Cleanup the @generated_jit leftovers (pygae#430)

The test_function_cache is rewritten to use @njit, which may not make
much sense for particular test.

clifford/__init__.py

@@ -81,12 +81,7 @@
 
 # Major library imports.
 import numpy as np
-import numba as _numba  # to avoid clashing with clifford.numba
 import sparse
-try:
-    from numba.np import numpy_support as _numpy_support
-except ImportError:
-    import numba.numpy_support as _numpy_support
 
 
 from clifford.io import write_ga_file, read_ga_file  # noqa: F401
@@ -152,12 +147,6 @@ def get_mult_function(mt: sparse.COO, gradeList,
         return _get_mult_function_runtime_sparse(mt)
 
 
-def _get_mult_function_result_type(a: _numba.types.Type, b: _numba.types.Type, mt: np.dtype):
-    a_dt = _numpy_support.as_dtype(getattr(a, 'dtype', a))
-    b_dt = _numpy_support.as_dtype(getattr(b, 'dtype', b))
-    return np.result_type(a_dt, mt, b_dt)
-
-
 def _get_mult_function(mt: sparse.COO):
     """
     Get a function similar to `` lambda a, b: np.einsum('i,ijk,k->j', a, mt, b)``

clifford/_numba_utils.py

@@ -59,39 +59,11 @@ def __repr__(self):
         return "_pickleable_function({!r})".format(self.__func)
 
 
-class _fake_generated_jit:
-    def __init__(self, f):
-        self.__cache = {}
-        self.__func = pickleable_function(f)
-        functools.update_wrapper(self, self.__func)
-
-    def __getnewargs_ex__(self):
-        return (self.__func,), {}
-
-    def __getstate__(self):
-        return {}
-
-    def __call__(self, *args):
-        arg_type = tuple(numba.typeof(arg) for arg in args)
-        try:
-            func = self.__cache[arg_type]
-        except KeyError:
-            func = self.__cache[arg_type] = self.__func(*arg_type)
-        return func(*args)
-
-
 if not DISABLE_JIT:
     njit = numba.njit
-    generated_jit = numba.generated_jit
 else:
     def njit(f=None, **kwargs):
         if f is None:
             return pickleable_function
         else:
             return pickleable_function(f)
-
-    def generated_jit(f=None, **kwargs):
-        if f is None:
-            return _fake_generated_jit
-        else:
-            return _fake_generated_jit(f)

clifford/test/test_function_cache.py

@@ -1,19 +1,15 @@
 import numpy as np
-from clifford._numba_utils import generated_jit
+from clifford._numba_utils import njit
 import pytest
 
 
-@generated_jit(cache=True)
-def foo(x):
-    from clifford.g3 import e3
-
-    def impl(x):
-        return (x * e3).value
-    return impl
+@njit(cache=True)
+def foo(x, y):
+    return (x * y).value
 
 
 # Make the test fail on a failed cache warning
 @pytest.mark.filterwarnings("error")
 def test_function_cache():
     from clifford.g3 import e3
-    np.testing.assert_array_equal((1.0*e3).value, foo(1.0))
+    np.testing.assert_array_equal((1.0*e3).value, foo(1.0, e3))