code :
# %%

from sklearn.preprocessing import StandardScaler
import numpy as np
from sklearn.preprocessing import StandardScaler


# %%
import pandas as pd

chunk_size = 10000  # This depends on your available memory
batch_size = 72 



# %%

def data_generator():
    reader = pd.read_csv(r"C:\Users\arisa\Desktop\combined_day.csv", chunksize=chunk_size)
    for chunk in reader:
        
        X = chunk.drop([
                'Date', 'Symbol',
                'y_High_1d', 'y_Low_1d', 'y_Priority_1d',
                 'y_High_2d', 'y_Low_2d', 'y_Priority_2d',
                  'y_High_3d', 'y_Low_3d', 'y_Priority_3d',
                   'y_High_5d', 'y_Low_5d', 'y_Priority_5d'], axis=1).values
        Y = chunk[['y_High_1d', 'y_Low_1d', 'y_Priority_1d',
                 'y_High_2d', 'y_Low_2d', 'y_Priority_2d',
                  'y_High_3d', 'y_Low_3d', 'y_Priority_3d',
                   'y_High_5d', 'y_Low_5d', 'y_Priority_5d']].values
        xScaler = StandardScaler()
        yScaler = StandardScaler()
        X_scaled = xScaler.fit_transform(X)
        Y_scaled = yScaler.fit_transform(Y)
        # Yield batches
        for i in range(0, len(X_scaled), batch_size):
            X_batch = X_scaled[i:i+batch_size]
            y_batch = { 
            'high_output_1d': Y_scaled[i:i + batch_size, 0],
            'low_output_1d': Y_scaled[i:i + batch_size, 1],
            'priority_output_1d': Y_scaled[i:i + batch_size, 2],
            'high_output_2d': Y_scaled[i:i + batch_size, 3],
            'low_output_2d': Y_scaled[i:i + batch_size, 4],
            'priority_output_2d': Y_scaled[i:i + batch_size, 5],
	        'high_output_3d': Y_scaled[i:i + batch_size, 6],
            'low_output_3d': Y_scaled[i:i + batch_size, 7],
            'priority_output_3d': Y_scaled[i:i + batch_size, 8],
            'high_output_5d': Y_scaled[i:i + batch_size, 9],
            'low_output_5d': Y_scaled[i:i + batch_size, 10],
            'priority_output_5d': Y_scaled[i:i + batch_size, 11],
            }
            
            yield np.array(X_batch), np.array(y_batch)

# %%

from tensorflow.keras.layers import Dense, Dropout
from tensorflow.keras import Model
from tensorflow.keras.layers import Input, Dropout

def build_model():
    input_shape = (6427,)

    inputs = Input(shape=input_shape)  # Corrected the input shape specification

    x = Dense(6427, activation='relu')(inputs)
    x = Dropout(0.25) (x)
    x = Dense(3200, activation='relu') (x)
    x = Dropout(0.20) (x)
    x = Dense(1800, activation='relu') (x)
    x = Dropout(0.15) (x)
    x = Dense(1024, activation='relu') (x)
    x = Dropout(0.10) (x)
    x = Dense(512, activation='relu') (x)
    x = Dropout(0.05) (x)
    x = Dense(256, activation='relu') (x)
    x = Dense(128, activation='relu') (x)
    x = Dense(64, activation='relu') (x)
    x = Dense(32, activation='relu')  (x)



    # Defining three separate outputs

    out_high_1d = Dense(1, name='high_output_1d')(x)  # No activation, linear output
    out_low_1d = Dense(1, name='low_output_1d')(x)    # No activation, linear output
    out_priority_1d = Dense(1, activation='sigmoid', name='priority_output_1d')(x)

    out_high_2d = Dense(1, name='high_output_2d')(x)  # No activation, linear output
    out_low_2d = Dense(1, name='low_output_2d')(x)    # No activation, linear output
    out_priority_2d = Dense(1, activation='sigmoid', name='priority_output_2d')(x)

    out_high_3d = Dense(1, name='high_output_3d')(x)  # No activation, linear output
    out_low_3d = Dense(1, name='low_output_3d')(x)    # No activation, linear output
    out_priority_3d = Dense(1, activation='sigmoid', name='priority_output_3d')(x)

    out_high_5d = Dense(1, name='high_output_5d')(x)  # No activation, linear output
    out_low_5d = Dense(1, name='low_output_5d')(x)    # No activation, linear output
    out_priority_5d = Dense(1, activation='sigmoid', name='priority_output_5d')(x)

