Αi|SSKJr SSKrSSKrSSKrSSKrSSKrSSKrSSKrSSK J r SSK J r SSK rSSKrSSKJr SSKJr SSKJrJrJrJrJrJrJrJrJr SS KJrJrJ r J!r!J"r"J#r#J$r$ \ (aKSS K%J&r& SS K J'r'J(r(J)r) SS K*J+r+J,r, SS KJ-r- SSK.J/r/ SSK0J1r1 "SS\)5r2"SS\)5r3"SS\)5r4/r5/r6S3Sjr7S4S5Sjjr8Sr9Sr:Sr;SrSr?Sr@S rAS!rBS"rCS#rDS$rES%rFS&rGS'rHS(rIS)rJS*rKS+rLS,rMS-rNS6S7S.jjrOS/rPS8S0jrQS9S1jrRS2rSg):) annotationsN)Iterable) TYPE_CHECKING)base)core) EagerParamBaseProgramVariable_create_tensor_current_expected_place_current_expected_place__dygraph_tracerin_dygraph_mode in_pir_mode) _is_file_path_is_memory_buffer_legacy_static_save_open_file_buffer_pack_loaded_dict_pickle_loads_mac_unpack_saved_dict)BytesIO)AnyLiteral TypedDict) NotRequiredUnpack)Tensor)NestedStructure) _StateDictc\rSrSrSrg) _EmptyDictBN)__name__ __module__ __qualname____firstlineno____static_attributes__r%S/var/www/html/banglarbhumi/venv/lib/python3.13/site-packages/paddle/framework/io.pyr#r#Bs r+r#c>\rSrSr%S\S'S\S'S\S'S\S'Srg ) _LoadOptionsEzNotRequired[str]model_filenameparams_filenameNotRequired[bool]keep_name_table return_numpyr%Nr&r'r(r)__annotations__r*r%r+r,r.r.Es(())**''r+r.c*\rSrSr%S\S'S\S'Srg) _SaveOptionsKr2use_binary_formatzNotRequired[Literal[2, 3, 4]]pickle_protocolr%Nr5r%r+r,r8r8Ks,,66r+r8c[[5S:aV[R5nU(a%UR5(aUR 5 [[5S:aMUgg)z, wait until all async save task to be done. rN)lenasync_save_queuepopis_alivejoin)tasks r,clear_async_save_task_queuerCTsF  ! ###% DMMOO IIK  ! #r+c H^[5(d [S5e[U5S:a[R"S5 U4Sjm[ U[ 5(a T"U5 Om[ U[RR5(a-[R"5(aUR5OUnO[S[U535eU(a [5 [R "["XU4S9nUR%5 [&R)U5 g)a async version of paddle.save. Note: currently only support dygraph mode. Note: any argument passed through configs will be overridden by default setting. Args: obj(Object) : The object to be saved. path(str|BytesIO) : The path/buffer of the object to be saved. If saved in the current directory, the input path string will be used as the file name. protocol(int, optional): The protocol version of pickle module must be greater than 1 and less than 5. Default: 4 sync_other_task(bool) : Determine whether to wait other async save task to be finished before this one be put in queue. **configs(dict, optional): compatible argument to paddle.save, but will be overridden by default setting. Examples: .. code-block:: python :name: code-example-1 import paddle emb = paddle.nn.Embedding(10, 10) layer_state_dict = emb.state_dict() # call paddle.async_save with the same style of paddle.save paddle.async_save(layer_state_dict, "emb.pdparams") for i in range(10): # do some calculations here # wait if any async_save task has not been done paddle.clear_async_task_queue() z5async_save currently is not supported in static mode.rzPconfigs are not supported in async mode, will be overridden by default settings.c(>UR5H}up[U[5(a T"U5 M$[U[RR 5(dMO[R "5(aUR5OUX'M gN)items isinstancedictreagerris_compiled_with_cuda pin_memory)sdkvmove_state_dict_to_cpus r,rP*async_save..move_state_dict_to_cpus^HHJDA!T""&q)Atzz0011*.