ai-content-maker/.venv/Lib/site-packages/numba/tests/test_copy_propagate.py

#
# Copyright (c) 2017 Intel Corporation
# SPDX-License-Identifier: BSD-2-Clause
#

from numba import jit, njit
from numba.core import types, ir, config, compiler
from numba.core.registry import cpu_target
from numba.core.annotations import type_annotations
from numba.core.ir_utils import (copy_propagate, apply_copy_propagate,
                            get_name_var_table)
from numba.core.typed_passes import type_inference_stage
from numba.tests.support import IRPreservingTestPipeline
import numpy as np
import unittest


def test_will_propagate(b, z, w):
    x = 3
    x1 = x
    if b > 0:
        y = z + w
    else:
        y = 0
    a = 2 * x1
    return a < b


def test_wont_propagate(b, z, w):
    x = 3
    if b > 0:
        y = z + w
        x = 1
    else:
        y = 0
    a = 2 * x
    return a < b


def null_func(a,b,c,d):
    False


def inListVar(list_var, var):
    for i in list_var:
        if i.name == var:
            return True
    return False


def findAssign(func_ir, var):
    for label, block in func_ir.blocks.items():
        for i, inst in enumerate(block.body):
            if isinstance(inst, ir.Assign) and inst.target.name!=var:
                all_var = inst.list_vars()
                if inListVar(all_var, var):
                    return True

    return False


class TestCopyPropagate(unittest.TestCase):
    def test1(self):
        typingctx = cpu_target.typing_context
        targetctx = cpu_target.target_context
        test_ir = compiler.run_frontend(test_will_propagate)
        typingctx.refresh()
        targetctx.refresh()
        args = (types.int64, types.int64, types.int64)
        typemap, return_type, calltypes, _ = type_inference_stage(typingctx,
                                                                    targetctx,
                                                                    test_ir,
                                                                    args,
                                                                    None)
        type_annotation = type_annotations.TypeAnnotation(
            func_ir=test_ir,
            typemap=typemap,
            calltypes=calltypes,
            lifted=(),
            lifted_from=None,
            args=args,
            return_type=return_type,
            html_output=config.HTML)
        in_cps, out_cps = copy_propagate(test_ir.blocks, typemap)
        apply_copy_propagate(test_ir.blocks, in_cps,
                                get_name_var_table(test_ir.blocks), typemap,
                                calltypes)

        self.assertFalse(findAssign(test_ir, "x1"))

    def test2(self):
        typingctx = cpu_target.typing_context
        targetctx = cpu_target.target_context
        test_ir = compiler.run_frontend(test_wont_propagate)
        typingctx.refresh()
        targetctx.refresh()
        args = (types.int64, types.int64, types.int64)
        typemap, return_type, calltypes, _ = type_inference_stage(typingctx,
                                                                    targetctx,
                                                                    test_ir,
                                                                    args,
                                                                    None)
        type_annotation = type_annotations.TypeAnnotation(
            func_ir=test_ir,
            typemap=typemap,
            calltypes=calltypes,
            lifted=(),
            lifted_from=None,
            args=args,
            return_type=return_type,
            html_output=config.HTML)
        in_cps, out_cps = copy_propagate(test_ir.blocks, typemap)
        apply_copy_propagate(test_ir.blocks, in_cps, get_name_var_table(test_ir.blocks), typemap, calltypes)

        self.assertTrue(findAssign(test_ir, "x"))

    def test_input_ir_extra_copies(self):
        """make sure Interpreter._remove_unused_temporaries() has removed extra copies
        in the IR in simple cases so copy propagation is faster
        """
        def test_impl(a):
            b = a + 3
            return b

        j_func = njit(pipeline_class=IRPreservingTestPipeline)(test_impl)
        self.assertEqual(test_impl(5), j_func(5))

        # make sure b is the target of the expression assignment, not a temporary
        fir = j_func.overloads[j_func.signatures[0]].metadata['preserved_ir']
        self.assertTrue(len(fir.blocks) == 1)
        block = next(iter(fir.blocks.values()))
        b_found = False
        for stmt in block.body:
            if isinstance(stmt, ir.Assign) and stmt.target.name == "b":
                b_found = True
                self.assertTrue(isinstance(stmt.value, ir.Expr)
                    and stmt.value.op == "binop" and stmt.value.lhs.name == "a")

        self.assertTrue(b_found)

    def test_input_ir_copy_remove_transform(self):
        """make sure Interpreter._remove_unused_temporaries() does not generate
        invalid code for rare chained assignment cases
        """
        # regular chained assignment
        def impl1(a):
            b = c = a + 1
            return (b, c)

        # chained assignment with setitem
        def impl2(A, i, a):
            b = A[i] = a + 1
            return b, A[i] + 2

        # chained assignment with setattr
        def impl3(A, a):
            b = A.a = a + 1
            return b, A.a + 2

        class C:
            pass

        self.assertEqual(impl1(5), njit(impl1)(5))
        self.assertEqual(impl2(np.ones(3), 0, 5), njit(impl2)(np.ones(3), 0, 5))
        self.assertEqual(impl3(C(), 5), jit(forceobj=True)(impl3)(C(), 5))


if __name__ == "__main__":
    unittest.main()