
    \iΏ              	          d Z ddlZddlmZ ddlmc mZ ddlZddlm	Z	 ddl
ZddlmZmZmZmZmZ ddlmZmZ ddlmZ ddlZ G d de      Ze G d d	             Ze G d
 d             Z G d d      Z G d d      Z G d d      Z G d dej<                        Z G d d      Z  G d dej<                        Z!	 	 	 	 d6de"de#de#de$fdZ%d  Z&d7d!ed"e"fd#Z'e(d$k(  rddl)Z) e)jT                  d%&      Z+e+jY                  d'e"d(d(d)gd*+       e+jY                  d,e"dd-.       e+jY                  d/e#dd0.       e+jY                  d1e#dd2.       e+jY                  d3e$dd4.       e+j[                         Z.e.j^                  d(k(  r= e%e.j`                  e.jb                  e.jd                  e.jf                  5      Z4 e'e4       ye.j^                  d)k(  r e&       Z4yyy)8z
Theory of Breakthrough Programming (TBP) - CIFAR-10 Implementation

A meta-framework that transforms training into a paradox-navigation problem.
Breakthrough occurs when entropy collapses into a novel paradigm.

Author: TBP Framework
Date: 2026-04-20
    N)DictListTupleOptionalCallable)	dataclassfield)Enumc                   $    e Zd ZdZdZdZdZdZdZy)InnovationDepthz8Energy threshold levels for different innovation depths.               N)	__name__
__module____qualname____doc__T1_INCREMENTALT2_ARCHITECTURALT3_ALGORITHMICT4_PARADIGMT5_META_PARADOX     ex01.pyr   r      s    BNNKOr   r   c                   t    e Zd ZU dZeed<   eed<   eed<   eed<   eed<   ej                  Z	eed<   dZ
eed	<   y
)Paradoxz8A high-energy question state that forces paradigm shift.name	assertionnegationcollapse_targetenergyinnovation_targetFresolvedN)r   r   r   r   str__annotations__floatr   r   r%   r&   boolr   r   r   r   r   #   s:    B
INMM)8)G)GGHdr   r   c                   X    e Zd ZU dZeed<   eed<   eed<   eed<   eed<   e	ed<   eed<   y	)
BreakthroughEventz3Records when entropy collapses into novel paradigm.	timestampparadoxentropy_beforeentropy_afterinnovation_typedescriptionenergy_spentN)
r   r   r   r   intr(   r   r)   r   r'   r   r   r   r,   r,   /   s.    =N$$r   r,   c                       e Zd ZdZddedefdZdej                  defdZ	de
j                  defd	Zdefd
ZdefdZde
j                  dedeeef   fdZy)StagnationDetectorz
    Module 1: Stagnation Detection (The Sensor Layer)
    
    Detects when current paradigm is exhausted via entropy monitoring.
    window_sizeplateau_thresholdc                 <    || _         || _        g | _        g | _        y N)r7   r8   loss_historyentropy_history)selfr7   r8   s      r   __init__zStagnationDetector.__init__B   s"    &!2!r   lossesreturnc                     t        j                  |j                         dz   d      }t        j                  |t        j
                  |dz         z         }|j                         S )z0Compute training entropy from loss distribution.:0yE>r   dim)Fsoftmaxabstorchsumlogitem)r=   r?   probsentropys       r   compute_entropyz"StagnationDetector.compute_entropyH   sL    		&**,-1599UUYYut|%<<==||~r   modelc                    t        j                  |j                         D cg c]  }|j                  j	                          c}      }t        j
                  |      t        j                  t        j
                  |            dz   z  }t        j                  |t        j                  |dz         z         }|j                         S c c}w )zCCompute entropy of the current theory (model weights distribution).rB   )	rH   cat
parametersdataflattenrG   rI   rJ   rK   )r=   rO   pweightsrL   rM   s         r   compute_theory_entropyz)StagnationDetector.compute_theory_entropyN   s    ))u7G7G7IJ!QVV^^-JK		'"eii		'0B&Cd&JK99UUYYut|%<<==||~	 Ks   !C
c                     t        | j                        | j                  k  ry| j                  | j                   d }t        j                  |      }|| j
                  k  S )z(Check if entropy has stopped decreasing.FN)lenr<   r7   npvarr8   )r=   recentvariances      r   detect_entropy_plateauz)StagnationDetector.detect_entropy_plateauV   sX    t##$t'7'77%%t'7'7&7&8966&>$0000r   c                    t        | j                        | j                  k  ryt        j                  | j                  | j                   d       }t        |      dk  ry|t        j
                  |      z
  }t        j                  ||d      }|t        |      dz  d }||d   dz   z  }t        j                  |d	d d
k        S )z%Detect SGD-like oscillation patterns.FN
   full)moder   r   rB   r   g)rY   r<   r7   rZ   arraymean	correlateany)r=   historycenteredautocorrs       r   detect_oscillationz%StagnationDetector.detect_oscillation`   s    t##$t'7'77((4//1A1A0A0BCDw<"RWWW--<<(@CM1,-.x{T12 vvhqrlT)**r   stepc                     | j                  |      }| j                  j                  |       | j                         xs | j	                         | j                         | j	                         |dS )z#Comprehensive stagnation detection.)is_stagnantentropy_plateauoscillationcurrent_entropy)rW   r<   appendr^   rj   )r=   rO   rk   rM   s       r   check_stagnationz#StagnationDetector.check_stagnationr   sg    --e4##G,  668UD<S<S<U#::<224&	
 	
