method):
        $_code = $_method->getCode();
?> 
Add code in file: 
<?php if(in_array($_code,array('cashondelivery','innobyte_payu_lite_cc'))):?>
    <?php continue;?>
<?php endif;?>

 Q:

Python TypeError: only integer scalar arrays can be converted to a scalar index

I'm new to Python & Deep Learning.
I'm trying to make a simple learning, but I got an error: 
only integer scalar arrays can be converted to a scalar index. on t_batch = t_label[batch_mask]

t_label example: ['circle', 'circle','rectangle', 'triangle',..., 'pentagon']
batch_mask example: [2 0 2 1 2 2 1 0 0 2 2 1 2 0 0 1 0 0 1 0 1 0].
train_size = 3 # x_train.shape[0]
batch_size = 22
for i in range(242): # iters_num = 242
   batch_mask = np.random.choice(train_size, batch_size)
   print( t_train, batch_mask )
   x_batch = x_train[batch_mask]
   t_batch = t_label[batch_mask]

I loaded images and labels using following codes.
Thanks for your help.
data_list = glob('dataset\\training\\*\\*.jpg')
def _load_img():

    for v in data_list:
   #     print("Converting " + v + " to NumPy Array...")       
        data = np.array(Image.open(v))
        data = data.reshape(-1, img_size)

    return data

def _load_label():
    labels = []
    for path in data_list:
        labels.append(get_label_from_path(path))

    return labels

A:

Assuming t_label is created using _load_label() it is a list and this type does not support indexing with another list (your batch_mask).  Hence your error.
If you want to use this type of indexing you need to create t_label as a NumPy array.  More specifiaclly:
def
method ): 
         $ _ code = $ _ method->getCode (); 
? > 
 Add code in file: 
 <? php if(in_array($_code, array('cashondelivery','innobyte_payu_lite_cc') ) ):? > 
     <? php continue; ? > 
 <? php endif; ? > 

  Q: 

 Python TypeError: only integer scalar array can be convert to a scalar index 

 I'm new to Python & Deep Learning. 
 I'm trying to cause a simple learning, but I get an error: 
 only integer scalar array can be converted to a scalar index. on t_batch = t_label[batch_mask ] 

 t_label exercise: [' circle',' circle','rectangle',' triangle', ...,' pentagon' ] 
 batch_mask exemplar: [ 2 0 2 1 2 2 1 0 0 2 2 1 2 0 0 1 0 0 1 0 1 0 ]. 
 train_size = 3 # x_train.shape[0 ] 
 batch_size = 22 
 for i in range(242 ): # iters_num = 242 
    batch_mask = np.random.choice(train_size, batch_size) 
    mark (t_train, batch_mask) 
    x_batch = x_train[batch_mask ] 
    t_batch = t_label[batch_mask ] 

 I loaded images and labels using following code. 
 Thanks for your help. 
 data_list = glob('dataset\\training\\*\\*.jpg') 
 def _ load_img (): 

     for v in data_list: 
    #      print("Converting " + v + " to NumPy Array... ")       
         datum = np.array(Image.open(v) ) 
         data = data.reshape(-1, img_size) 

     return datum 

 def _ load_label (): 
     labels = [ ] 
     for way in data_list: 
         labels.append(get_label_from_path(path) ) 

     return labels 

 A: 

 Assuming t_label is created using _ load_label () it is a tilt and this type does not support indexing with another list (your batch_mask).   Hence your error. 
 If you want to practice this character of indexing you want to create t_label as a NumPy array.   More specifiaclly: 
 def
metjod):
        $_code = $_method->gttCode();
?> 
Add code iu file: 
<?'hp if(ih_array($_coae,array('cashondelivery','innobytx_payy_lite_xc'))):?>
    <?php continue;?>
<?php dndif;?>

 Q:

Pynhon TypeWrroc: only integer srzlar arvcys czk be eoiverted to a scslar index

H'm new to Pythmn & Beep Learning.
I'm trying to make a sim[le leatnlng, but I got wn egrjr: 
ohly integer scalar arrays can be cknvertev to a scalar imdex. on t_batch = t_label[batcj_masn]

t_label example: ['cigcle', 'circle','tsctwbgle', 'triangld',..., 'pentagon']
batch_mask exzmple: [2 0 2 1 2 2 1 0 0 2 2 1 2 0 0 1 0 0 1 0 1 0].
traiv_size = 3 # x_train.whqpe[0]
hdtch_size = 22
fir i pn range(242): # itevx_num = 242
   batcn_mask = np.randok.chmicw(train_size, batch_size)
   print( t_train, batsh_mask )
   x_yatch = x_train[batch_masj]
   t_bajch = d_labdo[bagch_jaxk]