    # Constructing the model
    model = Model(inputs=inputs, outputs=[
        out_high_1d, out_low_1d, out_priority_1d,out_high_2d, out_low_2d, out_priority_2d,
        out_high_3d, out_low_3d, out_priority_3d,out_high_5d, out_low_5d, out_priority_5d])

    model.compile(optimizer='adam',
                  loss={
                    'high_output_1d': 'mse', 'low_output_1d': 'mse', 'priority_output_1d': 'binary_crossentropy',
                    'high_output_2d': 'mse', 'low_output_2d': 'mse', 'priority_output_2d': 'binary_crossentropy',
                    'high_output_3d': 'mse', 'low_output_3d': 'mse', 'priority_output_3d': 'binary_crossentropy',
                    'high_output_5d': 'mse', 'low_output_5d': 'mse', 'priority_output_5d': 'binary_crossentropy'
                  },
                  metrics={
                    'high_output_1d': ['mae'], 'low_output_1d': ['mae'], 'priority_output_1d': ['accuracy'],
                    'high_output_2d': ['mae'], 'low_output_2d': ['mae'], 'priority_output_2d': ['accuracy'],
                    'high_output_3d': ['mae'], 'low_output_3d': ['mae'], 'priority_output_3d': ['accuracy'],
                    'high_output_5d': ['mae'], 'low_output_5d': ['mae'], 'priority_output_5d': ['accuracy']
                  },
                  loss_weights={
                    'high_output_1d': 1.0, 'low_output_1d': 1.0, 'priority_output_1d': 1.0,
                    'high_output_2d': 1.0, 'low_output_2d': 1.0, 'priority_output_2d': 1.0,
                    'high_output_3d': 1.0, 'low_output_3d': 1.0, 'priority_output_3d': 1.0,
                    'high_output_5d': 1.0, 'low_output_5d': 1.0, 'priority_output_5d': 1.0
                  }
                  )
    return model


# %%

model = build_model()

history = model.fit(data_generator(), steps_per_epoch=100, epochs=10)





