1579 lines
46 KiB
Python
1579 lines
46 KiB
Python
import itertools
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import functools
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import sys
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import operator
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from collections import namedtuple
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import numpy as np
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import unittest
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import warnings
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from numba import jit, typeof, njit, typed
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from numba.core import errors, types, config
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from numba.tests.support import (TestCase, tag, ignore_internal_warnings,
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MemoryLeakMixin)
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from numba.core.extending import overload_method, box
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forceobj_flags = {'forceobj': True}
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no_pyobj_flags = {'nopython': True, '_nrt': False}
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nrt_no_pyobj_flags = {'nopython': True}
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def abs_usecase(x):
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return abs(x)
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def all_usecase(x, y):
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if x == None and y == None:
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return all([])
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elif x == None:
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return all([y])
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elif y == None:
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return all([x])
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else:
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return all([x, y])
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def any_usecase(x, y):
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if x == None and y == None:
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return any([])
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elif x == None:
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return any([y])
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elif y == None:
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return any([x])
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else:
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return any([x, y])
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def bool_usecase(x):
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return bool(x)
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def complex_usecase(x, y):
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return complex(x, y)
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def divmod_usecase(x, y):
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return divmod(x, y)
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def enumerate_usecase():
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result = 0
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for i, j in enumerate((1., 2.5, 3.)):
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result += i * j
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return result
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def enumerate_start_usecase():
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result = 0
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for i, j in enumerate((1., 2.5, 3.), 42):
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result += i * j
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return result
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def enumerate_invalid_start_usecase():
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result = 0
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for i, j in enumerate((1., 2.5, 3.), 3.14159):
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result += i * j
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return result
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def filter_usecase(x, filter_func):
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return filter(filter_func, x)
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def float_usecase(x):
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return float(x)
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def format_usecase(x, y):
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return x.format(y)
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def globals_usecase():
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return globals()
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# NOTE: hash() is tested in test_hashing
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def hex_usecase(x):
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return hex(x)
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def str_usecase(x):
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return str(x)
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def int_usecase(x, base):
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return int(x, base=base)
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def iter_next_usecase(x):
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it = iter(x)
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return next(it), next(it)
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def locals_usecase(x):
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y = 5
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return locals()['y']
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def long_usecase(x, base):
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return long(x, base=base)
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def map_usecase(x, map_func):
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return map(map_func, x)
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def max_usecase1(x, y):
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return max(x, y)
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def max_usecase2(x, y):
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return max([x, y])
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def max_usecase3(x):
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return max(x)
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def max_usecase4():
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return max(())
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def min_usecase1(x, y):
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return min(x, y)
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def min_usecase2(x, y):
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return min([x, y])
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def min_usecase3(x):
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return min(x)
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def min_usecase4():
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return min(())
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def oct_usecase(x):
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return oct(x)
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def reduce_usecase(reduce_func, x):
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return functools.reduce(reduce_func, x)
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def round_usecase1(x):
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return round(x)
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def round_usecase2(x, n):
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return round(x, n)
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def sum_usecase(x):
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return sum(x)
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def type_unary_usecase(a, b):
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return type(a)(b)
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def truth_usecase(p):
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return operator.truth(p)
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def unichr_usecase(x):
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return unichr(x)
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def zip_usecase():
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result = 0
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for i, j in zip((1, 2, 3), (4.5, 6.7)):
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result += i * j
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return result
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def zip_0_usecase():
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result = 0
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for i in zip():
