zjO,GddZedZedZedZedZedZedZedZd Zd Z d Z d Z d Z dZ dZdZdZdZdZdZdZdZdS)c,eZdZdZddgZdZdZdZdS)RegistryzA general registry object.nametabc"||_i|_dSN)rrselfrs p/lsinfo/ai/hellotax_ai/data_center/backend/venv/lib/python3.11/site-packages/paddle/incubate/autograd/primreg.py__init__zRegistry.__init__s cH||jvsJd|d||j|<dS)Nzname "z"" should not be registered before.)r)r rvalues r registerzRegistry.registers<48### =T = = =$##r c6|j|Sr)rgetrs r lookupzRegistry.lookupsx||D!!!r N)__name__ __module__ __qualname____doc__ __slots__r rrr r rrsP$$I """""r r primop_fn orig2prim prim2orig primop_jvpprimop_transposeprimop_position_argnames compositec6t|Sr) _primop_fnroptypes r lookup_fnr$,   V $ $$r c6t|Sr) _orig2primrr"s r lookup_orig2primr(0r%r c6t|Sr) _prim2origrr"s r lookup_prim2origr+4r%r c6t|Sr) _primop_jvprr"s r lookup_jvpr.8s   f % %%r c6t|Sr)_primop_transposerr"s r lookup_transposer1<s  # #F + ++r c6t|Sr)_composite_opsrr"s r lookup_compositer4@s   ( ((r c t|j}|Jd|jd|^}}g}|D]}tt |jj||}t|dksJdt|dt|dkr| || |d|S)a4 Returns the position inputs of `op` as registered with REGISTER_FN. Args: op(Operator): The op that needs to get the inputs Returns: Tensor(s): Inputs of the op Examples: .. code-block:: python >>> from paddle.incubate.autograd.primops import _simple_binop >>> from paddle.base.layer_helper import LayerHelper >>> from paddle.incubate.autograd.primreg import REGISTER_FN >>> # doctest: +SKIP('Depends on external code.') >>> @REGISTER_FN('div_p', 'X', 'Y', 'Z') >>> def div(x, y, out=None): ... return _simple_binop(LayerHelper('div_p', **locals())) The registered inputs are ['X', 'Y'] for div_p and accordingly this function will return inputs in the order of X then Y. Nzargs of z, should not be None in op_position_inputs().z>len(vars) should be greater than or equal to 0, but len(vars)=.) _primop_position_argnamesrtypelistmapblockvarinputlenappend)opargs input_names_inputsrvarss r op_position_inputsrHDs4 % + +BG 4 4D   H27HHH   O[! F##C bhhtnn55664yyA~~~ YSQUYY Y Y Y~~ t99q== MM$     MM$q' " " " " Mr crt|j}| Jd|^}}tt |jj||}t|dksJdt|dt|dkr|}n|d}|S)a Returns the output of `op` as registered with REGISTER_FN. Args: op(Operator): The op that needs to get the output Returns: Tensor(s): Output of the op Examples: .. code-block:: python >>> # doctest: +SKIP('Depends on external code.') >>> from paddle.incubate.autograd.primops import _simple_binop >>> from paddle.base.layer_helper import LayerHelper >>> from paddle.incubate.autograd.primreg import REGISTER_FN >>> @REGISTER_FN('div_p', 'X', 'Y', 'Z') >>> def div(x, y, out=None): ... return _simple_binop(LayerHelper('div_p', **locals())) The registered output is ['Z'] for div_p and accordingly this function will return output Z. Nz0args should not be None in op_position_output().r6zDlen(outvars) should be greater than or equal to 0, but len(outvars)=r7r8) r9rr:r;r<r=r>outputr@)rBrCrE output_nameoutvarsrJs r op_position_outputrMrs4 % + +BG 4 4D   O   OQ 3rx|RYY{%;%;<<==G w<<1   ^sSZ||^^^    7||a Mr ctts tdtdt|fd}|S)a Decorator for registering the Python function for a primitive op. Args: op_type(str): The op name position_argnames(list[str]): Input and output names of the op Returns: wrapper: Inner wrapper function Examples: .. code-block:: python >>> # doctest: +SKIP('Depends on external code.') >>> from paddle.incubate.autograd.primops import _simple_binop >>> from paddle.base.layer_helper import LayerHelper >>> from paddle.incubate.autograd.primreg import REGISTER_FN >>> @REGISTER_FN('tanh_p', 'X', 'Y') >>> def tanh(x, out=None): ... return _simple_unop(LayerHelper('tanh_p', **locals())) op_type must be str, but got r7c>t||Sr)r!r)fop_types r wrapperzREGISTER_FN..wrappersGQ'''r ) isinstancestr TypeErrorr:r9r)rRposition_argnamesrSs` r REGISTER_FNrXso2 gs # #JHW HHHIII&&w0ABBB Nr c|tts tdtdfd}|S)a Decorator for registering the lower function for an original op into sequence of primitive ops. Args: op_type(str): The