o zi3/@sBdZddlZddlZddlZddlZddlmZmZddlm Z m Z m Z m Z m Z mZmZmZmZmZddlmZddlZddlmZddlmZded efd d Zd e d dfd dZded ee ee ee ffddZ!dej"d e e e ffddZ#dej"d eee e e e fffddZ$  d5dej"de e e e fdedeedfd e e e e ff ddZ%ddddde d e d!eeee e fdeej"d"ee e e fd df d#d$Z&Gd%d&d&eZd'd(d)e d e e fd*d+Z'd'd(d)e d ee fd,d-Z(d'd(d)e d efd.d/Z)d'd(d)e d ee fd0d1Z*d'd(d)e d2e d dfd3d4Z+dS)6z%Utilities used for parameter parsing.N)fields is_dataclass) AnyDictListLiteralMutableMappingOptionalSequenceTupleTypeUnion)nn) AttributeDict)rank_zero_warnobjreturnc Cs0zt|WdStjtttfyYdSw)z"Tests if an object can be pickled.TF)pickledumps PickleErrorAttributeError RuntimeError TypeErrorrrW/home/ubuntu/.local/lib/python3.10/site-packages/pytorch_lightning/utilities/parsing.py is_picklables  rhparamscCs<dd|D}|D]}td|d|d||=q dS)z-Removes all unpicklable entries from hparams.cSsg|] \}}t|s|qSr)r.0kvrrr )z#clean_namespace..z Attribute 'z' removed from hparams because it cannot be pickled. You can suppress this warning by setting `self.save_hyperparameters(ignore=['z'])`.N)itemsr)r del_attrsr rrrclean_namespace'sr&clscCszt|jj}t|}|dj}dttjdt tj j tj j fdt tfdd}||tjj }||tjj }|||fS)a*Parse key words for standard ``self``, ``*args`` and ``**kwargs``. Examples: >>> class Model: ... def __init__(self, hparams, *my_args, anykw=42, **my_kwargs): ... pass >>> parse_class_init_keys(Model) ('self', 'my_args', 'my_kwargs') rparams param_typercSs"|D] }|j|kr|jSqdS)N)kindname)r(r)prrr_get_first_if_anyFs   z0parse_class_init_keys.._get_first_if_any)inspect signature__init__ parameterslistvaluesr+r Parameterr_ParameterKindVAR_POSITIONAL VAR_KEYWORDr str)r'init_parameters init_paramsn_selfr-n_argsn_kwargsrrrparse_class_init_keys3s     r>framecCst|\}}|S)z$For backwards compatibility: #16369.)_get_init_args)r?_ local_argsrrr get_init_argsUs rCc st|\}}}dvrdifSd}t|jj}t|\}}}dd|||fD}g|dddRfdd|D}|rL|||ifdd|D}|d} | |fS) N __class__cSsg|]}|r|qSrr)rnrrrr"bsz"_get_init_args..r? frame_argscsi|]}||qSrr)rr ) local_varsrr esz"_get_init_args..ci|] \}}|vr||qSrrr)exclude_argnamesrrrHi) r. getargvaluesr/r0r1r>updategetr$) r?rAr'r9self_varargs_var kwargs_var filtered_varsrBself_argr)rJrGrr@[s r@Fr path_argsinsideclasses.cCs|t|\}}}}t|jtjs|St|\}}d|vr1|r#t||r1||t|j|d|dS|s.)HyperparametersMixin)rVcSsg|] }t|tr|qSrrWr8rargrrrr"sz(save_hyperparameters..crIrrr)r^rrrHrKkwargscSsg|] \}}t|ts|qSrre)rirgrrrr"rKcsg|] \}}|kr|qSrrr)hprrr"r#cs i|] }t|tr||qSrrerf) init_argsrrrHs z Attribute z is an instance of `nn.Module` and is already saved during checkpointing. It is recommended to ignore them using `self.save_hyperparameters(ignore=[z])`.)lenrWr8r. currentframerXrYrZrrrpytorch_lightning.core.mixinsrdr\rMr2tuplesetr$ _hparams_name enumerate _set_hparams_hparamsrModulercopydeepcopy_hparams_initial) rr^r?r_r` current_framerdrB isx_non_str cand_namesr r!r)rjr^rkrrsave_hyperparameterssX          r|c@seZdZdZdS)ra0Extended dictionary accessible with dot notation. >>> ad = AttributeDict({'key1': 1, 'key2': 'abc'}) >>> ad.key1 1 >>> ad.update({'my-key': 3.14}) >>> ad.update(new_key=42) >>> ad.key1 = 2 >>> ad "key1": 2 "key2": abc "my-key": 3.14 "new_key": 42 N)__name__ __module__ __qualname____doc__rrrrrsrmodelzpl.LightningModule attributecCsg}t||r ||t|dr||jvr||j|j}|durG|jdurGt|j|r4||jt|jdrG||jjvrG||jj|S)zSpecial attribute finding for Lightning. Gets all of the objects or dicts that holds attribute. Checks for attribute in model namespace, the old hparams namespace/dict, and the datamodule. rN)hasattrr[r_trainer datamodule)rrholderstrainerrrr_lightning_get_all_attr_holderss     rcCs"t||}t|dkr dS|dS)zSpecial attribute finding for Lightning. Gets the object or dict that holds attribute, or None. Checks for attribute in model namespace, the old hparams namespace/dict, and the datamodule, returns the last one that has it. rN)rrl)rrrrrr _lightning_get_first_attr_holders  rcCst||duS)zSpecial hasattr for Lightning. Checks for attribute in model namespace, the old hparams namespace/dict, and the datamodule. N)r)rrrrrlightning_hasattrsrcCs<t||}|durt|dt|tr||St||S)a5Special getattr for Lightning. Checks for attribute in model namespace, the old hparams namespace/dict, and the datamodule. Raises: AttributeError: If ``model`` doesn't have ``attribute`` in any of model namespace, the hparams namespace/dict, and the datamodule. N_ is neither stored in the model namespace nor the `hparams` namespace/dict, nor the datamodule.)rrrWdictrb)rrholderrrrlightning_getattrs   rvaluecCsRt||}t|dkrt|d|D]}t|tr |||<qt|||qdS)a]Special setattr for Lightning. Checks for attribute in model namespace and the old hparams namespace/dict. Will also set the attribute on datamodule, if it exists. Raises: AttributeError: If ``model`` doesn't have ``attribute`` in any of model namespace, the hparams namespace/dict, and the datamodule. rrN)rrlrrWrsetattr)rrrrrrrrlightning_setattr5s   r)Fr),rrvr.rrY dataclassesrrtypingrrrrrr r r r r torchrpytorch_lightningpllightning_fabric.utilities.datar_AttributeDict%pytorch_lightning.utilities.rank_zerorobjectboolrr&r8r>rZrCr@r\r|rrrrrrrrrsf 0    $ "(  & H