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result += 1
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return result
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def zip_1_usecase():
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result = 0
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for i, in zip((1, 2)):
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result += i
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return result
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def zip_3_usecase():
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result = 0
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for i, j, k in zip((1, 2), (3, 4, 5), (6.7, 8.9)):
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result += i * j * k
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return result
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def zip_first_exhausted():
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iterable = range(7)
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n = 3
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it = iter(iterable)
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# 1st iterator is shorter
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front = list(zip(range(n), it))
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# Make sure that we didn't skip one in `it`
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back = list(it)
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return front, back
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def pow_op_usecase(x, y):
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return x ** y
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def pow_usecase(x, y):
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return pow(x, y)
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def sum_usecase(x):
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return sum(x)
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def sum_kwarg_usecase(x, start=0):
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ret = sum(x, start)
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return sum(x, start=start), ret
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def isinstance_usecase(a):
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if isinstance(a, (int, float)):
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if isinstance(a, int):
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return a + 1, 'int'
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if isinstance(a, float):
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return a + 2.0, 'float'
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elif isinstance(a, str):
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return a + ", world!", 'str'
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elif isinstance(a, complex):
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return a.imag, 'complex'
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elif isinstance(a, (tuple, list)):
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if isinstance(a, tuple):
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return 'tuple'
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else:
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return 'list'
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elif isinstance(a, set):
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return 'set'
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elif isinstance(a, bytes):
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return 'bytes'
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return 'no match'
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def isinstance_dict():
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a = {1: 2, 3: 4}
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b = {'a': 10, 'b': np.zeros(3)}
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if isinstance(a, dict) and isinstance(b, dict):
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return 'dict'
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else:
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return 'not dict'
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def isinstance_usecase_numba_types(a):
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if isinstance(a, typed.List):
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return 'typed list'
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elif isinstance(a, (types.int32, types.int64)):
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if isinstance(a, types.int32):
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return 'int32'
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else:
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return 'int64'
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elif isinstance(a, (types.float32, types.float64)):
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if isinstance(a, types.float32):
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return 'float32'
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elif isinstance(a, types.float64):
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return 'float64'
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elif isinstance(a, typed.Dict):
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return 'typed dict'
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else:
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return 'no match'
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def isinstance_usecase_numba_types_2():
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# some types cannot be passed as argument to njit functions
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a = b'hello'
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b = range(1, 2)
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c = dict()
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c[2] = 3
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if isinstance(a, bytes) and \
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isinstance(b, range) and \
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isinstance(c, dict):
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return True
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return False
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def invalid_isinstance_usecase(x):
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if isinstance(x, ('foo',)):
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return 'true branch'
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else:
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return 'false branch'
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def isinstance_usecase_invalid_type(x):
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# this should be a valid call when x := float
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if isinstance(x, (float, 'not a type')):
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return True
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else:
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return False
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def invalid_isinstance_usecase_phi_nopropagate(x):
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if x > 4:
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z = 10
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else:
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z = 'a'
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if isinstance(z, int):
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return True
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else:
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return False
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def invalid_isinstance_usecase_phi_nopropagate2(a):
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# Numba issue #9125
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x = 0
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if isinstance(a, int):
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a = (a, a)
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for i in range(len(a)):
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x += i
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return x
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def invalid_isinstance_optional_usecase(x):
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if x > 4:
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z = 10
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else:
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z = None
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if isinstance(z, int):
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return True
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else:
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return False
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def invalid_isinstance_unsupported_type_usecase():