*D*D*F*F A r+z1currently async_save does not support this type: )targetargsN)r ValueErrorr=warningswarnrHrIrrJrrKrL TypeErrortyperC threadingThreadsavestartr>append)objpathprotocolsync_other_taskconfigstrPs @r, async_saverd^sH    C   7|a ^ N#ts# C** + +"&"<"<">">cnnC?S { K  #%Cx+@AAGGIAr+c0n0nUR5GHoup4[U[[RR 45(Ga5UR [RRR:Xa!UR5R5X'OUR5R5R5(d [S5eUR5(aZUR R#5(a;[R$"S5(a [&R(R+US5n[,R."UR155X'UR2X#'GMkXAU'GMr X!S'U$)NzdThe saved tensor is not initialized. If you used group sharded, please use save_group_sharded_model.npuStructuredToParameterName@@)rGrHr rrJrrXVarDescVarTypeVOCABvalueget_map_tensor get_tensor_is_initializedrTis_denseplaceis_custom_placeis_compiled_with_custom_devicepaddle_C_ops npu_identitynparraycpuname) state_dict save_dict name_tablekeyrls r,_build_saved_state_dictrsIJ &&(  eh (9(9: ; ;zzT\\11777!&!=!=!? {{}//1AACC$~NN$$ 3355;;EBB"MM66ubAE!#%))+!6 #jjJO"cN%)&0:+, r+c [5(aSSKJnJn U"XR5nOSSKJnJn U"XR5n[ RR5 U"XUR5n0nUHnXWnUR5(aeURR5(aF[R"[R R#US5R%55Xg'M[R"UR%55Xg'M ['UR5S-n [(R*R-X 5n [(R*R/U 5(ab[1U S5n [2R4"U 5n SSS5 0n UH-nW UR7SS5nUc SUS35eUUX'M/ U nSSS5 U$!,(df  NO=f!,(df  W$=f) Nr)_construct_params_and_buffers_construct_program_holdersrgz.inforbstructured_namezCannot find saved variable (z#)'s structured name in saved model.)rpaddle.jit.pir_translated_layerrrr0paddle.jit.translated_layerrdygraphguardr1rprqrrrwrxrtrurvrystrosr_rAexistsopenpickleloadget) model_pathconfigrrprogramspersistable_var_dictload_param_dictvar_nametmp_varvar_info_filename var_info_pathfextra_var_infostructured_para_dictrs r,*_load_state_dict_from_save_inference_modelrs}} .j:O:OP .j:O:OP    < &"8"8  ,H*4G!!gmm&C&C&E&E,.HHMM..w;??A-)-/HHW[[],C)-  6 67'A ZC 77>>- ( (mT*a!'Q+#% +"0":">">%t#'228*<_`29H9$5,3OC F +*)  F s%#D*G> G-$?G>- G; 7G>> H c n/n/n[R"U5Hpup4nUHdn[RRX65n[RR Xp5nUR SS5n UR U 5 Mf Mr [RR5 UHYn [U SS9n [5RS0SU 0S[RRX 50S9 UR U 5 M[ SSS5 0n UHn U R5(a?U RR5(a [ R"R%U S 5n [&R("U R+55XR,'M U $!,(df  N=f) N\/T)rz persistablerOut file_path)rXinputsoutputsattrsrg)rwalkr_rArelpathreplacer]rrrr rtrace_oprprqrrrtrurvrwrxryrz)r load_var_list var_name_listroot_filesfilenamer tmp_var_namerrznew_varrvars r,!_load_state_dict_from_save_paramsrs[MM''*-H T4I77??9AL#++D#6H   * .    !D$$DAG   & &("BGGLL$BC '    )" O <<>>cii7799--,,S"5C$&HHSWWY$7! %  s -A F&& F4cnSSKJn SSKJnJn [ 5(aX-nOX-n[ RRU5n[ RRU5nU(aU(a[SUSUS35eU(dmU(dfSnUS-n US -n [ RRU 5(d$[ RRU 5(aUS - n[X-5eU(a[ RRU5n [ RRU5n URb[R"S 5 [ 5(a X-Ul O X-Ul UR b[R"S 5 X-UlX4$Un X4$) Nr)PIR_INFER_MODEL_SUFFIX)INFER_MODEL_SUFFIXINFER_PARAMS_SUFFIXzThe z .pdmodel and z directory exist at the same time, don't know which one to load, please make sure that the specified target of ``path`` is unique.z+The ``path`` (%s) to load model not exists.z .pdparamsz.pdoptzplease specify the full file name, not just the file name prefix. For example, it should be written as `paddle.load('model.pdparams')` instead of `paddle.load('model')`.zqWhen loading the result saved with the specified file prefix, the ``model_filename`` config does not take effect.zrWhen loading the result saved with the specified file prefix, the ``params_filename`` config does not take effect.)rrrrrrrr_risdirrTbasenamedirnamer0rUrVr1) r_rrrrprefix_format_pathprefix_format_existdirectory_format_exist error_msgparams_file_pathopti_file_path file_prefixrs r,_build_load_path_and_configr+s  }}!:!6''..);<WW]]4054& dV,% %  !)