def load(self, filename, create_if_missing=True):
        filename = Path(filename)
        if not filename.exists() and create_if_missing:
            self.load_pip_requirements()
            with filename.open("w") as f:
                f.write(yaml.dump(self.serialized, default_flow_style=False,
                                  encoding=None))
            self.filename = filename
            return self.save(filename)
        with filename.open() as f:
            for group, requirements in yaml.load(f.read()).items():
                for requirement in requirements:
                    self[group].add(Requirement.coerce(requirement))
        self.filename = filename
def test_if_likely():
    ib = tvm.tir.ir_builder.create()
    A = ib.pointer("float32", name="A")
    C = ib.pointer("float32", name="C")
    n = te.size_var("n")
    tx = te.thread_axis("threadIdx.x")
    ty = te.thread_axis("threadIdx.y")
    ib.scope_attr(tx, "thread_extent", 32)
    ib.scope_attr(ty, "thread_extent", 32)
    with ib.if_scope(ib.likely(tx * 32 + ty < n)):
        with ib.if_scope(ib.likely(tx * 32 + ty < n)):
            A[tx] = C[tx * 32 + ty]
    body = ib.get()
    mod = tvm.IRModule.from_expr(tvm.tir.PrimFunc([A, C, n], body))
    body = tvm.tir.transform.Simplify()(mod)["main"].body
    assert isinstance(body.body.body, tvm.tir.IfThenElse)
    assert not isinstance(body.body.body.then_case, tvm.tir.IfThenElse)