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ntpl = namedtuple('ntpl', ['a', 'b'])
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inst = ntpl(1, 2)
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def impl(x):
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return isinstance(inst, ntpl)
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return impl
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class TestBuiltins(TestCase):
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def run_nullary_func(self, pyfunc, flags):
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cfunc = jit((), **flags)(pyfunc)
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expected = pyfunc()
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self.assertPreciseEqual(cfunc(), expected)
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def test_abs(self, flags=forceobj_flags):
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pyfunc = abs_usecase
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cfunc = jit((types.int32,), **flags)(pyfunc)
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for x in [-1, 0, 1]:
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self.assertPreciseEqual(cfunc(x), pyfunc(x))
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cfunc = jit((types.float32,), **flags)(pyfunc)
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for x in [-1.1, 0.0, 1.1]:
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self.assertPreciseEqual(cfunc(x), pyfunc(x), prec='single')
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complex_values = [-1.1 + 0.5j, 0.0 + 0j, 1.1 + 3j,
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float('inf') + 1j * float('nan'),
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float('nan') - 1j * float('inf')]
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cfunc = jit((types.complex64,), **flags)(pyfunc)
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for x in complex_values:
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self.assertPreciseEqual(cfunc(x), pyfunc(x), prec='single')
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cfunc = jit((types.complex128,), **flags)(pyfunc)
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for x in complex_values:
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self.assertPreciseEqual(cfunc(x), pyfunc(x))
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for unsigned_type in types.unsigned_domain:
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unsigned_values = [0, 10, 2, 2 ** unsigned_type.bitwidth - 1]
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cfunc = jit((unsigned_type,), **flags)(pyfunc)
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for x in unsigned_values:
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self.assertPreciseEqual(cfunc(x), pyfunc(x))
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def test_abs_npm(self):
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self.test_abs(flags=no_pyobj_flags)
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def test_all(self, flags=forceobj_flags):
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pyfunc = all_usecase
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cfunc = jit((types.int32,types.int32), **flags)(pyfunc)
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x_operands = [-1, 0, 1, None]
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y_operands = [-1, 0, 1, None]
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for x, y in itertools.product(x_operands, y_operands):
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self.assertPreciseEqual(cfunc(x, y), pyfunc(x, y))
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def test_all_npm(self):
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with self.assertTypingError():
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self.test_all(flags=no_pyobj_flags)
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def test_any(self, flags=forceobj_flags):
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pyfunc = any_usecase
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cfunc = jit((types.int32,types.int32), **flags)(pyfunc)
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x_operands = [-1, 0, 1, None]
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y_operands = [-1, 0, 1, None]
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for x, y in itertools.product(x_operands, y_operands):
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self.assertPreciseEqual(cfunc(x, y), pyfunc(x, y))
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def test_any_npm(self):
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with self.assertTypingError():
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self.test_any(flags=no_pyobj_flags)
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def test_bool(self, flags=forceobj_flags):
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pyfunc = bool_usecase
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cfunc = jit((types.int32,), **flags)(pyfunc)
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for x in [-1, 0, 1]:
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self.assertPreciseEqual(cfunc(x), pyfunc(x))
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cfunc = jit((types.float64,), **flags)(pyfunc)
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for x in [0.0, -0.0, 1.5, float('inf'), float('nan')]:
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self.assertPreciseEqual(cfunc(x), pyfunc(x))
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cfunc = jit((types.complex128,), **flags)(pyfunc)
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for x in [complex(0, float('inf')), complex(0, float('nan'))]:
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self.assertPreciseEqual(cfunc(x), pyfunc(x))
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def test_bool_npm(self):
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self.test_bool(flags=no_pyobj_flags)
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def test_bool_nonnumber(self, flags=forceobj_flags):
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pyfunc = bool_usecase
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cfunc = jit((types.string,), **flags)(pyfunc)
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for x in ['x', '']:
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self.assertPreciseEqual(cfunc(x), pyfunc(x))
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cfunc = jit((types.Dummy('list'),), **flags)(pyfunc)
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for x in [[1], []]:
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self.assertPreciseEqual(cfunc(x), pyfunc(x))
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def test_bool_nonnumber_npm(self):
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with self.assertTypingError():
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self.test_bool_nonnumber(flags=no_pyobj_flags)
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def test_complex(self, flags=forceobj_flags):
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pyfunc = complex_usecase
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cfunc = jit((types.int32, types.int32), **flags)(pyfunc)
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x_operands = [-1, 0, 1]
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y_operands = [-1, 0, 1]
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for x, y in itertools.product(x_operands, y_operands):
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self.assertPreciseEqual(cfunc(x, y), pyfunc(x, y))
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def test_complex_npm(self):
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self.test_complex(flags=no_pyobj_flags)
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def test_divmod_ints(self, flags=forceobj_flags):
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pyfunc = divmod_usecase
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cfunc = jit((types.int64, types.int64), **flags)(pyfunc)
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def truncate_result(x, bits=64):
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# Remove any extraneous bits (since Numba will return
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# a 64-bit result by definition)
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if x >= 0:
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x &= (1 << (bits - 1)) - 1
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return x
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denominators = [1, 3, 7, 15, -1, -3, -7, -15, 2**63 - 1, -2**63]
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numerators = denominators + [0]
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for x, y, in itertools.product(numerators, denominators):
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expected_quot, expected_rem = pyfunc(x, y)
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quot, rem = cfunc(x, y)
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f = truncate_result