?A  +- 77>>* + +rww~~n/M/M * I )** ''**40K.J$$0 ' }}(3(L%(3(H%%%1 ' &1%FF "  J  r+cH/SQnUHnX!;dM [SUS35e SSKJn U"5nURSS5UlURSS5UlURSS5UlURS S 5UlURS S 5UlU$) N)r0r1r3r4 safetensorsThe additional config (z$) of `paddle.load` is not supported.r_SaveLoadConfigr0r1r3r4Fr) rTpaddle.jit.apirrr0r1r3r4rrbsupported_configsr~r inner_configs r,_parse_load_configrns  ')#.RS /"$L")++.>"EL#*;;/@$#GL #*;;/@$#GL ' NE BL&{{=%@L r+c/SQnUHnX!;dM [SUS35e SSKJn U"5nURSS5UlURSS5UlURS S5UlU$) N)r:r;rrz$) of `paddle.save` is not supported.rrr:Fr;r)rTrrrr:r;rrs r,_parse_save_configrsO  ')#.RS /"$L%,[[1De%LL"#*;;/@$#GL &{{=%@L r+c^ ^ ^ ^ [U[5(d[S[U535eUS:dUS:a[SU35eSm Sm Sm 0m U U 4Sjn[ US U5 U U U 4S jnU 4S jn[ R S :Xaw[ RRS :XaYU"5 [R"U5nU"5 Sn[S[U5U5HnURXhX-5 M g[R"X5n [R R#5U lT U R [$R&'T U R [$R(R*'T U R [,'U R R/T 5 U R1U5 g)N+The 'protocol' MUST be `int`, but received /Expected 1<'protocol'<5, but received protocol=cUR5(a}URR5(a^[R"S5(aC[ R "[RRUS5R55nO$[ R "UR55nURn[X!444$)Nrfrg) rprqrrrrsrwrxrtrurvryrztuple)selfdatarzs r,reduce_varbase$_pickle_save..reduce_varbases MMOO **,,33E::88FMM66tR@DDFGD88DHHJ'Dyy ''r+c[R"5nUR[R"55 UR 5R 5(aD[R"[RRUS5RU55nO%[R"URU55n[SSU044$)Nrgr) rPlace set_placertCPUPlace_placerrrwrxrurv_copyeval)rprs r,reduce_DenseTensor(_pickle_save..reduce_DenseTensors JJL FOO%& ;;= ( ( * *88FMM66tR@FFqIJD88DJJqM*Dv~.//r+c[S5e)Nz6paddle do not support saving `paddle.nn.Layer` object.)rT)rs r, reduce_Layer"_pickle_save..reduce_Layers D  r+c&>TTUR'U$rF) __class__)layerdispatch_table_layerrs r,create_layer_dispatch_table1_pickle_save..create_layer_dispatch_tables0<U__- r+cJ[U[RR5$rFrHrtnnLayer)rOs r,_pickle_save..s*Q 0r+c >T[R[RR'T[R[ 'T[R[R '[RRT5 grF)rdispatch_tablerrJrr DenseTensorupdate)rrrsr,add_dispatch_table(_pickle_save..add_dispatch_tablesX3Adjj//00>n-2Dd../$$%9:r+cd>[RR[R5 [RR[R R 5 [RR[5 TH"n[RRU5 M$ grF)rrr?rrrJrr)rNrs r,pop_dispatch_table(_pickle_save..pop_dispatch_tablesm!!$"2"23!!$**"3"34!!.1%A  ! ! % %a (&r+darwin@r)rHintrTrX_parse_every_objectsysplatform version_infomajorrdumpsranger=writePicklercopyregrcopyrrrJrrrdump)r^rr`rrr pickle_bytes max_bytesipicklerrrrrs @@@@r, _pickle_savers~ h $ $9$x.9I J  !|x!|=hZ H   (0  0# ;) ||xC$4$4$:$:a$?||C(  q#l+Y7A GGLQ]3 48..-!(!7!7!3Et//04Btzz0011?~.%%&:; Sr+c[U[R5(a [S5eU"U5(ag[ U5[ [ R[[4;ax[ U5[ [ R4;a[UR55nO[[U55nSnUHnU[XU5-nU(dM g U$g)Nz3`paddle.save` do not support saving 'SelectedRows'.TF)rHr SelectedRowsNotImplementedErrorrXrI collections OrderedDictlistrkeysrr= _contain_x)r^condition_funcrflagr~s r,rrs#t(())! A  c ct[44dEB B 9{667 7 #DS?DC Jsx8 8Dt r+cd[U[5(aSnUR5Hup#[U[5(a.UR5HupE[XQ5(dM g MH[U[R R [R45(aM g gg)Nc[U[RR[[ R R[ R[ R45$rF) rHrtrrr rrJrrrr^s r, condition!_is_state_dict..conditionsDIIOOJJ%%$$%%   r+FT)rHrIrGrrrJrr)r^rr~rlrNrOs r,_is_state_dictr s#t ))+JC%&&!KKMDA!!//$*  (9(94;K;K'LMM & r+c[U[5(aL[U5S:Xa=[n[USU5(a#[US[R 5(agg)NrrrTF)rHrr=rrwndarray)r^ name_typess r,_transformed_from_varbaser$/sK#u#c(a- c!fj ) )jQ.L.L r+cD[U[R5(agg)NTF)rHrwr"rs r,_transformed_from_lodtensorr&9s#rzz"" r+c[U[R5(d[S[ U5S35e[ R "5n[5nURX5 U$)Nz8Type of `ndarray` should be numpy.ndarray, but received .) rHrwr"rWrXrrr set)r"rcrqs r, _to_LodTensorr*AsZ grzz * *FtG}oUV W   A $ &EEE' Hr+cU(aUS$[5(a%[R"US5nUSUlU$[ US5$)Nrr)rrt to_tensorrzr*)r^r4rcs r,_tuple_to_tensorr-LsL1v    SV $QSV$$r+ctU(aU$[5(a[R"U5$[U5$rF)rrtr,r*r^r4s r,_ndarray_to_tensorr0Ys/ $$S!!r+c[5nUR5R5RU[ 55 U$rF)r rlrnr)r )tensor return_vars r,_lod_tensor2varbaser4bs6!J!!