r   N)2   gh㈵>)r   r   r   r   r4   r)   r>   rH   TensorrN   nnModulerW   r*   r^   rj   r   r'   rr   r   r   r   r6   r6   ;   s    "C " "ell u BII % 1 1+D +$

bii 

s 

tCI 

r   r6   c                   v   e Zd ZdZ edddddej                         edd	d
ddej                         edddddej                         edddddej                         edddddej                         edddddej                        gZ	d(d!e
ee      fd"Zd#efd$Zd#ee   fd%Zd&ed#ee   fd'Zy ))ParadoxInjectorz
    Module 2: Paradox Injection (The Mutation Layer)
    
    Injects high-energy question states that force system out of local maxima.
    NoBackprop_Paradoxz(Models require gradient descent to learnz)Models can learn WITHOUT gradient descentequilibrium_modelsg?)r    r!   r"   r#   r$   r%   NoiseLearning_Paradoxz%Training requires clean, labeled dataz!Noise itself is a learning signalnoise_based_learningffffff?ShrinkToGrow_Paradoxz*More parameters always improve performancez-Shrinking a model can improve its performancelottery_ticket333333?SlowIsFast_ParadoxzFaster convergence is betterz3Slower, oscillatory convergence finds better optimaoscillatory_learning      ?ForgettingProgress_Paradoxz(Training must preserve learned knowledgez5Forgetting some knowledge enables faster new learningelastic_weight_consolidationSparseIsDense_Paradoxz"Dense networks are more expressivez/Sparse, event-driven updates are more efficientevent_driven_sparseg      ?Nactive_paradoxesc                 X    |xs | j                   j                         | _        g | _        y r:   )	PARADOXEScopyr   injected_paradoxes)r=   r   s     r   r>   zParadoxInjector.__init__   s$     0 IDNN4G4G4I"$r   r@   c                     t         j                  j                  | j                        }d|_        | j
                  j                  |       |S )z)Inject a random paradox from the library.F)rZ   randomchoicer   r&   r   rq   r=   r.   s     r   inject_random_paradoxz%ParadoxInjector.inject_random_paradox   s=    ))""4#8#89 &&w/r   c                 Z    | j                   D cg c]  }|j                  r| c}S c c}w )z-Get all paradoxes that haven't been resolved.)r   r&   )r=   rU   s     r   get_unresolved_paradoxesz(ParadoxInjector.get_unresolved_paradoxes   s"    22Ea!**EEEs   ((r.   c                 d    d|j                    dd|j                   dddd|j                   dgS )	z1Generate questions from a paradox for navigation.zIs 'z' always true?z	What if 'z' were true?z>Can we find a state where both assertion and negation coexist?z5What structure collapses when we accept the negation?zHow does the collapse target 'z	' emerge?)r!   r"   r#   r   s     r   generate_paradox_questionsz*ParadoxInjector.generate_paradox_questions   sM     7$$%^4(()6LC,W-D-D,EYO
 	
r   r:   )r   r   r   r   r   r   r   r   r   r   r   r   r>   r   r   r'   r   r   r   r   rx   rx      s&    	%@@0-99	
 	(=82-<<	
 	'BD,-<<	
 	%4J2->>	
 	-@L:-<<	
 	(:F1-<<	
S1If%$w-)@ %w F$w- F
' 
d3i 
r   rx   c                       e Zd ZdZd Zdedej                  defdZ	dde
dedee   fd	Zdd
ee   dedee   fdZdefdZy)ODECCTNavigatorz
    Module 3: ODE-CCT Question Space Navigation (The Search Layer)
    