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self.assertPreciseEqual((f(quot), f(rem)),
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(f(expected_quot), f(expected_rem)))
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for x in numerators:
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with self.assertRaises(ZeroDivisionError):
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cfunc(x, 0)
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def test_divmod_ints_npm(self):
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self.test_divmod_ints(flags=no_pyobj_flags)
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def test_divmod_floats(self, flags=forceobj_flags):
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pyfunc = divmod_usecase
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cfunc = jit((types.float64, types.float64), **flags)(pyfunc)
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denominators = [1., 3.5, 1e100, -2., -7.5, -1e101,
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np.inf, -np.inf, np.nan]
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numerators = denominators + [-0.0, 0.0]
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for x, y, in itertools.product(numerators, denominators):
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expected_quot, expected_rem = pyfunc(x, y)
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quot, rem = cfunc(x, y)
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self.assertPreciseEqual((quot, rem), (expected_quot, expected_rem))
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|
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for x in numerators:
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with self.assertRaises(ZeroDivisionError):
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cfunc(x, 0.0)
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def test_divmod_floats_npm(self):
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self.test_divmod_floats(flags=no_pyobj_flags)
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def test_enumerate(self, flags=forceobj_flags):
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self.run_nullary_func(enumerate_usecase, flags)
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def test_enumerate_npm(self):
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self.test_enumerate(flags=no_pyobj_flags)
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def test_enumerate_start(self, flags=forceobj_flags):
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self.run_nullary_func(enumerate_start_usecase, flags)
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def test_enumerate_start_npm(self):
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self.test_enumerate_start(flags=no_pyobj_flags)
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def test_enumerate_start_invalid_start_type(self):
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pyfunc = enumerate_invalid_start_usecase
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cfunc = jit((), **forceobj_flags)(pyfunc)
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with self.assertRaises(TypeError) as raises:
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cfunc()
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msg = "'float' object cannot be interpreted as an integer"
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self.assertIn(msg, str(raises.exception))
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def test_enumerate_start_invalid_start_type_npm(self):
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pyfunc = enumerate_invalid_start_usecase
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with self.assertRaises(errors.TypingError) as raises:
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jit((), **no_pyobj_flags)(pyfunc)
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msg = "Only integers supported as start value in enumerate"
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self.assertIn(msg, str(raises.exception))
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|
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def test_filter(self, flags=forceobj_flags):
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pyfunc = filter_usecase
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argtys = (types.Dummy('list'), types.Dummy('function_ptr'))
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cfunc = jit(argtys, **flags)(pyfunc)
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|
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filter_func = lambda x: x % 2
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x = [0, 1, 2, 3, 4]
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self.assertSequenceEqual(list(cfunc(x, filter_func)),
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list(pyfunc(x, filter_func)))
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|
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def test_filter_npm(self):
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with self.assertTypingError():
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self.test_filter(flags=no_pyobj_flags)
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def test_float(self, flags=forceobj_flags):
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pyfunc = float_usecase
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cfunc = jit((types.int32,), **flags)(pyfunc)
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for x in [-1, 0, 1]:
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self.assertPreciseEqual(cfunc(x), pyfunc(x))
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|
|
cfunc = jit((types.float32,), **flags)(pyfunc)
|
|
for x in [-1.1, 0.0, 1.1]:
|
|
self.assertPreciseEqual(cfunc(x), pyfunc(x), prec='single')
|
|
|
|
cfunc = jit((types.string,), **flags)(pyfunc)
|
|
for x in ['-1.1', '0.0', '1.1']:
|
|
self.assertPreciseEqual(cfunc(x), pyfunc(x))
|
|
|
|
def test_float_npm(self):
|
|
with self.assertTypingError():
|
|
self.test_float(flags=no_pyobj_flags)
|
|
|
|
def test_format(self, flags=forceobj_flags):
|
|
pyfunc = format_usecase
|
|
|
|
cfunc = jit((types.string, types.int32,), **flags)(pyfunc)
|
|
x = '{0}'
|
|
for y in [-1, 0, 1]:
|
|
self.assertPreciseEqual(cfunc(x, y), pyfunc(x, y))
|
|
|
|
cfunc = jit((types.string, types.float32,), **flags)(pyfunc)
|
|
x = '{0}'
|
|
for y in [-1.1, 0.0, 1.1]:
|
|
self.assertPreciseEqual(cfunc(x, y), pyfunc(x, y))
|
|
|
|
cfunc = jit((types.string, types.string,), **flags)(pyfunc)
|
|
x = '{0}'
|
|
for y in ['a', 'b', 'c']:
|
|
self.assertPreciseEqual(cfunc(x, y), pyfunc(x, y))
|
|
|
|
def test_format_npm(self):
|
|
with self.assertTypingError():
|
|
self.test_format(flags=no_pyobj_flags)
|
|
|
|
def test_globals(self, flags=forceobj_flags):
|
|
pyfunc = globals_usecase
|
|
cfunc = jit((), **flags)(pyfunc)
|
|
g = cfunc()
|
|
self.assertIs(g, globals())
|
|
|
|
def test_globals_npm(self):
|
|
with self.assertTypingError():
|
|
self.test_globals(flags=no_pyobj_flags)
|
|
|
|
def test_globals_jit(self, flags=forceobj_flags):
|
|
# Issue #416: weird behaviour of globals() in combination with
|
|
# the @jit decorator.
|
|
pyfunc = globals_usecase
|
|
jitted = jit(**flags)(pyfunc)
|
|
self.assertIs(jitted(), globals())
|
|
self.assertIs(jitted(), globals())
|
|
|
|
def test_globals_jit_npm(self):
|
|
with self.assertTypingError():
|
|
self.test_globals_jit(nopython=True)
|
|
|
|
def test_hex(self, flags=forceobj_flags):
|
|
pyfunc = hex_usecase
|
|
|
|
cfunc = jit((types.int32,), **flags)(pyfunc)
|
|
for x in [-1, 0, 1]:
|
|
self.assertPreciseEqual(cfunc(x), pyfunc(x))
|
|
|
|
def test_hex_npm(self):
|
|
with self.assertTypingError():
|
|
self.test_hex(flags=no_pyobj_flags)
|
|
|
|
def test_int_str(self):
|
|
pyfunc = str_usecase
|
|
|
|
small_inputs = [
|
|
1234,
|
|
1,
|
|
0,
|
|
10,
|
|
1000,
|
|
]
|
|
|
|
large_inputs = [
|
|
123456789,
|
|
2222222,
|
|
1000000,
|
|
~0x0
|
|
]
|
|
|
|
args = [*small_inputs, *large_inputs]
|
|
|
|
typs = [
|
|
types.int8,
|
|
types.int16,
|
|
types.int32,
|
|
types.int64,
|
|
types.uint,
|
|
types.uint8,
|
|
types.uint16,
|
|
types.uint32,
|
|
types.uint64,
|
|
]
|
|
|
|
for typ in typs:
|
|
cfunc = jit((typ,), **nrt_no_pyobj_flags)(pyfunc)
|
|
for v in args:
|
|
self.assertPreciseEqual(cfunc(typ(v)), pyfunc(typ(v)))
|
|
|
|
if typ.signed:
|
|
self.assertPreciseEqual(cfunc(typ(-v)), pyfunc(typ(-v)))
|
|
|
|
def test_int(self, flags=forceobj_flags):
|
|
pyfunc = int_usecase
|
|
|
|
cfunc = jit((types.string, types.int32,), **flags)(pyfunc)
|
|
|
|
x_operands = ['-1', '0', '1', '10']
|
|
y_operands = [2, 8, 10, 16]
|
|
for x, y in itertools.product(x_operands, y_operands):
|
|
self.assertPreciseEqual(cfunc(x, y), pyfunc(x, y))
|
|
|
|
def test_int_npm(self):
|
|
with self.assertTypingError():
|
|
self.test_int(flags=no_pyobj_flags)
|
|
|
|
def test_iter_next(self, flags=forceobj_flags):
|
|
pyfunc = iter_next_usecase
|
|
cfunc = jit((types.UniTuple(types.int32, 3),), **flags)(pyfunc)
|
|
self.assertPreciseEqual(cfunc((1, 42, 5)), (1, 42))
|
|
|
|