#''0G0IJ r+c*U"U5(aU"U5$[U5[[R[4;ay[U5[:Xa[ [ U55nO[ UR55nUH0nU"X5(aU"X5X'M [XX5X'M2 U$[U5[:Xa[[[ U5X55$[U5[:Xa[[[ U5X55$[U[5(ae[U[[R[ R"R$[ R&45(d[)S[U5S35eU$)NzXThe iterable objects supported are tuple, list, dict, OrderedDict, string. But received r()rXrIrrrrr=rrrr)rHrrrwr"rrJrrr)r^r convert_funcrr~s r,rrhsLcC  ct[44d; ; 9 S?D #DCch'''1.Hn  ce  S > H   cc &tCy.OPP c8 $ $Z  "**djj//1A1A B. . &jkopsktjuuvw  r+c^SnSn[X5(a&[5(d [S5e[XU5 U4SjnU4Sjn[U[5(a[U[U5$[U[ U5$)NcJ[U[RR5$rFrrs r,is_layer$_parse_load_result..is_layers#vyy//r+ch[URS5nURRU5 U$)NF)_parse_load_result__dict__r)r^ temp_dicts r, parse_layer'_parse_load_result..parse_layers)&s||U;  I& r+zMLayer can only be loaded in dynamic graph mode, but now in static graph mode.c>[UTS9$N)r4)r-r/s r,tuple_to_tensor+_parse_load_result..tuple_to_tensors,??r+c>[UTS9$rB)r0r/s r,ndarray_to_tensor-_parse_load_result..ndarray_to_tensors!#LAAr+)rrrTrr$r&)r^r4r9r?rCrFs ` r,r<r<s0 #    _  C;7@B #011" *O  # ,.?  r+cUR5(d [S5e[U5(a[R"X5nU$[ U5(aN[R "U5n[US5nURU5 UR5nSSS5 U$[S[U535e!,(df  W$=f)NzlThe saved tensor is not initialized. If you used group sharded, please use save_group_sharded_model firstly.wb>Only supports saving objects to file or BytesIO, but received ) rorTrrsave_dense_tensorrsave_dense_tensor_to_memoryrrtellrrX)r2 file_name_seek tensor_bytesrs r,_save_dense_tensorrQs  ! ! # # z  Y&&v9 L 9 % %77? y$ /1 GGL !FFHE0 L"LTR[_L] ^  0 / Ls ;"B>> C c[RRR5n[ U5(a,[RRR X5nX4$[ U5(aa[US5nUR5n[RRRX5 UR5nSSS5 X4$[S[U535e!,(df  UW4$=fNrz>Only supports load objects from file or BytesIO, but received ) rtrrrrload_dense_tensorrrreadload_dense_tensor_from_memoryrMrrX)rNtemp_trOrrPs r,_load_dense_tensorrXs [[   ) ) +FY   226E = 9 % % y$ /1668L KK   : :6 PFFHE0 = "LTR[_L] ^  0 / 5=s A C-- C>cUR5R5(d [S5e[U5(a[R "X5nU$[ U5(aN[R"U5n[US5nURU5 UR5nSSS5 U$[S[U535e!,(df  W$=f)Nz$The saved tensor is not initialized.rIrJ) rnrorTrrsave_selected_rowsrsave_selected_rows_to_memoryrrrMrrX) selected_rowsrNrOselected_rows_bytesrs r,_save_selected_rowsr^s  # # % 5 5 7 7?@@Y'' A L 9 % %"?? N y$ /1 GG' (FFHE0 L"LTR[_L] ^  0 / Ls "C  Cc[R"5n[U5(a[R"X5nX4$[ U5(aa[ US5nUR 5n[RRRX5 SSS5 WR5nX4$[S[U535e!,(df  N8=frS) rrrload_selected_rowsrrrUrtrload_selected_rows_from_memoryrMrrX)rNtemp_srrOrr]s r,_load_selected_rowsrcs!GY''; > 9 % % y$ /1"#&&(  KK   ; ; 0  > "LTR[_L] ^  0 /s :C Cc[U[R5(a [X5 g[U[R5(a [ X5 g[U[R R5(a)[UR5R5U5 g[S[U5S35e)NzLWhen use_binary_format = True, `paddle.save` expected Tensor, but received r() rHrrrQrr^rJrrlrnrrX)r^r_s r,_save_binary_varres#t''((3% C** + +C& C** + +399;113T:"Z[_`c[dZeef g  r+c V[U5(a[RRU5nUS:Xa [ S5e[RR U5nU(a9[RR U5(d[R"USS9 O'[U5(d[ S[U535e[U5n[UR[5(d"[S[UR5S35eUR(a [X5 gUR b"UR n["R$"S 5 [U[&R(R*5(a[-5(a [&R.R1X5 gUR2R55 [7US 5nUR9UR2R;55 SSS5 g[=U5(aF[?5(a*UR@(a [CX5 g[EXU5 g[GXU5 g[7US 5n[IXU5 SSS5 g!,(df  g=f!,(df  g=f) a Save an