    Finds minimal question path that collapses paradox into novel paradigm.
    Uses TSP-style optimization for maximum collapse potential per cost.
    c                 @    g | _         g | _        t        d      | _        y )Ninf)question_pathcollapse_potentialsr)   rp   r=   s    r   r>   zODECCTNavigator.__init__   s    #% $U|r   questionrO   r@   c                 *   t        j                  |j                         D cg c]  }|j                  j	                          c}      }t        j
                  |      j                         }|t        j                  j                  dd      z  S c c}w )uw   
        Estimate collapse potential (Δ_i) for a question.
        Higher values mean more paradigm-changing.
        r   g       @)
rH   rQ   rR   rS   rT   stdrK   rZ   r   uniform)r=   r   rO   rU   params	diversitys         r   compute_collapse_potentialz*ODECCTNavigator.compute_collapse_potential   sj     e6F6F6HIAFFNN,IJIIf%**,	299,,S#666 Js   !Br.   n_questionsc           
      $   g }d|j                    dd|j                   dddg}g d}||z   }|d| D ]Z  }|j                  |d	|v rd
ndt        j                  j                  dd      t        j                  j                  dd      d       \ |S )z3Generate a lattice of questions around the paradox.zWhat if ?z	How does z emerge from chaos?z<What is the minimum energy required to resolve this paradox?z@Can we find an equilibrium state between assertion and negation?)z'What assumption are we not questioning?z5What would a completely different paradigm look like?z*What constraints are we blindly accepting?z/What if the problem definition itself is wrong?NzWhat ifPARADOXMETA333333?      ?皙?r   )texttypecollapse_potentialcost)r"   r#   rq   rZ   r   r   )r=   r.   r   	questionsbase_questionsmeta_questionsall_questionsqs           r   generate_question_latticez)ODECCTNavigator.generate_question_lattice   s    	 w''(*//00CDJN	

 '7|, 	A%.!^	&(ii&7&7S&A		))#s3	 	 r   r   	max_stepsc                 v    t        |d d      }|d| }|| _        |D cg c]  }|d   	 c}| _        |S c c}w )u{   
        TSP-style path finding: maximize Δ per cost.
        Returns optimal question sequence for breakthrough.
        c                     | d   | d   dz   z  S )Nr   r   rB   r   )r   s    r   <lambda>z8ODECCTNavigator.find_breakthrough_path.<locals>.<lambda>  s    !01QvY5EF r   T)keyreverseNr   )sortedr   r   )r=   r   r   sorted_questionspathr   s         r   find_breakthrough_pathz&ODECCTNavigator.find_breakthrough_path  sR     "F
  
+!EI#JA&:$;#J  $Ks   6c                 ,    t        | j                        S )z0Calculate total entropy reduction from the path.)rI   r   r   s    r   compute_path_entropy_reductionz.ODECCTNavigator.compute_path_entropy_reduction  s    4++,,r   N)   )r`   )r   r   r   r   r>   r'   ru   rv   r)   r   r   r4   r   r   r   r   r   r   r   r   r   r      s}    ,
73 7ryy 7U 7 s TXY]T^ @T
 s TXY]T^ &- -r   r   c                   Z    e Zd ZdZddej
                  dedef fdZd Z	dde
j                  ded	e
j                  fd
Zde
j                  d	e
j                  fdZde
j                  d	e
j                  fdZde
j                  defdZde
j                  ded	e
j                  fdZ xZS )BreakthroughOptimizerz
    Novel optimizer that incorporates paradox resolution into training.
    This is the COLLAPSE mechanism - transforms entropy into novel structure.
    rO   r.   lrc                     t         |           || _        || _        || _        d| _        d| _        d| _        | j                          y )N	ASSERTION        )	superr>   rO   r.   r   phasecollapse_progressr3   _init_innovation_params)r=   rO   r.   r   	__class__s       r   r>   zBreakthroughOptimizer.__init__-  sH    
 