cfunc = jit((types.UniTuple(types.int32, 1),), **flags)(pyfunc)
|
|
with self.assertRaises(StopIteration):
|
|
cfunc((1,))
|
|
|
|
def test_iter_next_npm(self):
|
|
self.test_iter_next(flags=no_pyobj_flags)
|
|
|
|
def test_locals(self, flags=forceobj_flags):
|
|
pyfunc = locals_usecase
|
|
with self.assertRaises(errors.ForbiddenConstruct):
|
|
jit((types.int64,), **flags)(pyfunc)
|
|
|
|
def test_locals_forceobj(self):
|
|
self.test_locals(flags=forceobj_flags)
|
|
|
|
def test_locals_npm(self):
|
|
with self.assertTypingError():
|
|
self.test_locals(flags=no_pyobj_flags)
|
|
|
|
def test_map(self, flags=forceobj_flags):
|
|
pyfunc = map_usecase
|
|
argtys = (types.Dummy('list'), types.Dummy('function_ptr'))
|
|
cfunc = jit(argtys, **flags)(pyfunc)
|
|
|
|
map_func = lambda x: x * 2
|
|
x = [0, 1, 2, 3, 4]
|
|
self.assertSequenceEqual(list(cfunc(x, map_func)),
|
|
list(pyfunc(x, map_func)))
|
|
|
|
def test_map_npm(self):
|
|
with self.assertTypingError():
|
|
self.test_map(flags=no_pyobj_flags)
|
|
|
|
#
|
|
# min() and max()
|
|
#
|
|
|
|
def check_minmax_1(self, pyfunc, flags):
|
|
cfunc = jit((types.int32, types.int32), **flags)(pyfunc)
|
|
|
|
x_operands = [-1, 0, 1]
|
|
y_operands = [-1, 0, 1]
|
|
for x, y in itertools.product(x_operands, y_operands):
|
|
self.assertPreciseEqual(cfunc(x, y), pyfunc(x, y))
|
|
|
|
def test_max_1(self, flags=forceobj_flags):
|
|
"""
|
|
max(*args)
|
|
"""
|
|
self.check_minmax_1(max_usecase1, flags)
|
|
|
|
def test_min_1(self, flags=forceobj_flags):
|
|
"""
|
|
min(*args)
|
|
"""
|
|
self.check_minmax_1(min_usecase1, flags)
|
|
|
|
def test_max_npm_1(self):
|
|
self.test_max_1(flags=no_pyobj_flags)
|
|
|
|
def test_min_npm_1(self):
|
|
self.test_min_1(flags=no_pyobj_flags)
|
|
|
|
def check_minmax_2(self, pyfunc, flags):
|
|
cfunc = jit((types.int32, types.int32), **flags)(pyfunc)
|
|
|
|
x_operands = [-1, 0, 1]
|
|
y_operands = [-1, 0, 1]
|
|
for x, y in itertools.product(x_operands, y_operands):
|
|
self.assertPreciseEqual(cfunc(x, y), pyfunc(x, y))
|
|
|
|
def test_max_2(self, flags=forceobj_flags):
|
|
"""
|
|
max(list)
|
|
"""
|
|
self.check_minmax_2(max_usecase2, flags)
|
|
|
|
def test_min_2(self, flags=forceobj_flags):
|
|
"""
|
|
min(list)
|
|
"""
|
|
self.check_minmax_2(min_usecase2, flags)
|
|
|
|
def test_max_npm_2(self):
|
|
with self.assertTypingError():
|
|
self.test_max_2(flags=no_pyobj_flags)
|
|
|
|
def test_min_npm_2(self):
|
|
with self.assertTypingError():
|
|
self.test_min_2(flags=no_pyobj_flags)
|
|
|
|
def check_minmax_3(self, pyfunc, flags):
|
|
def check(argty):
|
|
cfunc = jit((argty,), **flags)(pyfunc)
|
|
# Check that the algorithm matches Python's with a non-total order
|
|
tup = (1.5, float('nan'), 2.5)
|
|
for val in [tup, tup[::-1]]:
|
|
self.assertPreciseEqual(cfunc(val), pyfunc(val))
|
|
|
|
check(types.UniTuple(types.float64, 3))
|
|
check(types.Tuple((types.float32, types.float64, types.float32)))
|
|
|
|
def test_max_3(self, flags=forceobj_flags):
|
|
"""
|
|
max(tuple)
|
|
"""
|
|
self.check_minmax_3(max_usecase3, flags)
|
|
|
|
def test_min_3(self, flags=forceobj_flags):
|
|
"""
|
|
min(tuple)
|
|
"""
|
|
self.check_minmax_3(min_usecase3, flags)
|
|
|
|
def test_max_npm_3(self):
|
|
self.test_max_3(flags=no_pyobj_flags)
|
|
|
|
def test_min_npm_3(self):
|
|
self.test_min_3(flags=no_pyobj_flags)
|
|
|
|
def check_min_max_invalid_types(self, pyfunc, flags=forceobj_flags):
|
|
cfunc = jit((types.int32, types.Dummy('list'),), **flags)(pyfunc)
|
|
cfunc(1, [1])
|
|
|
|
def test_max_1_invalid_types(self):
|
|
with self.assertRaises(TypeError):
|
|
self.check_min_max_invalid_types(max_usecase1)
|
|
|
|
def test_max_1_invalid_types_npm(self):
|
|
with self.assertTypingError():
|
|
self.check_min_max_invalid_types(max_usecase1, flags=no_pyobj_flags)
|
|
|
|
def test_min_1_invalid_types(self):
|
|
with self.assertRaises(TypeError):
|
|
self.check_min_max_invalid_types(min_usecase1)
|
|
|
|
def test_min_1_invalid_types_npm(self):
|
|
with self.assertTypingError():
|
|
self.check_min_max_invalid_types(min_usecase1, flags=no_pyobj_flags)
|
|
|
|
def check_minmax_bool1(self, pyfunc, flags):
|
|
cfunc = jit((types.bool_, types.bool_), **flags)(pyfunc)
|
|
|
|
operands = (False, True)
|
|
for x, y in itertools.product(operands, operands):
|
|
self.assertPreciseEqual(cfunc(x, y), pyfunc(x, y))
|
|
|
|
def test_max_bool1(self, flags=forceobj_flags):
|
|
# tests max(<booleans>)
|
|
self.check_minmax_bool1(max_usecase1, flags)
|
|
|
|
def test_min_bool1(self, flags=forceobj_flags):
|
|
# tests min(<booleans>)
|
|
self.check_minmax_bool1(min_usecase1, flags)
|
|
|
|
# Test that max(1) and min(1) fail
|
|
|
|
def check_min_max_unary_non_iterable(self, pyfunc, flags=forceobj_flags):
|
|
cfunc = jit((types.int32,), **flags)(pyfunc)
|
|
cfunc(1)
|
|
|
|
def test_max_unary_non_iterable(self):
|
|
with self.assertRaises(TypeError):
|
|
self.check_min_max_unary_non_iterable(max_usecase3)
|
|
|
|
def test_max_unary_non_iterable_npm(self):
|
|
with self.assertTypingError():
|
|
self.check_min_max_unary_non_iterable(max_usecase3)
|
|
|
|
def test_min_unary_non_iterable(self):
|
|
with self.assertRaises(TypeError):
|
|
self.check_min_max_unary_non_iterable(min_usecase3)
|
|
|
|
def test_min_unary_non_iterable_npm(self):
|
|
with self.assertTypingError():
|
|
self.check_min_max_unary_non_iterable(min_usecase3)
|
|
|
|
# Test that max(()) and min(()) fail
|
|
|
|
def check_min_max_empty_tuple(self, pyfunc, func_name):
|
|
with self.assertTypingError() as raises:
|
|
jit((), **no_pyobj_flags)(pyfunc)
|
|
self.assertIn("%s() argument is an empty tuple" % func_name,
|
|
str(raises.exception))
|
|
|
|
def test_max_empty_tuple(self):
|
|
self.check_min_max_empty_tuple(max_usecase4, "max")
|
|
|
|
def test_min_empty_tuple(self):
|
|
self.check_min_max_empty_tuple(min_usecase4, "min")
|
|
|
|
|
|
def test_oct(self, flags=forceobj_flags):
|
|
pyfunc = oct_usecase
|
|
|
|
cfunc = jit((types.int32,), **flags)(pyfunc)
|
|
for x in [-8, -1, 0, 1, 8]:
|
|
self.assertPreciseEqual(cfunc(x), pyfunc(x))
|
|
|
|
def test_oct_npm(self):
|
|
with self.assertTypingError():
|
|
self.test_oct(flags=no_pyobj_flags)
|
|
|
|
def test_reduce(self, flags=forceobj_flags):
|
|
pyfunc = reduce_usecase
|
|
argtys = (types.Dummy('function_ptr'), types.Dummy('list'))
|
|
cfunc = jit(argtys, **flags)(pyfunc)
|
|
|
|
reduce_func = lambda x, y: x + y
|
|
|
|
x = range(10)
|
|
self.assertPreciseEqual(cfunc(reduce_func, x), pyfunc(reduce_func, x))
|
|
|
|
x = [x + x/10.0 for x in range(10)]
|
|
self.assertPreciseEqual(cfunc(reduce_func, x), pyfunc(reduce_func, x))
|
|
|
|
x = [complex(x, x) for x in range(10)]
|
|
self.assertPreciseEqual(cfunc(reduce_func, x), pyfunc(reduce_func, x))
|
|
|
|
def test_reduce_npm(self):
|
|
with self.assertTypingError():
|
|
self.test_reduce(flags=no_pyobj_flags)
|
|
|
|
def test_round1(self, flags=forceobj_flags):
|
|
pyfunc = round_usecase1
|
|
|
|
for tp in (types.float64, types.float32):
|
|
cfunc = jit((tp,), **flags)(pyfunc)
|
|
values = [-1.6, -1.5, -1.4, -0.5, 0.0, 0.1, 0.5, 0.6, 1.4, 1.5, 5.0]
|
|
values += [-0.1, -0.0]
|
|
for x in values:
|
|
self.assertPreciseEqual(cfunc(x), pyfunc(x))
|
|
|
|
def test_round1_npm(self):
|
|
self.test_round1(flags=no_pyobj_flags)
|
|
|
|
def test_round2(self, flags=forceobj_flags):
|
|
pyfunc = round_usecase2
|
|
|
|
for tp in (types.float64, types.float32):
|
|
prec = 'single' if tp is types.float32 else 'exact'
|
|
cfunc = jit((tp, types.int32), **flags)(pyfunc)
|
|
for x in [0.0, 0.1, 0.125, 0.25, 0.5, 0.75, 1.25,
|
|
1.5, 1.75, 2.25, 2.5, 2.75, 12.5, 15.0, 22.5]:
|
|
for n in (-1, 0, 1, 2):
|
|
self.assertPreciseEqual(cfunc(x, n), pyfunc(x, n),
|
|
prec=prec)
|
|
expected = pyfunc(-x, n)
|
|
self.assertPreciseEqual(cfunc(-x, n), pyfunc(-x, n),
|
|
prec=prec)
|
|
|
|
def test_round2_npm(self):
|
|
self.test_round2(flags=no_pyobj_flags)
|
|
|
|
def test_sum_objmode(self, flags=forceobj_flags):
|
|
pyfunc = sum_usecase
|
|
|
|
cfunc = jit((types.Dummy('list'),), **flags)(pyfunc)
|
|
|
|
x = range(10)
|
|
self.assertPreciseEqual(cfunc(x), pyfunc(x))
|
|
|
|
x = [x + x/10.0 for x in range(10)]
|
|
self.assertPreciseEqual(cfunc(x), pyfunc(x))
|
|
|
|
x = [complex(x, x) for x in range(10)]
|
|
self.assertPreciseEqual(cfunc(x), pyfunc(x))
|
|
|
|
def test_sum(self):
|
|
# In Python 3.8+ "start" can be specified as a kwarg, so test that too
|
|
sum_default = njit(sum_usecase)
|
|
sum_kwarg = njit(sum_kwarg_usecase)
|
|
|
|
@njit
|
|
def sum_range(sz, start=0):
|
|
tmp = range(sz)
|
|
ret = sum(tmp, start)
|
|
return sum(tmp, start=start), ret
|
|
|
|
ntpl = namedtuple('ntpl', ['a', 'b'])
|
|
|
|
# check call with default kwarg, start=0
|
|
def args():
|
|
yield [*range(10)]
|
|
yield [x + x/10.0 for x in range(10)]
|
|
yield [x * 1j for x in range(10)]
|
|
yield (1, 2, 3)
|
|
yield (1, 2, 3j)
|
|
# uints will likely end up as floats as `start` is signed, so just
|
|
# test mixed signed ints
|
|
yield (np.int64(32), np.int32(2), np.int8(3))
|
|
tl = typed.List(range(5))
|
|
yield tl
|
|
yield np.ones(5)
|
|
yield ntpl(100, 200)
|
|
yield ntpl(100, 200j)
|
|
|
|
for x in args():
|
|
self.assertPreciseEqual(sum_default(x), sum_default.py_func(x))