object to the specified path. Note: Now supports saving ``state_dict`` of Layer/Optimizer, Tensor and nested structure containing Tensor, Program. Note: Different from ``paddle.jit.save``, since the save result of ``paddle.save`` is a single file, there is no need to distinguish multiple saved files by adding a suffix. The argument ``path`` of ``paddle.save`` will be directly used as the saved file name instead of a prefix. In order to unify the saved file name format, we recommend using the paddle standard suffix: 1. for ``Layer.state_dict`` , recommend to use ``.pdparams`` ; 2. for ``Optimizer.state_dict`` , recommend to use ``.pdopt`` . For specific examples, please refer to API code examples. Args: obj(Object) : The object to be saved. path(str|BytesIO) : The path/buffer of the object to be saved. If saved in the current directory, the input path string will be used as the file name. protocol(int, optional): The protocol version of pickle module must be greater than 1 and less than 5. Default: 4 **configs(dict, optional): optional keyword arguments. The following options are currently supported: use_binary_format(bool): When the saved object is static graph variable, you can specify ``use_binary_for_var``. If True, save the file in the c++ binary format when saving a single static graph variable; otherwise, save it in pickle format. Default: False Returns: None Examples: .. code-block:: python :name: code-example-1 >>> # example 1: dynamic graph >>> import paddle >>> emb = paddle.nn.Embedding(10, 10) >>> layer_state_dict = emb.state_dict() >>> # save state_dict of emb >>> paddle.save(layer_state_dict, "emb.pdparams") >>> scheduler = paddle.optimizer.lr.NoamDecay( ... d_model=100, warmup_steps=100, verbose=True) >>> adam = paddle.optimizer.Adam( ... learning_rate=scheduler, ... parameters=emb.parameters()) >>> opt_state_dict = adam.state_dict() >>> # save state_dict of optimizer >>> paddle.save(opt_state_dict, "adam.pdopt") >>> # save weight of emb >>> paddle.save(emb.weight, "emb.weight.pdtensor") .. code-block:: python :name: code-example-2 >>> # example 2: Save multiple state_dict at the same time >>> import paddle >>> from paddle import nn >>> from paddle.optimizer import Adam >>> layer = paddle.nn.Linear(3, 4) >>> adam = Adam(learning_rate=0.001, parameters=layer.parameters()) >>> obj = {'model': layer.state_dict(), 'opt': adam.state_dict(), 'epoch': 100} >>> path = 'example/model.pdparams' >>> paddle.save(obj, path) .. code-block:: python :name: code-example-3 >>> # example 3: static graph >>> import paddle >>> import paddle.static as static >>> paddle.enable_static() >>> # create network >>> x = paddle.static.data(name="x", shape=[None, 224], dtype='float32') >>> z = paddle.static.nn.fc(x, 10) >>> place = paddle.CPUPlace() >>> exe = paddle.static.Executor(place) >>> exe.run(paddle.static.default_startup_program()) >>> prog = paddle.static.default_main_program() >>> for var in prog.list_vars(): ... if list(var.shape) == [224, 10]: ... tensor = var.get_value() ... break >>> # save/load tensor >>> path_tensor = 'temp/tensor.pdtensor' >>> paddle.save(tensor, path_tensor) >>> # save/load