o p i@sddlmZddlZddlmZmZmZmZmZddl m Z ddl Z ddl m Z ddlmZer6ddlmZed Ze d ZGd d d eZed'ddZed(d)ddZd*ddZ d*dddd+ddZ d*d,dd Zd-d%d&ZdS).) annotationsN) TYPE_CHECKINGCallableProtocolTypeVaroverload) ParamSpec)DYNAMIC_DIMS_ATTR_NAME)TransformOptions)Sequence_RetT_InputTc@s*eZdZed ddZed d ddZd S) _NotToStaticDecoratorfuncCallable[_InputT, _RetT]returncCdSNselfrrrX/home/app/PaddleOCR-VL/.venv_paddleocr/lib/python3.10/site-packages/paddle/jit/marker.py__call__(z_NotToStaticDecorator.__call__.NonecCrrrrrrrr-Nrrrr.rrrr)__name__ __module__ __qualname__rrrrrrr's  rrrrcCrrrrrrr not_to_static1rr$.rcCrrrr#rrrr$7rcCst|dddS)a A Decorator to suppresses the convention of a function. Args: func(callable): The function to decorate. Returns: callable: A function which won't be converted in Dynamic-to-Static. Examples: .. code-block:: python >>> # doctest: +SKIP('`paddle.jit.to_static` can not run in xdoctest') >>> import paddle >>> @paddle.jit.not_to_static ... def func_not_to_static(x): ... res = x - 1 ... return res >>> @paddle.jit.to_static ... def func(x): ... if paddle.mean(x) < 0: ... out = func_not_to_static(x) ... else: ... out = x + 1 ... return out ... >>> x = paddle.ones([1, 2], dtype='float32') >>> out = func(x) >>> print(out) Tensor(shape=[1, 2], dtype=float32, place=Place(cpu), stop_gradient=True, [[2., 2.]]) FTfor_sotfor_ast)unifiedr#rrrr$<s#Tr%fn7Callable[_InputT, _RetT] | type[paddle.nn.Layer] | Noner&boolr'cs0d dd|durfddS|d S) aV Mark a function already unified in dygraph and static mode. So that it won't be transformed again in SOT or AST mode. Args: fn(callable): The function to decorate. for_sot(bool): Whether to mark the function as unified in SOT mode. for_ast(bool): Whether to mark the function as unified in AST mode. r&r+r'cSsBtj}|r |tjjO}|r|tjjO}t|d}|||S)N)Zskip_transform_mode)r Z ToStaticModeZNilZSOTASTattach)r)r&r'modeoptionsrrr_mark_as_unifiedrs    z!unified.._mark_as_unifiedNcs|dS)Nr%r)r)r0r'r&rrszunified..r%)r&r+r'r+r)r)r&r'rr1rr(bs  r(cCshddlm}t|rt|tjjr|jj ||St |r)|jj ||St dt|jd)z Mark a function or paddle.nn.Layer to be executed in dynamic mode, it will break the graph and prevent it from being converted to static mode. r)sotz0Expected a callable or paddle.nn.Layer, but got .)Z paddle.jitr3inspectisclass issubclasspaddlennZLayerutilsZpaddle_api_configZadd_break_graph_layer_class isfunctionZadd_break_graph_function TypeErrortyper )r)r3rrr force_dynamics  r>tensor paddle.Tensordimsint | Sequence[int]cCsvt|tjstdt|jdt|tr|f}t|ttfs$tdt dd|Ds1tdt |t t|dS)as Mark a tensor as having dynamic dimensions. This is used to indicate that the tensor's shape may change dynamically during execution, which is particularly useful in dynamic-to-static conversion scenarios. Args: tensor (paddle.Tensor): The tensor to mark as dynamic. dims (int | Sequence[int]): The dimensions to mark as dynamic. z"Expected a paddle.Tensor, but got r4z#Dimensions must be a list or tuple.css|]}t|tVqdSr) isinstanceint).0dimrrr szdynamic_dims..z All dimensions must be integers.N) rCr8ZTensorr<r=r rDlisttupleallsetattrr )r?rArrr dynamic_dimss  rLrrrr)r)r*r&r+r'r+rr)r)r*rr)r?r@rArBrr) __future__rr5typingrrrrrZtyping_extensionsrr8Zpaddle.jit.dy2static.utilsr Zdy2static.utilsr collections.abcr r rrr$r(r>rLrrrrs2       '"