|
|
|
|
# Check the uint use case, as start is signed, NumPy will end up with
|
|
# a float result whereas Numba will end up with an int (see integer
|
|
# typing NBEP).
|
|
x = (np.uint64(32), np.uint32(2), np.uint8(3))
|
|
self.assertEqual(sum_default(x), sum_default.py_func(x))
|
|
|
|
# check call with changing default kwarg, start
|
|
def args_kws():
|
|
yield [*range(10)], 12
|
|
yield [x + x/10.0 for x in range(10)], 19j
|
|
yield [x * 1j for x in range(10)], -2
|
|
yield (1, 2, 3), 9
|
|
yield (1, 2, 3j), -0
|
|
# uints will likely end up as floats as `start` is signed, so just
|
|
# test mixed signed ints
|
|
yield (np.int64(32), np.int32(2), np.int8(3)), np.uint32(7)
|
|
tl = typed.List(range(5))
|
|
yield tl, 100
|
|
yield np.ones((5, 5)), 10 * np.ones((5,))
|
|
yield ntpl(100, 200), -50
|
|
yield ntpl(100, 200j), 9
|
|
|
|
for x, start in args_kws():
|
|
self.assertPreciseEqual(sum_kwarg(x, start=start),
|
|
sum_kwarg.py_func(x, start=start))
|
|
|
|
# check call with range()
|
|
for start in range(-3, 4):
|
|
for sz in range(-3, 4):
|
|
self.assertPreciseEqual(sum_range(sz, start=start),
|
|
sum_range.py_func(sz, start=start))
|
|
|
|
def test_sum_exceptions(self):
|
|
sum_default = njit(sum_usecase)
|
|
sum_kwarg = njit(sum_kwarg_usecase)
|
|
|
|
# check start as string/bytes/bytearray is error
|
|
msg = "sum() can't sum {}"
|
|
|
|
with self.assertRaises(errors.TypingError) as raises:
|
|
sum_kwarg((1, 2, 3), 'a')
|
|
|
|
self.assertIn(msg.format('strings'), str(raises.exception))
|
|
|
|
with self.assertRaises(errors.TypingError) as raises:
|
|
sum_kwarg((1, 2, 3), b'123')
|
|
|
|
self.assertIn(msg.format('bytes'), str(raises.exception))
|
|
|
|
with self.assertRaises(errors.TypingError) as raises:
|
|
sum_kwarg((1, 2, 3), bytearray(b'123'))
|
|
|
|
self.assertIn(msg.format('bytearray'), str(raises.exception))
|
|
|
|
# check invalid type has no impl
|
|
with self.assertRaises(errors.TypingError) as raises:
|
|
sum_default('abcd')
|
|
|
|
self.assertIn('No implementation', str(raises.exception))
|
|
|
|
def test_truth(self):
|
|
pyfunc = truth_usecase
|
|
cfunc = jit(nopython=True)(pyfunc)
|
|
|
|
self.assertEqual(pyfunc(True), cfunc(True))
|
|
self.assertEqual(pyfunc(False), cfunc(False))
|
|
|
|
def test_type_unary(self):
|
|
# Test type(val) and type(val)(other_val)
|
|
pyfunc = type_unary_usecase
|
|
cfunc = jit(nopython=True)(pyfunc)
|
|
|
|
def check(*args):
|
|
expected = pyfunc(*args)
|
|
self.assertPreciseEqual(cfunc(*args), expected)
|
|
|
|
check(1.5, 2)
|
|
check(1, 2.5)
|
|
check(1.5j, 2)
|
|
check(True, 2)
|
|
check(2.5j, False)
|
|
|
|
def test_zip(self, flags=forceobj_flags):
|
|
self.run_nullary_func(zip_usecase, flags)
|
|
|
|
def test_zip_npm(self):
|
|
self.test_zip(flags=no_pyobj_flags)
|
|
|
|
def test_zip_1(self, flags=forceobj_flags):
|
|
self.run_nullary_func(zip_1_usecase, flags)
|
|
|
|
def test_zip_1_npm(self):
|
|
self.test_zip_1(flags=no_pyobj_flags)
|
|
|
|
def test_zip_3(self, flags=forceobj_flags):
|
|
self.run_nullary_func(zip_3_usecase, flags)
|
|
|
|
def test_zip_3_npm(self):
|
|
self.test_zip_3(flags=no_pyobj_flags)
|
|
|
|
def test_zip_0(self, flags=forceobj_flags):
|
|
self.run_nullary_func(zip_0_usecase, flags)
|
|
|
|
def test_zip_0_npm(self):
|
|
self.test_zip_0(flags=no_pyobj_flags)
|
|
|
|
def test_zip_first_exhausted(self, flags=forceobj_flags):
|
|
"""
|
|
Test side effect to the input iterators when a left iterator has been
|
|
exhausted before the ones on the right.
|
|
"""
|
|
self.run_nullary_func(zip_first_exhausted, flags)
|
|
|
|
def test_zip_first_exhausted_npm(self):
|
|
self.test_zip_first_exhausted(flags=nrt_no_pyobj_flags)
|
|
|
|
def test_pow_op_usecase(self):
|
|
args = [
|
|
(2, 3),
|
|
(2.0, 3),
|
|
(2, 3.0),
|
|
(2j, 3.0j),
|
|
]
|
|
|
|
for x, y in args:
|
|
argtys = (typeof(x), typeof(y))
|
|
cfunc = jit(argtys, **no_pyobj_flags)(pow_op_usecase)
|
|
r = cfunc(x, y)
|
|
self.assertPreciseEqual(r, pow_op_usecase(x, y))
|
|
|
|
def test_pow_usecase(self):
|
|
args = [
|
|
(2, 3),
|
|
(2.0, 3),
|
|
(2, 3.0),
|
|
(2j, 3.0j),
|
|
]
|
|
|
|
for x, y in args:
|
|
argtys = (typeof(x), typeof(y))
|
|
cfunc = jit(argtys, **no_pyobj_flags)(pow_usecase)
|
|
r = cfunc(x, y)
|
|
self.assertPreciseEqual(r, pow_usecase(x, y))
|
|
|
|
def _check_min_max(self, pyfunc):
|
|
cfunc = njit()(pyfunc)
|
|
expected = pyfunc()
|
|
got = cfunc()
|
|
self.assertPreciseEqual(expected, got)
|
|
|
|
def test_min_max_iterable_input(self):
|
|
|
|
@njit
|
|
def frange(start, stop, step):
|
|
i = start
|
|
while i < stop:
|
|
yield i
|
|
i += step
|
|
|
|
def sample_functions(op):
|
|
yield lambda: op(range(10))
|
|
yield lambda: op(range(4, 12))
|
|
yield lambda: op(range(-4, -15, -1))
|
|
yield lambda: op([6.6, 5.5, 7.7])
|
|
yield lambda: op([(3, 4), (1, 2)])
|
|
yield lambda: op(frange(1.1, 3.3, 0.1))
|
|
yield lambda: op([np.nan, -np.inf, np.inf, np.nan])
|
|
yield lambda: op([(3,), (1,), (2,)])
|
|
|
|
for fn in sample_functions(op=min):
|
|
self._check_min_max(fn)
|
|
|
|
for fn in sample_functions(op=max):
|
|
self._check_min_max(fn)
|
|
|
|
|
|
class TestOperatorMixedTypes(TestCase):
|
|
|
|
def test_eq_ne(self):
|
|
for opstr in ('eq', 'ne'):
|
|
op = getattr(operator, opstr)
|
|
|
|
@njit
|
|
def func(a, b):
|
|
return op(a, b)