error:
{
	"name": "ValueError",
	"message": "When passing a dataset to a Keras model, the arrays must be at least rank 1. Received: {'high_output_1d': array([ 8.79217299e+00,  8.84339892e-01,  7.55902042e-01,  1.11906540e-01,
       -2.26649447e-02, -4.11701868e-01, -5.68778841e-01,  5.85432460e-01,
       -5.02327334e-01,  1.52637873e+00,  2.23464977e+00,  2.29235950e-01,
        1.50940229e+00, -5.23579976e-01, -4.16326501e-01,  4.92877190e-02,
        5.42060489e-02,  3.12979719e-01,  1.40941909e-01, -4.95542371e-03,
        1.96429079e-01, -5.32675319e-01,  1.02765435e+00, -2.93751310e-01,
        1.92111487e+00,  9.38977297e-01, -4.44392048e-01,  6.52754685e-02,
        4.67296064e+00, -2.50815330e-02,  1.56193473e+00, -5.70026099e-01,
       -2.85948033e-01,  3.00088762e-01,  1.20186367e+00,  1.22634695e+00,
       -3.80834498e-01,  1.00077118e+00,  1.12641743e-01, -4.37100319e-02,
        1.45405367e+00,  6.49528231e-01, -5.61224631e-01, -4.32377906e-01,
       -8.13504326e-02, -3.33933058e-01, -3.46453842e-01, -2.39538075e-01,
        6.51959971e-01,  2.52093706e+00, -2.39324606e-01, -4.79073157e-04,
       -1.70394678e-01, -5.42552270e-01, -4.43487031e-01,  1.45189491e+00,
       -3.76486529e-01,  1.70622454e-01,  1.33705161e+00,  2.82900771e-01,
       -3.17095428e-01, -6.55754874e-02,  1.70774551e-01, -1.04341810e-01,
        3.98202705e-01, -4.68149980e-01, -5.94507569e-01, -4.16240397e-01,
       -1.55905947e-01,  2.03732870e-01, -4.72319210e-01,  1.31966277e+00]), 'low_output_1d': array([ 0.62222168,  0.50641497, -0.6090518 , -0.22490433,  0.38988916,
       -0.07180503, -0.47035044,  0.82141432, -1.17004721,  0.63709271,
        0.53498097, -0.02723523,  0.53917205, -1.0045638 , -3.09418541,
       -0.23573305, -2.10687079, -0.55468606,  0.48654386, -0.7127193 ,
       -1.20487145, -1.63227043,  0.66007135, -8.21289095, -1.79706476,
       -4.60779591, -1.94973754, -5.44184606,  0.52137756, -1.70102634,
        0.5151494 , -1.56606524, -2.86856769, -1.21492057, -0.25423014,
        0.01421622, -0.44466742,  0.45018618,  0.619783  , -1.17005953,
        0.6103516 ,  0.61889233, -1.75820998, -2.11729097, -0.39898939,
       -1.10658574, -1.24708922, -0.59100492,  0.1219168 ,  0.32716717,
        0.08521251, -0.11573405, -0.72660666, -1.14529386, -0.07100378,
       -0.42453936, -3.48321905, -3.22402981, -0.13042889, -0.30978229,
       -1.84511656, -0.22848678,  0.41075251, -0.49965728,  0.72595419,
       -0.6290018 , -0.74311692,  0.01713297,  0.35140018,  0.28823087,
       -0.48991381,  0.84596564]), 'priority_output_1d': array([-1.00722611, -1.00722611, -1.00722611,  0.99282573, -1.00722611,
        0.99282573,  0.99282573, -1.00722611,  0.99282573, -1.00722611,
       -1.00722611, -1.00722611, -1.00722611,  0.99282573,  0.99282573,
       -1.00722611,  0.99282573,  0.99282573, -1.00722611,  0.99282573,
        0.99282573,  0.99282573, -1.00722611,  0.99282573, -1.00722611,
        0.99282573,  0.99282573,  0.99282573, -1.00722611,  0.99282573,
       -1.00722611,  0.99282573,  0.99282573,  0.99282573, -1.00722611,
       -1.00722611,  0.99282573, -1.00722611, -1.00722611, -1.00722611,
       -1.00722611, -1.00722611,  0.99282573,  0.99282573, -1.00722611,
        0.99282573,  0.99282573, -1.00722611, -1.00722611, -1.00722611,
        0.99282573,  0.99282573,  0.99282573,  0.99282573,  0.99282573,
       -1.00722611,  0.99282573,  0.99282573, -1.00722611, -1.00722611,
        0.99282573,  0.99282573, -1.00722611,  0.99282573, -1.00722611,
        0.99282573,  0.99282573, -1.00722611, -1.00722611, -1.00722611,
       -1.00722611, -1.00722611]), 'high_output_2d': array([ 5.93195112e+00,  1.38234890e+00,  5.47186882e-01, -1.17218450e-01,
       -2.10999641e-01, -4.82114627e-01, -3.49111146e-02,  2.12775865e-01,