state_dict >>> path_state_dict = 'temp/model.pdparams' >>> paddle.save(prog.state_dict("param"), path_tensor) .. code-block:: python :name: code-example-4 >>> # example 4: save program >>> import paddle >>> paddle.enable_static() >>> data = paddle.static.data( ... name='x_static_save', shape=(None, 224), dtype='float32') >>> y_static = z = paddle.static.nn.fc(data, 10) >>> main_program = paddle.static.default_main_program() >>> path = "example/main_program.pdmodel" >>> paddle.save(main_program, path) .. code-block:: python :name: code-example-5 >>> # example 5: save object to memory >>> from io import BytesIO >>> import paddle >>> from paddle.nn import Linear >>> paddle.disable_static() >>> linear = Linear(5, 10) >>> state_dict = linear.state_dict() >>> byio = BytesIO() >>> paddle.save(state_dict, byio) >>> paddle.seed(2023) >>> tensor = paddle.randn([2, 3], dtype='float32') >>> paddle.save(tensor, byio) ~The input path MUST be format of dirname/filename [dirname\filename in Windows system], but received filename is empty string.Texist_okz, ''//$' 277>>'22 KK$ / t $ $J4PT:, W    (F f.. 5 5GVMeMeHfGggh i  #  ! ! ---H MM\  c6==00 1 1}} 11#< &tT2aGGCHH88:;32C   %%s) H5#Cx8"4.!SX./.32/.s*J 3 J J J(c[U[5(d[S[U5S35e[ U5S:Xa[ R "S5 [U5(a[RRU5nUS:Xa [S5e[RRU5nU(a9[RRU5(d[R"USS9 SS KJn U"X5 g) NSNow only supports save state_dict of Layer or Optimizer, expect dict, but received r(r/The input state dict is empty, no need to save.rgrhTri) save_file)rHrIrrXr=rUrVrrr_rrTrrrksafetensors.paddlerw)r^r_rrrws r,rrrrs c4 ! ))-c 1 6   3x1} GHT77##D) r>,  ''//$' 277>>'22 KK$ /, cr+c ^^[U[5(d[S[U5S35e[ U5S:Xa[ R "S5 [U[5(d[S[U535eUS:dUS:a[SU35e[U5(a[RRU5nUS :Xa [S 5e[RRU5nU(a9[RRU5(d[R"US S 9 [U[5(a [!U5n[#WU5n[U5(a[$R&S :Xaz[$R(R*S:Xa\[,R."XRS9m[1US5nSmUR3UU4Sj[5S[ T5T555 SSS5 g[7US5n[,R8"XVUS9 SSS5 g!,(df  g=f!,(df  g=f)Nrur(rrvrrrrrgrhTrirr)r`rIrc32># UH nTXT-v M g7frFr%).0rr r s r, _legacy_save..s!?AQY/?s)rHrIrrXr=rUrVrrTrrr_rrrrkrrrrrrrrr writelinesrrr ) r^r_r`rr saved_objrr r s @@r,rsrss c4 ! ))-c 1 6   3x1} GH h $ $9$x.9I J  !|x!|=hZ H  T77##D) r>,  ''//$' 277>>'22 KK$ /#t+C0 "9h7I d LLH $    " "a '||IA $ I LLq#l"3Y?  tT *a KK x 8+ * + *s3H/I/ H= Ic  [U5(d%[RRU5(Ga[ U5n[ R nUR(aUR(aSSK J n U"U5n[U5nU$SSKnSSK J n [[5[R 5(aUR"S:a`[$R"S:aLUR'USS9n0nUR)5H$nUR+U5R-5XX'M& U$U"U[5S9nU$U"US S9nU$[/US 5n[1U5(a>[2R4S :Xa*[2R6R8S :Xa [;X5nO[ R<"US S9n[U[>5(a[U5nSU;aUSRA5Htup[XY[BRD5(dM([GXYUR5XY'UR(aMU[IXYSS5(dMkXU l%Mv URL(d SU;aUS O+[OXRR5nO[OXRR5nSSS5 U$[U40UD6nU$!,(df  W$=f!UGan [QU5upU sSn A $! [SU5upUR(a[RT"5nURW[$RX"55 U R[5R]5(aJ[BR^"[$R`RcU S5ReU55ssSn A $[BR^"U ReU55ssSn A $[g5(a[iU 5ssSn A $U ssSn A $! [k5(aH[$RlRo5n[$RRqX5 UsssSn A $[/US 5nURs5n[nRt"U5n[$RvRy5(Gal[$RzR}5 [$R~RUR5nUR5n/nURHnURK5S:XdMUR5SnURS5nU [$RlRUURURS9nURU5 UR5RU5 SSS5 O!,(df  O=fURU5 M UHnURU5 M SSS5 O!,(df  O=fUsSSS5 sssSn A $!,(df  O=f! [SUS35e=f=f=fSn A W$Sn A ff=f)a Load an object can be used in paddle from specified path. Note: Now supports loading ``state_dict`` of Layer/Optimizer, Tensor and nested structure containing Tensor, Program. Note: In order to use the model parameters saved by paddle more efficiently, ``paddle.load`` supports