@ -3554,7 +3554,7 @@ def group_norm(input,
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    Refer  to  ` Group  Normalization  < https : / / arxiv . org / abs / 1803.08494 > ` _  . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    Parameters : 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        input ( Variable ) :  4 - D  Tensor ,  the  data  type  is  float32  or  float64 . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        input ( Tensor ) :  4 - D  Tensor ,  the  data  type  is  float32  or  float64 . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        groups ( int ) :  The  number  of  groups  that  divided  from  channels ,  the  data  type 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            is  int32 . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        epsilon ( float ,  optional ) :  The  small  value  added  to  the  variance  to  prevent 
 
				
			 
			
		
	
	
		
			
				
					
						
						
						
							
								 
							 
						
					 
				
				 
				 
				
					@ -3576,26 +3576,17 @@ def group_norm(input,
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            property .  For  more  information ,  please  refer  to  : ref : ` api_guide_Name `  . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    Returns : 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        Variable :  A  4 - D  Tensor  has  same  data  type  and  data  format  with  ` input ` . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    Raises : 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        ValueError :  If  ` data_layout `  is  neither  ' NCHW '  nor  ' NHWC ' . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        ValueError :  If  ` groups `  is  greater  than  the  number  of  input  channels . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        ValueError :  If  ` groups `  is  less  than  1. 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        ShapeError :  If  the  param_attr ( Scale )  is  not  1 - D  Tensor . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        ShapeError :  If  the  param_attr ( Scale ) ' s first dimension size is not equal to the input channels. 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        ShapeError :  If  the  bias_attr ( Bias )  is  not  1 - D  Tensor . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        ShapeError :  If  the  bias_attr ( Bias ) ' s first dimension size is not equal to the input channels. 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        Tensor :  A  4 - D  Tensor  has  same  data  type  and  data  format  with  ` input ` . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    Examples : 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					       . .  code - block : :  python 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            import  paddle . fluid  as  fluid 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            import  paddle 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            paddle . enable_static ( ) 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            data  =  fluid . data ( name = ' data ' ,  shape = [ None ,  8 ,  32 ,  32 ] ,  dtype = ' float32 ' ) 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            x  =  fluid . layers . group_norm ( input = data ,  groups = 4 ) 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            data  =  paddle . static . data ( name = ' data ' ,  shape = [ 2 ,  8 ,  32 ,  32 ] ,  dtype = ' float32 ' ) 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            x  =  paddle . static . nn . group_norm ( input = data ,  groups = 4 ) 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            print ( x . shape )  # [2, 8, 32, 32] 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    """ 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    helper  =  LayerHelper ( ' group_norm ' ,  * * locals ( ) ) 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    dtype  =  helper . input_dtype ( ) 
 
				
			 
			
		
	
	
		
			
				
					
						
							
								 
							 
						
						
							
								 
							 
						
						
					 
				
				 
				 
				
					@ -3685,7 +3676,7 @@ def spectral_norm(weight, dim=0, power_iters=1, eps=1e-12, name=None):
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    Refer  to  ` Spectral  Normalization  < https : / / arxiv . org / abs / 1802.05957 > ` _  . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    Args : 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        weight ( $ { weight_type } ) :  $ { weight_comment } 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        weight ( Tensor ) :  $ { weight_comment } 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        dim ( int ) :  $ { dim_comment } 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        power_iters ( int ) :  $ { power_iters_comment } 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        eps ( float ) :  $ { eps_comment } 
 
				
			 
			
		
	
	
		
			
				
					
						
						
						
							
								 
							 
						
					 
				
				 
				 
				
					@ -3694,7 +3685,7 @@ def spectral_norm(weight, dim=0, power_iters=1, eps=1e-12, name=None):
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					                             None  by  default . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    Returns : 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        Variable:  A  tensor  variable   of  weight  parameters  after  spectral  normalization . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					        Tensor:  A  tensor   of  weight  parameters  after  spectral  normalization . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					                  The  data  type  and  shape  is  same  as  input  tensor . 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    Examples : 
 
				
			 
			
		
	
	
		
			
				
					
						
						
						
							
								 
							 
						
					 
				
				 
				 
				
					@ -3703,8 +3694,9 @@ def spectral_norm(weight, dim=0, power_iters=1, eps=1e-12, name=None):
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            import  paddle 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            paddle . enable_static ( ) 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            weight  =  paddle .  data( name = ' weight ' ,  shape = [ 2 ,  8 ,  32 ,  32 ] ,  dtype = ' float32 ' ) 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            weight  =  paddle . static.  data( name = ' weight ' ,  shape = [ 2 ,  8 ,  32 ,  32 ] ,  dtype = ' float32 ' ) 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            x  =  paddle . static . nn . spectral_norm ( weight = weight ,  dim = 1 ,  power_iters = 2 ) 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					            print ( x . shape )  # [2, 8, 32, 32] 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    """ 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    helper  =  LayerHelper ( ' spectral_norm ' ,  * * locals ( ) ) 
 
				
			 
			
		
	
		
			
				
					 
					 
				
				 
				 
				
					    check_variable_and_dtype ( weight ,  ' weight ' ,  [ ' float32 ' ,  ' float64 ' ] ,