op name Returns: wrapper: Inner wrapper function Examples: .. code-block:: python >>> # doctest: +SKIP('Depends on external code.') >>> from paddle.base.layer_helper import LayerHelper >>> from paddle.incubate.autograd.utils import get_input_var_list >>> from paddle.incubate.autograd import primops >>> from paddle.incubate.autograd.primreg import REGISTER_ORIG2PRIM >>> @REGISTER_ORIG2PRIM('tanh') >>> def tanh_orig2prim(op): ... x, = get_input_var_list(op) ... return primops.tanh(x) rOr7cLfd}t|dS)Nc\|jksJd|jd|g|Ri|SNz3op.type should be equal to op_type, but op.type is z and op_type is r:rBrCkwargsrQrRs r _lowerz3REGISTER_ORIG2PRIM..wrapper.._lowerV7g%%%hbghh_fhh&%%1R)$)))&)) )r )r'rrQr`rRs` r rSz#REGISTER_ORIG2PRIM..wrapper@ * * * * * * GV,,,,,r rTrUrVr:rRrSs` r REGISTER_ORIG2PRIMrfsX2 gs # #JHW HHHIII----- Nr c|tts tdtdfd}|S)a Decorator for registering the lower function for an original op into sequence of primitive ops. Args: op_type(str): The op name Returns: wrapper: Inner wrapper function Examples: .. code-block:: python >>> # doctest: +SKIP('Depends on external code.') >>> import paddle >>> from paddle.incubate.autograd.primreg import REGISTER_COMPOSITE >>> @REGISTER_COMPOSITE('softmax') >>> def softmax_composite(x, axis): ... molecular = paddle.exp(x) ... denominator = paddle.broadcast_to(sum(molecular, axis=axis, keepdim=True), x.shape) ... res = paddle.divide(molecular, denominator) ... return res rOr7cLfd}t|dS)NcT|jksJd|jd|i|Sr\r]r^s r r`z3REGISTER_COMPOSITE..wrapper.._lowersK7g%%%hbghh_fhh&%%1d%f%% %r )r3rrbs` r rSz#REGISTER_COMPOSITE..wrappers@ & & & & & & 00000r rdres` r REGISTER_COMPOSITErjsX2 gs # #JHW HHHIII11111 Nr c|tts tdtdfd}|S)a Decorator for registering the lower function for an primitive op into sequence of original ops. Args: op_type(str): The op name Returns: wrapper: Inner wrapper function Examples: .. code-block:: python >>> # doctest: +SKIP('Depends on external code.') >>> import paddle >>> from paddle.incubate.autograd.primreg import REGISTER_PRIM2ORIG >>> from paddle.incubate.autograd.utils import get_input_var_list >>> @REGISTER_PRIM2ORIG('tanh_p') >>> def tanh_prim2orig(op): ... x, = get_input_var_list(op) ... return paddle.tanh(x) ... rOr7cLfd}t|dS)Nc\|jksJd|jd|g|Ri|Sr\r]r^s r r`z3REGISTER_PRIM2ORIG..wrapper.._lower-rar )r*rrbs` r rSz#REGISTER_PRIM2ORIG..wrapper,rcr rdres` r REGISTER_PRIM2ORIGrnsX0 gs # #JHW HHHIII----- Nr c|tts tdtdfd}|S)a, Decorator for registering the JVP function for a primitive op. Args: op_type(str): The op name Returns: wrapper: Inner wrapper function Examples: .. code-block:: python >>> # doctest: +SKIP('Depends on external code.') >>> from paddle.incubate.autograd import primops >>> from paddle.incubate.autograd.primreg import REGISTER_JVP >>> @REGISTER_JVP('add_p') >>> def add_jvp(op, x_dot, y_dot): ... return primops.add(x_dot, y_dot) rOr7cLfd}t|S)Nc\|jksJd|jd|g|Ri|Sr\r]r^s r _jvpz+REGISTER_JVP..wrapper.._jvpRrar )r-r)rQrrrRs` r rSzREGISTER_JVP..wrapperQs? * * * * * * Wd+++r rdres` r REGISTER_JVPrs8X, gs # #JHW HHHIII Nr c|tts tdtdfd}|S)a/ Decorator for registering the transpose function for a primitive op that denotes a linear operation in the forward AD graph. Args: op_type(str): The op name Returns: wrapper: Inner wrapper function Examples: .. code-block:: python >>> # doctest: +SKIP('Depends on external code.') >>> from paddle.incubate.autograd.primreg import REGISTER_TRANSPOSE >>> @REGISTER_TRANSPOSE('add_p') >>> def add_transpose(op, z_bar): ... return z_bar, z_bar rOr7cLfd}t|S)Nc^|jksJd|jd||g|Ri|Sr\r])rB dot_checkerrCr_rQrRs r _transposez7REGISTER_TRANSPOSE..wrapper.._transposexsX7g%%%hbghh_fhh&%%1R6t666v66 6r )r0r)rQryrRs` r rSz#REGISTER_TRANSPOSE..wrapperws? 7 7 7 7 7 7 ""7J777r rdres` r REGISTER_TRANSPOSErz^rtr N)rr!r'r*r-r0r9r3r$r(r+r.r1r4rHrMrXrfrjrnrsrzrr r r{s """"""""&Xk " " Xk " " Xk " " h|$$ H/00$H%?@@+&&%%%%%%%%%&&&,,,)))+++\'''T"""J%%%P%%%P$$$N###L#####r