes = tuple(
    809             [self.typingctx.resolve_argument_type(a) for a in args])
--> 810         kernel = self.compile(argtypes)
    811         return kernel
    812 

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/cuda/compiler.py in compile(self, sig)
    824                 self.targetoptions['link'] = ()
    825             kernel = compile_kernel(self.py_func, argtypes,
--> 826                                     **self.targetoptions)
    827             self.definitions[(cc, argtypes)] = kernel
    828             if self.bind:

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/compiler_lock.py in _acquire_compile_lock(*args, **kwargs)
     30         def _acquire_compile_lock(*args, **kwargs):
     31             with self:
---> 32                 return func(*args, **kwargs)
     33         return _acquire_compile_lock
     34 

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/cuda/compiler.py in compile_kernel(pyfunc, args, link, debug, inline, fastmath, extensions, max_registers)
     60 def compile_kernel(pyfunc, args, link, debug=False, inline=False,
     61                    fastmath=False, extensions=[], max_registers=None):
---> 62     cres = compile_cuda(pyfunc, types.void, args, debug=debug, inline=inline)
     63     fname = cres.fndesc.llvm_func_name
     64     lib, kernel = cres.target_context.prepare_cuda_kernel(cres.library, fname,

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/compiler_lock.py in _acquire_compile_lock(*args, **kwargs)
     30         def _acquire_compile_lock(*args, **kwargs):
     31             with self:
---> 32                 return func(*args, **kwargs)
     33         return _acquire_compile_lock
     34 

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/cuda/compiler.py in compile_cuda(pyfunc, return_type, args, debug, inline)
     49                                   return_type=return_type,
     50                                   flags=flags,
---> 51                                   locals={})
     52 
     53     library = cres.library

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/compiler.py in compile_extra(typingctx, targetctx, func, args, return_type, flags, locals, library, pipeline_class)
    526     pipeline = pipeline_class(typingctx, targetctx, library,
    527                               args, return_type, flags, locals)
--> 528     return pipeline.compile_extra(func)
    529 
    530 

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/compiler.py in compile_extra(self, func)
    324         self.state.lifted = ()
    325         self.state.lifted_from = None
--> 326         return self._compile_bytecode()
    327 
    328     def compile_ir(self, func_ir, lifted=(), lifted_from=None):

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/compiler.py in _compile_bytecode(self)
    383         """
    384         assert self.state.func_ir is None
--> 385         return self._compile_core()
    386 
    387     def _compile_ir(self):

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/compiler.py in _compile_core(self)
    363                 self.state.status.fail_reason = e
    364                 if is_final_pipeline:
--> 365                     raise e
    366         else:
    367             raise CompilerError("All available pipelines exhausted")

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/compiler.py in _compile_core(self)
    354             res = None
    355             try:
--> 356                 pm.run(self.state)
    357                 if self.state.cr is not None:
    358                     break

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/compiler_machinery.py in run(self, state)
    326                     (self.pipeline_name, pass_desc)
    327                 patched_exception = self._patch_error(msg, e)
--> 328                 raise patched_exception
    329 
    330     def dependency_analysis(self):

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/compiler_machinery.py in run(self, state)
    317                 pass_inst = _pass_registry.get(pss).pass_inst
    318                 if isinstance(pass_inst, CompilerPass):
--> 319                     self._runPass(idx, pass_inst, state)
    320                 else:
    321                     raise BaseException("Legacy pass in use")

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/compiler_lock.py in _acquire_compile_lock(*args, **kwargs)
     30         def _acquire_compile_lock(*args, **kwargs):
     31             with self:
---> 32                 return func(*args, **kwargs)
     33         return _acquire_compile_lock
     34 

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/compiler_machinery.py in _runPass(self, index, pss, internal_state)
    279             mutated |= check(pss.run_initialization, internal_state)
    280         with SimpleTimer() as pass_time:
--> 281             mutated |= check(pss.run_pass, internal_state)
    282         with SimpleTimer() as finalize_time:
    283             mutated |= check(pss.run_finalizer, internal_state)

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/compiler_machinery.py in check(func, compiler_state)
    266 
    267         def check(func, compiler_state):
--> 268             mangled = func(compiler_state)
    269             if mangled not in (True, False):
    270                 msg = ("CompilerPass implementations should return True/False. "

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/typed_passes.py in run_pass(self, state)
     92                 state.args,
     93                 state.return_type,
---> 94                 state.locals)
     95             state.typemap = typemap
     96             state.return_type = return_type

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/typed_passes.py in type_inference_stage(typingctx, interp, args, return_type, locals)
     64 
     65         infer.build_constraint()
---> 66         infer.propagate()
     67         typemap, restype, calltypes = infer.unify()
     68 

/opt/conda/envs/rapids/lib/python3.7/site-packages/numba/typeinfer.py in propagate(self, raise_errors)
    949                                   if isinstance(e, ForceLiteralArg)]
    950                 if not force_lit_args:
--> 951                     raise errors[0]
    952                 else:
    953                     raise reduce(operator.or_, force_lit_args)

TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Invalid use of Function(<numba.cuda.compiler.DeviceFunctionTemplate object at 0x7f914147a320>) with argument(s) of type(s): (int32, int32)
 * parameterized
In definition 0:
    TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Invalid use of Function(<built-in function eq>) with argument(s) of type(s): (int32, list(unicode_type))
Known signatures:
 * (bool, bool) -> bool
 * (int8, int8) -> bool
 * (int16, int16) -> bool
 * (int32, int32) -> bool
 * (int64, int64) -> bool
 * (uint8, uint8) -> bool
 * (uint16, uint16) -> bool
 * (uint32, uint32) -> bool
 * (uint64, uint64) -> bool
 * (float32, float32) -> bool
 * (float64, float64) -> bool
 * (complex64, complex64) -> bool
 * (complex128, complex128) -> bool
 * parameterized
In definition 0:
    All templates rejected with literals.
In definition 1:
    All templates rejected without literals.
In definition 2:
    All templates rejected with literals.
In definition 3:
    All templates rejected without literals.
In definition 4:
    All templates rejected with literals.
In definition 5:
    All templates rejected without literals.
In definition 6:
    All templates rejected with literals.
In definition 7:
    All templates rejected without literals.
In definition 8:
    All templates rejected with literals.
In definition 9:
    All templates rejected without literals.
In definition 10:
    All templates rejected with literals.
In definition 11:
    All templates rejected without literals.
In definition 12:
    All templates rejected with literals.
In definition 13:
    All templates rejected without literals.
In definition 14:
    All templates rejected with literals.
In definition 15:
    All templates rejected without literals.
In definition 16:
    All templates rejected with literals.
In definition 17:
    All templates rejected without literals.
In definition 18:
    All templates rejected with literals.
In definition 19:
    All templates rejected without literals.
This error is usually caused by passing an argument of a type that is unsupported by the named function.
[1] During: typing of intrinsic-call at <string> (2)

File "<string>", line 2:
<source missing, REPL/exec in use?>

    raised from /opt/conda/envs/rapids/lib/python3.7/site-packages/numba/typeinfer.py:951
In definition 1:
    TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Invalid use of Function(<built-in function eq>) with argument(s) of type(s): (int32, list(unicode_type))
Known signatures:
 * (bool, bool) -> bool
 * (int8, int8) -> bool
 * (int16, int16) -> bool
 * (int32, int32) -> bool
 * (int64, int64) -> bool
 * (uint8, uint8) -> bool
 * (uint16, uint16) -> bool
 * (uint32, uint32) -> bool
 * (uint64, uint64) -> bool
 * (float32, float32) -> bool
 * (float64, float64) -> bool
 * (complex64, complex64) -> bool
 * (complex128, complex128) -> bool
 * parameterized
In definition 0:
    All templates rejected with literals.
In definition 1:
    All templates rejected without literals.
In definition 2:
    All templates rejected with literals.
In definition 3:
    All templates rejected without literals.
In definition 4:
    All templates rejected with literals.
In definition 5:
    All templates rejected without literals.
In definition 6:
    All templates rejected with literals.
In definition 7:
    All templates rejected without literals.
In definition 8:
    All templates rejected with literals.
In definition 9:
    All templates rejected without literals.
In definition 10:
    All templates rejected with literals.
In definition 11:
    All templates rejected without literals.
In definition 12:
    All templates rejected with literals.
In definition 13:
    All templates rejected without literals.
In definition 14:
    All templates rejected with literals.
In definition 15:
    All templates rejected without literals.
In definition 16:
    All templates rejected with literals.
In definition 17:
    All templates rejected without literals.
In definition 18:
    All templates rejected with literals.
In definition 19:
    All templates rejected without literals.
This error is usually caused by passing an argument of a type that is unsupported by the named function.
[1] During: typing of intrinsic-call at <string> (2)

File "<string>", line 2:
<source missing, REPL/exec in use?>

    raised from /opt/conda/envs/rapids/lib/python3.7/site-packages/numba/typeinfer.py:951
This error is usually caused by passing an argument of a type that is unsupported by the named function.
[1] During: resolving callee type: Function(<numba.cuda.compiler.DeviceFunctionTemplate object at 0x7f914147a320>)
[2] During: typing of call at <string> (6)


File "<string>", line 6:
<source missing, REPL/exec in use?>

Expected behavior
I expect it to output similar to the pdf.query, pdf.query("id1 == ['1'] and id2 == 45")

id1	id2
1	45

Environment overview (please complete the following information)

• Environment location: [Docker]
• Method of cuDF install: [Docker]

Additional context
Converting from cudf to pandas to do the query also inexplicitly fails

tdf = cdf.to_pandas()
tdf['id1']

will output correctly with

0    1
1    2
2    3
3    1
Name: id1, dtype: category
Categories (3, int64): [1, 2, 3]

but when you run the query...

tdf.query("id1 == ['1'] and id2 == 45")

Outputs an empty table

	id1	id2