|
|
|
|
# all these things should evaluate to being equal or not, all should
|
|
# survive typing.
|
|
things = (1, 0, True, False, 1.0, 2.0, 1.1, 1j, None, "", "1")
|
|
for x, y in itertools.product(things, things):
|
|
self.assertPreciseEqual(func.py_func(x, y), func(x, y))
|
|
|
|
def test_cmp(self):
|
|
for opstr in ('gt', 'lt', 'ge', 'le', 'eq', 'ne'):
|
|
op = getattr(operator, opstr)
|
|
@njit
|
|
def func(a, b):
|
|
return op(a, b)
|
|
|
|
# numerical things should all be comparable
|
|
things = (1, 0, True, False, 1.0, 0.0, 1.1)
|
|
for x, y in itertools.product(things, things):
|
|
expected = func.py_func(x, y)
|
|
got = func(x, y)
|
|
message = ("%s %s %s does not match between Python and Numba"
|
|
% (x, opstr, y))
|
|
self.assertEqual(expected, got, message)
|
|
|
|
|
|
class TestIsinstanceBuiltin(TestCase):
|
|
def test_isinstance(self):
|
|
pyfunc = isinstance_usecase
|
|
cfunc = jit(nopython=True)(pyfunc)
|
|
|
|
inputs = (
|
|
3, # int
|
|
5.0, # float
|
|
"Hello", # string
|
|
b'world', # bytes
|
|
1j, # complex
|
|
[1, 2, 3], # list
|
|
(1, 3, 3, 3), # UniTuple
|
|
set([1, 2]), # set
|
|
(1, 'nba', 2), # Heterogeneous Tuple
|
|
# {'hello': 2}, # dict - doesn't work as input
|
|
None,
|
|
)
|
|
|
|
for inpt in inputs:
|
|
expected = pyfunc(inpt)
|
|
got = cfunc(inpt)
|
|
self.assertEqual(expected, got)
|
|
|
|
def test_isinstance_dict(self):
|
|
# Tests typed.Dict and LiteralStrKeyDict
|
|
pyfunc = isinstance_dict
|
|
cfunc = jit(nopython=True)(pyfunc)
|
|
self.assertEqual(pyfunc(), cfunc())
|
|
|
|
def test_isinstance_issue9125(self):
|
|
pyfunc = invalid_isinstance_usecase_phi_nopropagate2
|
|
cfunc = jit(nopython=True)(pyfunc)
|
|
self.assertEqual(pyfunc(3), cfunc(3))
|
|
|
|
def test_isinstance_numba_types(self):
|
|
# This makes use of type aliasing between python scalars and NumPy
|
|
# scalars, see also test_numba_types()
|
|
pyfunc = isinstance_usecase_numba_types
|
|
cfunc = jit(nopython=True)(pyfunc)
|
|
|
|
inputs = (
|
|
(types.int32(1), 'int32'),
|
|
(types.int64(2), 'int64'),
|
|
(types.float32(3.0), 'float32'),
|
|
(types.float64(4.0), 'float64'),
|
|
(types.complex64(5j), 'no match'),
|
|
(typed.List([1, 2]), 'typed list'),
|
|
(typed.Dict.empty(types.int64, types.int64), 'typed dict')
|
|
)
|
|
|
|
for inpt, expected in inputs:
|
|
got = cfunc(inpt)
|
|
self.assertEqual(expected, got)
|
|
|
|
def test_isinstance_numba_types_2(self):
|
|
pyfunc = isinstance_usecase_numba_types_2
|
|
cfunc = jit(nopython=True)(pyfunc)
|
|
self.assertEqual(pyfunc(), cfunc())
|
|
|
|
def test_isinstance_invalid_type(self):
|
|
pyfunc = isinstance_usecase_invalid_type
|
|
cfunc = jit(nopython=True)(pyfunc)
|
|
|
|
# valid type
|
|
self.assertTrue(cfunc(3.4))
|
|
|
|
# invalid type
|
|
msg = 'Cannot infer numba type of python type'
|
|
|
|
with self.assertRaises(errors.TypingError) as raises:
|
|
cfunc(100)
|
|
|
|
self.assertIn(msg, str(raises.exception))
|
|
|
|
def test_isinstance_exceptions(self):
|
|
fns = [
|
|
(invalid_isinstance_usecase,
|
|
'Cannot infer numba type of python type'),
|
|
(invalid_isinstance_usecase_phi_nopropagate,
|
|
('isinstance() cannot determine the type of variable "z" due to a '
|
|
'branch.')),
|
|
(invalid_isinstance_optional_usecase,
|
|
('isinstance() cannot determine the type of variable "z" due to a '
|
|
'branch.')),
|
|
(invalid_isinstance_unsupported_type_usecase(),
|
|
('isinstance() does not support variables of type "ntpl(')),
|
|
]
|
|
|
|
for fn, msg in fns:
|
|
fn = njit(fn)
|
|
|
|
with self.assertRaises(errors.TypingError) as raises:
|
|
fn(100)
|
|
|
|
self.assertIn(msg, str(raises.exception))
|
|
|
|
def test_combinations(self):
|
|
# Combinatorically test common classes and instances
|
|
def gen_w_arg(clazz_type):
|
|
def impl(x):
|
|
return isinstance(x, clazz_type)
|
|
return impl
|
|
|
|
clazz_types = (int, float, complex, str, list, tuple, bytes, set, range,
|
|
np.int8, np.float32,)
|
|
instances = (1, 2.3, 4j, '5', [6,], (7,), b'8', {9,}, None,
|
|
(10, 11, 12), (13, 'a', 14j), np.array([15, 16, 17]),
|
|
np.int8(18), np.float32(19),
|
|
typed.Dict.empty(types.unicode_type, types.float64),
|
|
typed.List.empty_list(types.complex128), np.ones(4))
|
|
|
|
for ct in clazz_types:
|
|
fn = njit(gen_w_arg(ct))
|
|
for x in instances:
|
|
expected = fn.py_func(x)
|
|
got = fn(x)
|
|
self.assertEqual(got, expected)
|
|
|
|
def test_numba_types(self):
|
|
# Check types which are Numba types, this would break without the jit
|
|
# decorator in all cases except numba.typed containers.
|
|
def gen_w_arg(clazz_type):
|
|
def impl():
|
|
return isinstance(1, clazz_type)
|
|
return impl
|
|
|
|
clazz_types = (types.Integer, types.Float, types.Array,)
|
|
|
|
msg = "Numba type classes.*are not supported"
|
|
for ct in clazz_types:
|
|
fn = njit(gen_w_arg(ct))
|
|
with self.assertRaises(errors.TypingError) as raises:
|
|
fn()
|
|
self.assertRegex(str(raises.exception), msg)
|
|
|
|
def test_python_numpy_scalar_alias_problem(self):
|
|
# There's a problem due to Python and NumPy scalars being aliased in the
|
|
# type system. This is because e.g. int scalar values and NumPy np.intp
|
|
# type alias to types.intp. This test merely records this fact.
|
|
|
|
@njit
|
|
def foo():
|
|
return isinstance(np.intp(10), int)
|
|
|
|
self.assertEqual(foo(), True)
|
|
self.assertEqual(foo.py_func(), False)
|
|
|
|
@njit
|
|
def bar():
|
|
return isinstance(1, np.intp)
|
|
|
|
self.assertEqual(bar(), True)
|
|
self.assertEqual(bar.py_func(), False)
|
|
|
|
def test_branch_prune(self):