!$ 	$$&r   c                    | j                   j                  dk(  r<t        j                  t	        j
                  d            | _        d| _        d| _        y| j                   j                  dk(  rd| _	        d| _
        d| _        y| j                   j                  d	k(  rd| _        g | _        d
| _        y| j                   j                  dk(  rd| _        d| _        yt        j                  t	        j
                  d            | _        y)z5Initialize parameters based on the innovation target.ry   r   r   r   r~   Nr   	magnituder   g?r   )r.   r    ru   	ParameterrH   tensorenergy_scaleequilibrium_thresholdrestoration_factormaskprune_ratiogrowth_strategyspike_thresholdevent_buffersparse_factoroscillation_amplitudeoscillation_frequencymutation_strengthr   s    r   r   z-BreakthroughOptimizer._init_innovation_params9  s    << 44 "U\\#-> ?D),D&&)D#\\"88DI"D#.D \\"99#&D  "D!$D\\"66),D&),D& &(\\%,,s2C%DD"r   xtrainingr@   c                     |s| j                  |      S | j                  dk(  r| j                  |      }n | j                  dk(  r| j                  |      }| j                  |      S )z0Forward pass with paradox-aware transformations.NEGATIONCOLLAPSE)rO   r   _apply_negation_apply_collapse)r=   r   r   s      r   forwardzBreakthroughOptimizer.forwardV  s[    ::a=  ::#$$Q'AZZ:%$$Q'Azz!}r   c                 H   | j                   j                  dk(  r:t        j                  |      | j                  j                         z  }||dz  z   }|S | j                   j                  dk(  r5t        j
                  |      | j                  kD  j                         }||z  }|S )z+Apply the negation of the current paradigm.ry   r   r   )r.   r    rH   
randn_liker   rG   r   r)   )r=   r   noiser   s       r   r   z%BreakthroughOptimizer._apply_negatione  s    << 44$$Q'$*;*;*?*?*AAEECKA  \\"99IIaL4#7#77>>@DDAr   c                 &   | j                   j                  dk(  rt        j                  |      }|S | j                   j                  dk(  r| j                  >t        j
                  t        | j                  j                               d         | _        t        | j                  j                               D ]W  \  }\  }}|dk(  s|xj                  | j                  d|j                          j                  |j                        z  c_        Y |S )z/Collapse entropy into novel paradigm structure.ry   r~   Nr   )r.   r    rH   tanhr   	ones_likelistrO   rR   	enumeratenamed_parametersrS   numelreshapeshape)r=   r   ir    params        r   r   z%BreakthroughOptimizer._apply_collapses  s    << 44 

1A  \\"88yy !OOD1F1F1H,I!,LM	$-djj.I.I.K$L Q =D%6JJ$))NU[[]";"C"CEKK"PPJQ r   lossepochc                    | xj                   |j                         z  c_         | j                  j                  dz  }| j                  j                  dz  }| j                   |dz  k  rd| _        n| j                   |k  rd| _        nd| _        t        d| j                   |z        | _        t        j                  j                  || j                  j                         dd	      }t        j                         5  t        | j                  j                               D ]G  \  }}||   | j                  ||      }|| j                  ||   |z   z  z  }|j!                  dd       I 	 d
d
d
       y
# 1 sw Y   y
xY w)u~   
        Paradox-aware optimization step.
        Resolves paradox by navigating assertion → negation → collapse.
        d   rs   r   r   r   r   r   T)retain_graphallow_unusedNr`   )r3   rK   r.   r$   r   minr   rH   autogradgradrO   rR   no_gradr   _compute_paradox_modificationr   clamp_)	r=   r   r   energy_thresholdcollapse_threshold	gradientsr   r   paradox_mods	            r   rk   zBreakthroughOptimizer.step  sZ   
 	TYY[(  <<..4!\\0025/#55$DJ!11#DJ#DJ!$S$*;*;>N*N!O NN''$**'') ( 
	 ]]_ 	*%djj&;&;&=> *5Q<+"&"D"DUE"RKTWW	!{(BCCE LLb)*	* 	* 	*s   ;/E3+>E33E<r   c                 Z   | j                   j                  dk(  rt        j                  t        j                  dt
        j                  z  | j                  z  |z  |j                  |j                              }| j                  |z  t        j                  |      z  dz  S | j                   j                  dk(  rgt        j                  t        j                  |      | j                        }t        j                  |      |kD  j                         }| d|z
  z  dz  }|S | j                   j                  dk(  r9t        j                  |      | j                   kD  j                         }| |z  d	z  S | j"                  t        j                  |      z  | j                   j$                  z  S )
z0Compute paradox-specific parameter modification.r   r   )devicedtyper   r~   r   {Gz?r   g?)r.   r    rH   sinr   rZ   pir   r  r  r   r   quantilerG   r   r)   r   r   r$   )r=   r   r   ro   	thresholdr   growth_signal
spike_masks           r   r   z3BreakthroughOptimizer._compute_paradox_modification  s]   << 44))ELLBEE	D666>||kk% K
 --;e>N>Nu>UUX[[[\\"88uyy'79I9IJIIIe$y0779D"Fa$h/$6M  \\"99))E*T-A-AAHHJJ6J&-- ))E,<,<U,CCdllFYFYYYr   )r  )T)r   r   r   r   ru   rv   r   r)   r>   r   rH   rt   r*   r   r   r   r4   rk   r   __classcell__r   s   @r   r   r   '  s    