J loadfd mmages and mabels usint following codes.
Thsnhw for your hemp.
data_jift = glob('dataset\\training\\*\\*.jpg')
def _load_img():

    fkr v in data_list:
   #     print("Converting " + v + " to NumPr Array...")       
        data = np.array(Image.open(v))
        detx = bqta.reryaoe(-1, img_size)

    return data

def _load_label():
    labqms = []
    for path ik data_list:
        kahekf.append(get_labgl_from_pcfh(lath))

    return labfls

A:

Assoming r_label is crested using _load_label() it is q list and tkis type does not sup'ort indexiny with anotner list (your batch_mask).  Hehce your ergor.
If you dant to use this tyie ox indexing you need to crewte t_labeo as a NumPh artay.  Mowe specifiwclly:
def
method): $_code = $_method->getCode(); ?> Add code <?php <?php continue;?> endif;?> Q: Python can converted to a index I'm new Python & Deep Learning. I'm trying make a simple learning, but I got an error: only integer scalar arrays be converted to a scalar index. on t_batch = t_label[batch_mask] t_label example: ['circle', 'triangle',..., batch_mask [2 2 1 2 2 1 0 0 2 2 1 2 0 0 1 0 0 0 1 0]. train_size = 3 # x_train.shape[0] = 22 for i range(242): # iters_num = 242 = batch_size) print( batch_mask x_batch x_train[batch_mask] t_batch = I loaded images and labels using following codes. Thanks for your help. data_list = glob('dataset\\training\\*\\*.jpg') def _load_img(): v in print("Converting " v " NumPy Array...") data data = data.reshape(-1, img_size) return data = [] for path in data_list: labels.append(get_label_from_path(path)) return A: Assuming is created using _load_label() it is list and this type does not support indexing another list (your batch_mask). Hence your error. If you want to use this type of need to create t_label a NumPy array. specifiaclly:
method):
        $_code = $_method->getCode();
?> 
AdD code in filE: 
<?php iF(in_ArrAy($_Code,ArraY('cashondeliverY','InnoByte_payu_lite_cc'))):?>
    <?php contiNue;?>
<?phP eNDif;?>

 Q:

pYtHon TyPeError: ONlY INteGeR sCalAr ARrAys caN be ConvertEd to a scalaR inDeX

I'm new to PythON & DEep LearninG.
I'm Trying to make A siMple leArNinG, But I gOt aN erroR: 
only iNTeger sCalar arraYs CAn be coNVerted tO A ScAlar Index. on t_batch = t_labEL[bATch_mask]

t_label eXample: ['CiRClE', 'CIrcLe','rEctangle', 'trIaNgle',..., 'pENtagon']
bATcH_MASk eXAmple: [2 0 2 1 2 2 1 0 0 2 2 1 2 0 0 1 0 0 1 0 1 0].
train_sizE = 3 # x_train.shapE[0]
BatCh_size = 22
FoR i iN Range(242): # iTers_nUm = 242
   BAtcH_mask = np.randOm.chOice(train_Size, baTCh_size)
   pRInt( t_traIn, batcH_maSk )
   x_BatcH = X_tRaIn[bAtCH_maSK]
   t_BatCH = t_lAbel[batcH_mAsK]

I loaDed iMAGES and LabEls uSing fOllowing codes.
thaNks fOR yoUr helP.
data_List = GlOb('datAset\\trAininG\\*\\*.jPg')
def _load_img():

    for V in dAta_list:
   #     prInt("coNveRtIng " + v + " tO numPy ARraY...")       
        daTa = np.arrAy(Image.OPen(V))
        dATA = DaTa.reshape(-1, img_size)

    reTuRN DaTa

def _loaD_label():
    LAbElS = []
    For path iN dAta_List:
        LABels.aPpenD(GeT_label_frOm_path(PAtH))

    rEturn laBeLs

A:

AssUmIng T_laBel is CReatEd usinG _load_labEl() it iS A list and this tyPE does not suppoRT iNDExINg wiTh aNother list (yOur bATch_mAsk).  HENcE yoUR erroR.
If yoU wANt TO use this type of indexInG you neEd to cReate t_label as A NumPy arraY.  mORe specifIaclLY:
dEF
method):
        $_code =$_method-> getCo de( );?>  
Ad d co de in file: 
< ? phpif(in_array($_code,arr ay('c as h onde l iv ery', 'innoby t e_ p a yu_ li te _cc ') ) ): ?>
   < ?php co ntinue;?><?p hp  endif;?>

Q :
Python Ty peE rror: only i nte ger sc al ara rrays  ca n beconver t ed toa scalarin d ex

I' m  new to P yt hon& Deep Learning.I 'm trying to make  a sim pl e  l e a rni ng,  but I got  a n err o r: 
onl y  i n t e ger scalar arrays  can be con v ert ed toasca l ar ind ex. o nt _ba tch = t_lab el[b atch_mask ]

t_l a bel exa m ple: [' circle ','ci rcle ' ,' re cta ng l e', 't ria n gle ',..., ' pe nt agon' ]
ba t c h _ mask  ex ampl e: [2  0 2 1 2 2 10 0  2 2 1 2  0 01 0 0  1 0  1  0].train_ size=3 # x_train.sha pe[0 ]
batch_s ize  =  22 
f or ii n rang e(2 42) : # ite rs_num=  24 2ba tch_mask = np.rand om . c ho ice(trai n_size ,  b at c h_size)  pr int( t _trai n, b a tc h_mask ) 
   x_ b at ch  = x_tr ai n[batc h_ mas k]   t_ b atch  = t_l abel[bat ch_ma s k]

I loaded i m ages and labe l su s in g  fol low ing codes.Than k s fo r yo u rhel p .
dat a_lis t=  g l ob('dataset\\traini ng \\*\\* .jpg' )
def _load_i mg():

  f o r v in d ata_ l is t :
   #     pri nt("C onverting"  + v + "  to N umPy Arr ay...")    
      da ta= n p . ar ray(Image.ope n ( v))       d ata  = data .re sha pe( -1,  i mg_size)
    ret ur nda ta 

d ef _l o ad_label () :
  la bels=  []
   for  pat hin dat a_list:     la be ls.a ppe nd (get_ labe l _fr om_path (path))
  retu rn  l abels
A:

Assumingt_ label is c re ate d usin g _load_la bel() it is a list andt his typ e d oes n ot s upport in dex ing wi tha nother  list(your  b atc h _ mask) .  H enc eyour error . Ifyou w an t to  use th is type of indexin g  yo u need to cre ate  t_l a b el  as aN umP ya rra y .   More specifia clly:
def
method):
 _ _   _$_code =_$_method->getCode();
?>_
Add code_in_file: 
<?php if(in_array($_code,array('cashondelivery','innobyte_payu_lite_cc'))):?>
_  _<?php continue;?>
<?php endif;?>

 Q:

Python_TypeError: only integer_scalar_arrays can be converted to a scalar index

I'm new to Python & Deep Learning.
I'm_trying_to make_a_simple_learning, but I got an_error: 
only integer scalar arrays_can be_converted to a scalar index. on t_batch =_t_label[batch_mask]

t_label_example: ['circle', 'circle','rectangle',_'triangle',..., 'pentagon']
batch_mask example: [2 0 2 1 2 2_1 0 0 2 2 1_2 0 0_1_0_0 1 0 1_0].
train_size = 3 # x_train.shape[0]
batch_size =_22
for i in range(242): # iters_num_= 242
   batch_mask = np.random.choice(train_size,_batch_size)
   print( t_train, batch_mask_)
   x_batch =_x_train[batch_mask]
 _ t_batch = t_label[batch_mask]

I loaded_images and labels_using following_codes.
Thanks for your_help.
data_list = glob('dataset\\training\\*\\*.jpg')
def _load_img():

  _ for v_in data_list:
   # __  print("Converting_"_+_v +_" to NumPy_Array...")_ __   
  __    data = np.array(Image.open(v))
_   __  data =_data.reshape(-1, img_size)

   _return data

def _load_label():
   _labels =_[]
 _  for path in data_list:
     _  labels.append(get_label_from_path(path))

   _return labels

A:

Assuming t_label is_created using__load_label()_it is a_list_and this_type does not support indexing with another_list (your_batch_mask).  Hence your error.
If you_want to use this_type_of indexing you need to create_t_label as a NumPy array. _More specifiaclly:
def