|
|
# Check that isinstance branches are pruned allowing otherwise
|
|
# impossible type specific specialisation.
|
|
|
|
@njit
|
|
def foo(x):
|
|
if isinstance(x, str):
|
|
return x + 'some_string'
|
|
elif isinstance(x, complex):
|
|
return np.imag(x)
|
|
elif isinstance(x, tuple):
|
|
return len(x)
|
|
else:
|
|
assert 0
|
|
|
|
for x in ('string', 1 + 2j, ('a', 3, 4j)):
|
|
expected = foo.py_func(x)
|
|
got = foo(x)
|
|
self.assertEqual(got, expected)
|
|
|
|
|
|
class TestGetattrBuiltin(MemoryLeakMixin, TestCase):
|
|
# Tests the getattr() builtin
|
|
|
|
def test_getattr_func_retty(self):
|
|
|
|
@njit
|
|
def foo(x):
|
|
attr = getattr(x, '__hash__')
|
|
return attr()
|
|
|
|
for x in (1, 2.34, (5, 6, 7)):
|
|
self.assertPreciseEqual(foo(x), foo.py_func(x))
|
|
|
|
def test_getattr_value_retty(self):
|
|
|
|
@njit
|
|
def foo(x):
|
|
return getattr(x, 'ndim')
|
|
|
|
for x in range(3):
|
|
tmp = np.empty((1, ) * x)
|
|
self.assertPreciseEqual(foo(tmp), foo.py_func(tmp))
|
|
|
|
def test_getattr_module_obj(self):
|
|
# Consts on modules work ok
|
|
|
|
@njit
|
|
def foo():
|
|
return getattr(np, 'pi')
|
|
|
|
self.assertPreciseEqual(foo(), foo.py_func())
|
|
|
|
def test_getattr_module_obj_not_implemented(self):
|
|
# Functions on modules do not work at present
|
|
|
|
@njit
|
|
def foo():
|
|
return getattr(np, 'cos')(1)
|
|
|
|
with self.assertRaises(errors.TypingError) as raises:
|
|
foo()
|
|
|
|
msg = "Returning function objects is not implemented"
|
|
self.assertIn(msg, str(raises.exception))
|
|
|
|
def test_getattr_raises_attribute_error(self):
|
|
|
|
invalid_attr = '__not_a_valid_attr__'
|
|
|
|
@njit
|
|
def foo(x):
|
|
return getattr(x, invalid_attr)
|
|
|
|
with self.assertRaises(AttributeError) as raises:
|
|
foo(1.23)
|
|
|
|
self.assertIn(f"'float64' has no attribute '{invalid_attr}'",
|
|
str(raises.exception))
|
|
|
|
def test_getattr_with_default(self):
|
|
# Checks returning a default works
|
|
|
|
@njit
|
|
def foo(x, default):
|
|
return getattr(x, '__not_a_valid_attr__', default)
|
|
|
|
for x, y in zip((1, 2.34, (5, 6, 7),), (None, 20, 'some_string')):
|
|
self.assertPreciseEqual(foo(x, y), foo.py_func(x, y))
|
|
|
|
def test_getattr_non_literal_str(self):
|
|
|
|
@njit
|
|
def foo(x, nonliteral_str):
|
|
return getattr(x, nonliteral_str)
|
|
|
|
with self.assertRaises(errors.TypingError) as raises:
|
|
foo(1, '__hash__')
|
|
|
|
msg = "argument 'name' must be a literal string"
|
|
self.assertIn(msg, str(raises.exception))
|
|
|
|
def test_getattr_no_optional_type_generated(self):
|
|
|
|
@njit
|
|
def default_hash():
|
|
return 12345
|
|
|
|
@njit
|
|
def foo():
|
|
hash_func = getattr(np.ones(1), "__not_a_valid_attr__",
|
|
default_hash)
|
|
return hash_func() # Optionals have no call support
|
|
|
|
self.assertPreciseEqual(foo(), foo.py_func())
|
|
|
|
|
|
class TestHasattrBuiltin(MemoryLeakMixin, TestCase):
|
|
# Tests the hasattr() builtin
|
|
|
|
def test_hasattr(self):
|
|
|
|
@njit
|
|
def foo(x):
|
|
return hasattr(x, '__hash__'), hasattr(x, '__not_a_valid_attr__')
|
|
|
|
ty = types.int64
|
|
for x in (1, 2.34, (5, 6, 7), typed.Dict.empty(ty, ty),
|
|
typed.List.empty_list(ty), np.ones(4), 'ABC'):
|
|
self.assertPreciseEqual(foo(x), foo.py_func(x))
|
|
|
|
def test_hasattr_non_const_attr(self):
|
|
# This tests that an error is raised in the case that a hasattr() call
|
|
# is made on an attribute that cannot be resolved as a compile time
|
|
# constant (there's a phi in the way!).
|
|
|
|
@njit
|
|
def foo(pred):
|
|
if pred > 3:
|
|
attr = "__hash__"
|
|
else:
|
|
attr = "__str__"
|
|
|
|
hasattr(1, attr)
|
|
|
|
with self.assertRaises(errors.NumbaTypeError) as raises:
|
|
foo(6)
|
|
|
|
msg = ('hasattr() cannot determine the type of variable '
|
|
'"attr" due to a branch.')
|
|
self.assertIn(msg, str(raises.exception))
|
|
|
|
|
|
class TestStrAndReprBuiltin(MemoryLeakMixin, TestCase):
|
|
|
|
def test_str_default(self):
|
|
|
|
@njit
|
|
def foo():
|
|
return str()
|
|
|
|
self.assertEqual(foo(), foo.py_func())
|
|
|
|
def test_str_object_kwarg(self):
|
|
|
|
@njit
|
|
def foo(x):
|
|
return str(object=x)
|
|
|
|
value = "a string"
|
|
self.assertEqual(foo(value), foo.py_func(value))
|
|
|
|
def test_str_calls_dunder_str(self):
|
|
|
|
@njit
|
|
def foo(x):
|
|
return str(x)
|
|
|
|
Dummy, DummyType = self.make_dummy_type()
|
|
dummy = Dummy()
|
|
string_repr = "this is the dummy object str"
|
|
Dummy.__str__= lambda inst: string_repr
|
|
|
|
@overload_method(DummyType, "__str__")
|
|
def ol_dummy_string(dummy):
|
|
def impl(dummy):
|
|
return string_repr
|
|
return impl
|
|
|
|
@overload_method(DummyType, "__repr__")
|
|
def ol_dummy_repr(dummy):
|
|
def impl(dummy):
|
|
return "SHOULD NOT BE CALLED"
|
|
return impl
|
|
|
|
self.assertEqual(foo(dummy), foo.py_func(dummy))
|
|
|
|
def test_str_falls_back_to_repr(self):
|
|
|
|
@njit
|
|
def foo(x):
|
|
return str(x)
|
|
|
|
Dummy, DummyType = self.make_dummy_type()
|
|
dummy = Dummy()
|
|
string_repr = "this is the dummy object repr"
|
|
Dummy.__repr__= lambda inst: string_repr
|
|
|
|
@overload_method(DummyType, "__repr__")
|
|
def ol_dummy_repr(dummy):
|
|
def impl(dummy):
|
|
return string_repr
|
|
return impl
|
|
|
|
self.assertEqual(foo(dummy), foo.py_func(dummy))
|
|
|
|
def test_repr(self):
|
|
@njit
|
|
def foo(x):
|
|
return repr(x), x
|
|
|
|
for x in ("abc", False, 123):
|
|
self.assertEqual(foo(x), foo.py_func(x))
|
|
|
|
def test_repr_fallback(self):
|
|
# checks str/repr fallback, there's no overloaded __str__ or __repr__
|
|
# for the dummy type so it has to use generic '<object type:(type)>'
|
|
# string for the `repr` call.
|
|
|
|
Dummy, DummyType = self.make_dummy_type()
|
|
dummy = Dummy()
|
|
string_repr = f"<object type:{typeof(dummy)}>"
|
|
Dummy.__repr__= lambda inst: string_repr
|
|
|
|
@box(DummyType)
|
|
def box_dummy(typ, obj, c):
|
|
clazobj = c.pyapi.unserialize(c.pyapi.serialize_object(Dummy))
|
|
return c.pyapi.call_function_objargs(clazobj, ())
|
|
|
|
@njit
|
|
def foo(x):
|
|
return str(x)
|
|
|
|
self.assertEqual(foo(dummy), foo.py_func(dummy))
|
|
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|