'bii 
'' 
'u 
'E:    %,,  %,, &$* $*c $*LZ5<< Z ZPUP\P\ Zr   r   c                   0   e Zd ZdZ	 	 ddej
                  dej                  j                  j                  dej                  j                  j                  de
dee   f
dZd	ed
edefdZdeeef   fdZd
edee   fdZ	 	 	 ddedededefdZdefdZy)BreakthroughTrainerz=
    Main training class that orchestrates TBP protocol.
    NrO   train_loadertest_loaderr  r.   c                 @   |j                  |      | _        || _        || _        || _        t               | _        t               | _        t               | _
        |xs | j                  j                         | _        g | _        d| _        g | _        g | _        g | _        y )Nr   )torO   r  r  r  r6   stagnation_detectorrx   paradox_injectorr   	navigatorr   active_paradoxbreakthrough_eventscurrent_phasetrain_lossestest_accuraciesr<   )r=   rO   r  r  r  r.   s         r   r>   zBreakthroughTrainer.__init__  s     XXf%
(& $6#7  / 1(* &V)>)>)T)T)V =? ( !!r   	optimizerr   r@   c                    | j                   j                          d}t        | j                        D ]  \  }\  }}|j	                  | j
                        |j	                  | j
                        }} ||d      }t        j                  ||      }|j                  ||       ||j                         z  } |t        | j                        z  S )z0Train one epoch with paradox-aware optimization.r   T)r   )rO   trainr   r  r  r  rE   cross_entropyrk   rK   rY   )	r=   r  r   
total_loss	batch_idxrS   targetoutputr   s	            r   train_epochzBreakthroughTrainer.train_epoch  s    


)243D3D)E 
	&%I~f774;;/4;;1G&D td3F??662D NN4'$))+%J
	& C 1 1222r   c                    | j                   j                          d}d}d}t        j                         5  | j                  D ]  \  }}|j                  | j                        |j                  | j                        }}| j                  |      }t        j                  ||      }||j                         z  }|j                  d      \  }}	||j                  d      z  }||	j                  |      j                         j                         z  } 	 ddd       d|z  |z  }
|t        | j                        z  |
fS # 1 sw Y   +xY w)zEvaluate model on test set.r   r   r   Ng      Y@)rO   evalrH   r   r  r  r  rE   r"  rK   maxsizeeqrI   rY   )r=   correcttotal	test_lossrS   r%  r&  r   _	predictedaccuracys              r   evaluatezBreakthroughTrainer.evaluate  s   

	]]_ 		= $ 0 0 =f#wwt{{3VYYt{{5KfD)vv6TYY[(	%zz!}9Q'9<</335::<<=		= 7?U*3t//00(::		= 		=s   CD==Ec                    | j                   j                  | j                  |      }|d   rt        | j                        dkD  r|d   }t        | j                        dk\  r| j                  d   n|}||z
  }|dkD  rt        || j                  ||| j                  j                  d|dd| j                  j                   t        | j                  d	d
             }| j                  j                  |       d| j                  _        |S y
)zz
        Check if a breakthrough event has occurred.
        Breakthrough = entropy collapse into novel paradigm.
        rm   r`   rp   r   r   zEntropy collapsed by .2fz via iN)r-   r.   r/   r0   r1   r2   r3   T)r  rr   rO   rY   r<   r,   r  r%   r    rI   r  r  rq   r&   )r=   r   
stagnationrecent_entropyolder_entropyentropy_dropbreakthroughs          r   check_for_breakthroughz*BreakthroughTrainer.check_for_breakthrough  s
    -->>tzz5Q
m$T-A-A)BR)G'(9:N9<T=Q=Q9RVX9XD005^lM(>9Lc!0# //#0"0$($7$7$I$I"7S7ItObObOgOgNh i!$T%6%6tu%=!>  ((//=/3##,##r   epochsr   breakthrough_thresholdc                    t        dd        t        d       t        d        t        d| j                  j                          t        d| j                  j                          t        d| j                  j                          t        d| j                  j
                          t        d| j                  j                  j                          t        d d       t        | j                  | j                  |      }d	}d
}t        |      D ]"  }| j                  ||      }| j                  j                  |       | j                         \  }	}
| j                  j                  |
       | j                  j!                  | j                        }| j"                  j                  |       |j$                  | j&                  k7  r8|j$                  | _        t        d| j&                  j)                          d       |dz  d
k(  s|
|kD  r:t        d|dd|dd|	dd|
dd|dd|j$                   d|j*                  d       |
|kD  r|
}|}| j-                  |      }|sUt        dd        t        d       t        d        t        d|j.                          t        d|j0                  j                          t        d|j2                  j                          t        d|j4                  dd|j6                  d       t        d |j8                          t        d d       % ||| j                  d!   || j                  j                  | j:                  | j"                  | j                  | j                  t=        | j                        |j*                  d"}| j?                  |       |S )#z
        Run the TBP training protocol.
        