loading ``state_dict`` of Layer from the result of other save APIs except ``paddle.save`` , but the argument ``path`` format is different: 1. loading from ``paddle.static.save`` or ``paddle.Model().save(training=True)`` , ``path`` needs to be a complete file name, such as ``model.pdparams`` or ``model.pdopt`` ; 2. loading from ``paddle.jit.save`` or ``paddle.static.save_inference_model`` or ``paddle.Model().save(training=False)`` , ``path`` needs to be a file prefix, such as ``model/mnist``, and ``paddle.load`` will get information from ``mnist.pdmodel`` and ``mnist.pdiparams`` ; 3. loading from paddle 1.x APIs ``paddle.base.io.save_inference_model`` or ``paddle.base.io.save_params/save_persistables`` , ``path`` needs to be a directory, such as ``model`` and model is a directory. Note: If you load ``state_dict`` from the saved result of static graph mode API such as ``paddle.static.save`` or ``paddle.static.save_inference_model`` , the structured variable name in dynamic mode cannot be restored. You need to set the argument ``use_structured_name=False`` when using ``Layer.set_state_dict`` later. Args: path(str|BytesIO) : The path/buffer to load the target object. Generally, the path is the target file path. When loading state_dict from the saved result of the API used to save the inference model, the path may be a file prefix or directory. **configs (dict, optional): other load configuration options for compatibility. We do not recommend using these configurations, they may be removed in the future. If not necessary, DO NOT use them. Default None. The following options are currently supported: (1) model_filename (str): The inference model file name of the paddle 1.x ``save_inference_model`` save format. Default file name is :code:`__model__` . (2) params_filename (str): The persistable variables file name of the paddle 1.x ``save_inference_model`` save format. No default file name, save variables separately by default. (3) return_numpy(bool): If specified as True, return tensor as numpy.ndarray, otherwise return tensor as paddle.Tensor. Default False. Returns: Object(Object): a target object can be used in paddle Examples: .. code-block:: pycon :name: code-example-1 >>> # example 1: dynamic graph >>> import paddle >>> emb = paddle.nn.Embedding(10, 10) >>> layer_state_dict = emb.state_dict() >>> # save state_dict of emb >>> paddle.save(layer_state_dict, "emb.pdparams") >>> scheduler = paddle.optimizer.lr.NoamDecay( ... d_model=100, ... warmup_steps=100, ... verbose=True, ... ) >>> adam = paddle.optimizer.Adam( ... learning_rate=scheduler, ... parameters=emb.parameters(), ... ) >>> opt_state_dict = adam.state_dict() >>> # save state_dict of optimizer >>> paddle.save(opt_state_dict, "adam.pdopt") >>> # save weight of emb >>> paddle.save(emb.weight, "emb.weight.pdtensor") >>> # load state_dict of emb >>> load_layer_state_dict = paddle.load("emb.pdparams") >>> # load state_dict of optimizer >>> load_opt_state_dict = paddle.load("adam.pdopt") >>> # load weight of emb >>> load_weight = paddle.load("emb.weight.pdtensor") .. code-block:: pycon :name: code-example-2 >>> # example 2: Load multiple state_dict at the same time >>> import paddle >>> from paddle import nn >>> from paddle.optimizer import Adam >>> layer = paddle.nn.Linear(3, 4) >>> adam = Adam(learning_rate=0.001, parameters=layer.parameters()) >>> obj = {'model': layer.state_dict(), 'opt': adam.state_dict(), 'epoch': 100} >>> path = 'example/model.pdparams' >>> paddle.save(obj, path) >>> obj_load = paddle.load(path) .. code-block:: pycon :name: code-example-3 >>> # example 3: static graph >>> import paddle >>> import paddle.static as static >>> paddle.enable_static() >>> # create network >>> x = paddle.static.data(name="x", shape=[None, 224], dtype='float32') >>> z = paddle.static.nn.fc(x, 10) >>> place = paddle.CPUPlace() >>> exe = paddle.static.Executor(place) >>> exe.run(paddle.static.default_startup_program()) >>> prog = paddle.static.default_main_program() >>> for var in prog.list_vars(): ... if list(var.shape) == [224, 10]: ... tensor = paddle.static.global_scope().find_var(var.name).get_tensor() ... break >>> # save/load tensor >>> path_tensor = 'temp/tensor.pdtensor' >>> paddle.save(tensor, path_tensor) >>> load_tensor = paddle.load(path_tensor) >>> # save/load state_dict >>> path_state_dict = 'temp/model.pdparams' >>> paddle.save(prog.state_dict("param"), path_tensor) >>> load_state_dict = paddle.load(path_tensor) .. code-block:: pycon :name: code-example-4 >>> # example 4: load program >>> import paddle >>> paddle.enable_static() >>> data = paddle.static.data(name='x_static_save', shape=(None, 224), dtype='float32') >>> y_static = z = paddle.static.nn.fc(data, 10) >>> main_program = paddle.static.default_main_program() >>> path = "example/main_program.pdmodel" >>> paddle.save(main_program, path) >>> load_main = paddle.load(path) .. code-block:: pycon :name: code-example-5 >>> # example 5: save object to memory >>> from io import BytesIO >>> import paddle >>> from paddle.nn import Linear >>> paddle.disable_static() >>> linear = Linear(5, 10) >>> state_dict = linear.state_dict() >>> byio = BytesIO() >>> paddle.save(state_dict, byio) >>> paddle.seed(2023) >>> tensor = paddle.randn([2, 3], dtype='float32') >>> paddle.save(tensor, byio) >>> byio.seek(0) >>> # load state_dict >>> dict_load = paddle.load(byio) r load_fileNz0.6.2z3.2.0rt) framework)deviceryrrrlatin1encodingrhrzrgrgz pd_op.feed)rzshapedtypez%`paddle.load` can not parse the file:r()Prrr_isfilerrUnpicklingErrorrr4safetensors.numpyrrrxrHr r CUDAPlace __version__rt safe_openrrncudarrrrrrrrrIrGrwr"r0getattrrzr3r<rcrXrrrrrrrxrurvrrr4rrmr deserialize_pir_programrUparse_from_stringrin_pir_executor_mode pir_utilsIrGuardpirtranslate_to_pirro global_blockopsrresultrrrreplace_all_uses_withget_defining_op move_beforer] remove_oprT _legacy_load)r_rbrexception_typer load_resultrrrNr~rz msg_pickler2rrprogramprogram_desc_strblockremove_op_listopr org_valuerls r,rr&sWP"''.."6"6#G,//I !!&&;"+D/K"3K"@K.#"+'<!"9";T^^LL'33g= & 2 2g =!, 5 5dh 5 OA*,K%&VVX12a1E1E1G &.#"+4 $-D-F+K#"'0U&C """4.!"$'' 0((..!3"3D">% )(&==&,mm&;&;&=G"KK??N#*NN.tT:a/0vvx,&-&?&? 0'G &//DDFF%+%5%5%=%=%?.4jj.I.I(/ /&G-4,@,@,BE57N.3ii+-779 +D79xxz&7IH8: ! 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