        Returns:
            Dictionary with training results and breakthrough events.
        
<============================================================zBREAKTHROUGH TRAINING PROTOCOLzActive Paradox: zAssertion: z
Negation: zCollapse Target: zTarget Innovation Depth: r   r   z
>>> PARADIGM PHASE SHIFT: z <<<
r   zEpoch 3dz	 | Loss: .4fz | Test Loss: z | Acc: r5  z% | Entropy: z
 | Phase: z | Collapse: .2%z<!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!u!   🚀 BREAKTHROUGH EVENT DETECTED!zEpoch: z	Paradox: zInnovation Type: zEntropy Reduction:     → zDescription: )best_accuracy
best_epochfinal_accuracytotal_epochsr  r  r<   training_lossesr  total_energy_spentcollapse_reached) printr  r    r!   r"   r#   r%   r   rO   ranger'  r  rq   r3  r  r  rW   r<   r   r  upperr   r;  r-   r.   r1   r/   r0   r2   r  rI   _print_final_report)r=   r<  r   r=  r  rF  rG  r   
train_lossr/  r2  rM   r:  reports                 r   runzBreakthroughTrainer.run2  s    	6(m.0 !4!4!9!9 :;<D//99:;<
4..7789:!$"5"5"E"E!FGH)$*=*=*O*O*T*T)UVWm *$**d6I6I2N	
6] )	%E)))U;J$$Z0 #'--/Ix  ''1 ..EEdjjQG  ''0 $"4"44%.__"4T5G5G5M5M5O4PPVWX qyA~M!9uRj	*S1A B$$-c?(8C. I"")#j8I J##,#>#>s"CE F -' ("
  66u=L6(m$9;" 6 6789	,"6"6";";!<=>),*F*F*K*K)LMN+L,G,G+LER^RlRlmpQqrsl&>&>%?@Am$S)	%Z +$"2226""1166#'#;#;#33#00#33"%d&7&7"8 ) ; ;
 	  (r   rR  c                    t        dd        t        d       t        d        t        d|d   dd|d    d	       t        d
|d   dd       t        d|d           t        dt        |d                 t        d|d   d       t        d|d   d       |d   rt        dd        t        d       t        d        t        |d         D ]k  \  }}t        |dz    d|j                          t        d|j                  dd|j
                  d       t        d|j                  j                          m t        d d       y)z$Print comprehensive training report.r?  r@  zBREAKTHROUGH TRAINING COMPLETEzBest Accuracy: rF  r5  z	% (Epoch rG  )zFinal Accuracy: rH  %zParadox Resolved: r  zBreakthrough Events: r  zTotal Energy Spent: rK  zCollapse Progress: rL  rC  zBREAKTHROUGH EVENTS:r   z. z   Entropy: rB  rD  z   Innovation: N)rM  rY   r   r2   r/   r0   r1   r    )r=   rR  r   events       r   rP  z'BreakthroughTrainer._print_final_report  s   6(m.0 7<If\FZE[[\]^ (8!9# >a@A"6*:#;"<=>%c&1F*G&H%IJK$V,@%A#$FGH#F+=$>s#CDE'(Bvh- (*VH%f-B&CD F51R 1 1234U%9%9#$>eEDWDWX[C\]^(=(=(B(B'CDEF
 	mr   )cudaN)rs   r  r}   )r   r   r   r   ru   rv   rH   utilsrS   
DataLoaderr'   r   r   r>   r   r4   r)   r'  r   r3  r,   r;  r   rS  rP  r   r   r   r  r    s     %)"yy" kk&&11" [[%%00	"
 " '""<3%: 33 35 3&;%u- ;*C H=N4O B (+	XX X !&	X
 
Xt$ r   r  c                   h     e Zd ZdZddee   f fdZdej                  dej                  fdZ	 xZ
S )ParadoxAwareCNNz
    Neural network architecture designed for paradox-based training.
    Incorporates structure that can collapse into novel paradigms.
    r.   c                    t         |           || _        t        j                  dddd      | _        t        j                  dddd      | _        t        j                  dddd      | _        t        j                  g d      | _	        t        j                  g d      | _
        t        j                  g d	      | _        t        j                  d
      | _        t        j                  dd      | _        t        j                  dd      | _        t        j                  dd      | _        t        j$                  d      | _        y )Nr   @   r   )kernel_sizepadding      )r^      rc  )ra     rd  )rb     re  )r   r   i   i   r`   r   )r   r>   r.   ru   Conv2dconv1conv2conv3	LayerNormnorm1norm2norm3AdaptiveAvgPool2dpoolLinearfc1fc2fc3Dropoutdropout)r=   r.   r   s     r   r>   zParadoxAwareCNN.__init__  s     YYq"!Q?
YYr3AqA
YYsCQB
 \\,/
\\-0
\\+.
 ((0	 99[#.99S#&99S"% zz#r   r   r@   c                    | j                  t        j                  | j                  |                  }t        j                  |dd      }| j                  t        j                  | j                  |                  }t        j                  |dd      }| j                  t        j                  | j                  |                  }| j                  r`| j                  j                  dk(  rG|j                  d      dkD  j                         j                  d      j                  d      }||z  }n| j                  |      }|j                  |j!                  d      d      }| j#                  t        j                  | j%                  |                  }| j#                  t        j                  | j'                  |                  }| j)                  |      }|S )	Nr   )r_  strider   )r   r   rC   r   rE  r   )rk  rE   relurg  
max_pool2drl  rh  rm  ri  r.   r    rd   r)   	unsqueezero  viewr+  ru  rq  rr  rs  )r=   r   spikes      r   r   zParadoxAwareCNN.forward  sP   JJqvvdjjm,-LL!4JJqvvdjjm,-LL!4JJqvvdjjm,- <<DLL--1HHVVV'#-446@@DNNrREE	A		!AFF166!9b!LL,-LL,-HHQKr   r:   )r   r   r   r   r   r   r>   rH   rt   r   r  r  s   @r   r\  r\    s4    
' 1 '2 %,, r   r\  rs   ra  r  paradox_namer<  
batch_sizer   c           	           t        d       t        d       t        d       t        j                  j                         rdnd}t        d|        t	        j
                  t	        j                  dd	      t	        j                         t	        j                         t	        j                  d
d      g      }t	        j
                  t	        j                         t	        j                  d
d      g      }t        j                  j                  ddd|      }t        j                  j                  ddd|      }t        j                  j                  j                  ||dd      }	t        j                  j                  j                  ||dd      }
t        dt!        |              t        dt!        |              t"        j$                  } rt'         fd|D        |d         }nt(        j*                  j-                  |      }t        d|j.                          t        d|j0                  j.                          t        d|j2                          t5        |      }t7        ||	|
||      }|j9                  ||      }|S )z;
    Run breakthrough training experiment on CIFAR-10.
    G
======================================================================uB   🚀 THEORY OF BREAKTHROUGH PROGRAMMING - CIFAR-10 EXPERIMENT 🚀F======================================================================rX  cpuzDevice: rc  r   )r`  )gHPs?gec]?g~jt?)gۊe?ggDio?g|?5^?z../dataT)rootr!  download	transformF)r~  shufflenum_workerszTraining samples: zTest samples: c              3   B   K   | ]  }|j                   k(  s|  y wr:   )r    ).0rU   r}  s     r   	<genexpr>z.run_breakthrough_experiment.<locals>.<genexpr>  s     B1166\+AQBs   r   z
Selected Paradox: zInnovation Target: zEnergy Level: )rO   r  r  r  r.   )r<  r   )rM  rH   rX  is_available
transformsCompose
RandomCropRandomHorizontalFlipToTensor	NormalizetorchvisiondatasetsCIFAR10rY  rS   rZ  rY   rx   r   nextrZ   r   r   r    r%   r$   r\  r  rS  )r}  r<  r~  r   r  transform_traintransform_testtrain_datasettest_datasetr  r  paradox_libraryselected_paradoxrO   trainerresultss   `               r   run_breakthrough_experimentr    sg    
-	
NO	&M zz..0VeF	HVH
 !((b!,'')57OP	* O  ''57OP) N
  ((00dT_ 1 M ''//edn 0 L ;;##..*d / L ++""--U . K 
s=12
34	N3|,-
./ &//OBBA

 99++O<	 !1!6!6 7
89	 0 B B G GH
IJ	N+223
45 ,-E "! G kkBk/GNr   c                     t        d       t        d       t        d       i } g d}|D ]?  }t        dd        t        d|        t        d        	 t        |dd	d
      }|| |<   A t        d       t        d       t        d       | j	                         D ]|  \  }}d|v rt        | d|d           t        | d       t        d|d   dd       t        dt        |d                 t        d|d   d       t        d|d   d       ~ | S # t        $ r,}t        d| d|        dt        |      i| |<   Y d}~$d}~ww xY w)zU
    Run experiments with multiple paradoxes to find best breakthrough approach.
    r  u(   🔬 MULTI-PARADOX COMPARISON EXPERIMENTr  )ry   r~   r   r   r?  z2==================================================z	Testing:    ra  r  r}  r<  r~  r   zError with z: errorNu   📊 PARADOX COMPARISON SUMMARYz
: ERROR - :z  Best Accuracy: rF  r5  rV  z  Breakthrough Events: r  z  Total Energy: rK  z  Collapse Progress: rL  rC  )rM  r  	Exceptionr'   itemsrY   )r  paradox_namesr}  resulter    s         r   run_multi_paradox_comparisonr  2  s    
-	
45	&MGM & 66(m	,()
	60)	F %+GL!6$ 
-	
+,	&M LffTF*VG_$567TF!*%f_&=c%B!DE+C7L0M,N+OPQ$V,@%A#$FGH)&1C*DS)IJKL N'  	6K~Rs34%,c!f$5GL!	6s   D	E'!EEr  	save_pathc                    	 ddl m} |j                  ddd      \  }}|d   j                  | d   dd	
       |d   j	                  d       |d   j                  d       |d   j                  d       |d   j                  dd
       |d   j                  | d   dd	
       |d   j	                  d       |d   j                  d       |d   j                  d       |d   j                  dd
       |d   j                  | d   dd	
       |d   j	                  d       |d   j                  d       |d   j                  d       |d   j                  dd
       | d   D ]%  }|d   j                  |j                  ddd	d       ' |d   j                  | d   ddd    | d   ddd    t        t        | d   ddd                d!d"#       |d   j	                  d$       |d   j                  d%       |d   j                  d&       |d   j                  dd
       |j                  d'| d(    d)d*+       |j                          |j                  |d,d-.       t!        d/|        y# t"        $ r t!        d0       Y yw xY w)1z3
    Visualize breakthrough training dynamics.
    r   Nr   )   r`   )figsize)r   r   rJ  zb-r}   )alphazTraining Loss (Energy Spent)EpochLossTr   )r   r   r  zg-zTest AccuracyzAccuracy (%))r   r   r<   zr-z%Theory Entropy (Breakthrough Monitor)Entropyr  orangez--Breakthrough)r   color	linestyler  label)r   r   r   viridisr   )ccmapr  zLoss vs Accuracy TrajectoryzTraining LosszTest Accuracy (%)z!Breakthrough Training Analysis - r  r  bold)fontsize
fontweight   tight)dpibbox_incheszAnalysis plot saved to: z1Matplotlib not available. Skipping visualization.)matplotlib.pyplotpyplotsubplotsplot	set_title
set_xlabel
set_ylabelgridaxvliner-   scatterrN  rY   suptitletight_layoutsavefigrM  ImportError)r  r  pltfigaxesrW  s         r   plot_breakthrough_analysisr  i  s   0C'LLAxL8	T 	T
 12DDT
;<T
g&T
f%T
C( 	T
 12DDT
_-T
g&T
n-T
C( 	T
 12DDT
DET
g&T
i(T
C( 23 	OEJ(,C~  O	O
 	T
7#45cc:!"34SqS9!#g.?&@1&E"FG( 	 	5 	T
:;T
o.T
12T
C(8AQ9R8STF 	 	4I3G<(45 CABCs   I2I5 5JJ__main__z$Breakthrough ML Training on CIFAR-10)r2   z--modesingle
comparisonz9Training mode: single paradox or multi-paradox comparison)r   defaultchoiceshelpz	--paradoxz3Specific paradox to test (e.g., NoBackprop_Paradox))r   r  r  z--epochszNumber of training epochsz--batch_sizez
Batch sizez--lrzLearning rater  )Nrs   ra  r  )zbreakthrough_analysis.png)5r   rH   torch.nnru   torch.nn.functional
functionalrE   r  torchvision.transformsr  numpyrZ   typingr   r   r   r   r   dataclassesr   r	   enumr
   warningsr   r   r,   r6   rx   r   rv   r   r  r\  r'   r4   r)   r  r  r  r   argparseArgumentParserparseradd_argument
parse_argsargsrb   r.   r<  r~  r   r  r   r   r   <module>r     sD        +  8 8 (  d       A
 A
HR
 R
jL- L-f^ZBII ^ZBY Y@4bii 4x 	LLL L 		L^0n4C 4C 4Cv z$X$$1WXF
sH (,7W  Y #tQ  S

b7  9
S#(  *
UD+  - DyyH-;;ww	
 	#7+	l	".0 
#7 r   