       -6.00258826e-02,  2.69754835e+00,  1.36209487e+00,  8.17323170e-01,
        8.56678929e-01, -5.60081087e-01, -4.85337476e-01,  3.05186246e-01,
       -1.57429203e-01,  2.29069439e-02,  2.47855747e-02, -1.98658097e-01,
       -5.83157454e-02, -2.20404574e-01,  5.47992380e-01, -3.99916353e-01,
        1.49107851e+00,  4.59156859e-01, -5.04896006e-01,  1.49296426e+00,
        3.06132334e+00,  7.16719071e-01,  8.93288131e-01, -5.92448812e-01,
       -3.94478346e-01,  3.10091035e-02,  1.77167650e+00,  6.59421187e-01,
        2.47216135e-01,  5.54774159e-01,  5.19199504e-02,  5.43345110e-01,
        9.98295765e-01,  2.57443410e-01, -5.86315178e-01, -4.96523500e-01,
       -2.09686055e-01, -4.27918512e-01, -4.36644091e-01,  2.18096856e-01,
        2.55430992e+00,  1.56160491e+00, -5.44706096e-02, -1.95538584e-01,
       -3.13950652e-01, -5.73302643e-01,  3.94407937e-01,  8.16602752e-01,
       -4.57573496e-01, -7.63000604e-02,  7.36569889e-01,  1.94529970e-03,
       -4.16184577e-01, -3.65386694e-02,  2.37737179e-01, -8.60126399e-03,
        8.22977813e-02, -5.21452613e-01, -6.09509643e-01, -2.16428747e-01,
        2.45915781e-01, -5.32258238e-02,  5.66537814e-01,  8.31274632e-01]), 'low_output_2d': array([ 0.73460625,  0.64671157, -0.19990256,  0.09165671,  0.5582711 ,
       -0.39642705, -0.09463135,  0.52442862, -0.67282313,  0.74589302,
        0.66839252,  0.2416831 ,  0.67157345, -2.66241052, -2.08606292,
       -0.65998524, -1.98286003, -0.15864018,  0.08001662, -1.6989241 ,
       -1.22777353, -0.97650242, -5.11315829, -5.971045  , -2.06402195,
       -3.23485916, -5.0190101 , -3.86788442,  0.65806784, -1.02868661,
        0.65334081, -2.39117122, -2.63411308, -0.84146959,  0.06939908,
        0.27314382, -0.07513852,  0.60403519, -0.19094916, -0.62569477,
        0.72559712, -0.36975717, -2.82820373, -1.34462207, -0.22531267,
       -1.36886125, -1.31274648, -0.18620538,  0.35488613,  0.51066653,
        0.3270284 , -0.78666465, -1.25822529, -0.71969117, -0.67043215,
       -1.06784349, -4.47822764, -2.18461189,  0.16336144, -0.62637131,
       -1.75632453,  0.08893772,  0.57410592, -0.11687458,  0.14413867,
       -0.33238227, -0.58863737,  0.27535756,  0.52905884,  0.12669226,
       -0.10947951,  0.90442287]), 'priority_output_2d': array([-1.03916644, -1.03916644, -1.03916644,  0.96230975, -1.03916644,
        0.96230975, -1.03916644,  0.96230975, -1.03916644, -1.03916644,
       -1.03916644, -1.03916644, -1.03916644,  0.96230975,  0.96230975,
        0.96230975,  0.96230975,  0.96230975,  0.96230975,  0.96230975,
        0.96230975, -1.03916644,  0.96230975,  0.96230975,  0.96230975,
        0.96230975,  0.96230975, -1.03916644, -1.03916644, -1.03916644,
       -1.03916644,  0.96230975,  0.96230975, -1.03916644, -1.03916644,
       -1.03916644, -1.03916644, -1.03916644, -1.03916644, -1.03916644,
       -1.03916644,  0.96230975,  0.96230975,  0.96230975,  0.96230975,
        0.96230975,  0.96230975, -1.03916644, -1.03916644, -1.03916644,
       -1.03916644,  0.96230975,  0.96230975,  0.96230975, -1.03916644,
        0.96230975,  0.96230975,  0.96230975, -1.03916644,  0.96230975,
        0.96230975, -1.03916644, -1.03916644, -1.03916644,  0.96230975,
        0.96230975,  0.96230975, -1.03916644, -1.03916644,  0.96230975,
       -1.03916644, -1.03916644]), 'high_output_3d': array([ 4.71621415,  1.19804116,  0.31770009, -0.22501563, -0.30162026,
       -0.31233449, -0.15778335,  0.43421314,  1.16057897,  2.07421064,
        1.29344201,  0.53835938,  0.57050691, -0.58676546, -0.52571156,
        0.12002325, -0.25786155, -0.110555  , -0.10902045, -0.29153914,
       -0.17690129, -0.28912251,  0.31835806, -0.4559358 ,  1.08871261,
        0.24579327,  0.09608714,  1.09025297,  2.37135817,  0.4561815 ,
        0.60041093, -0.61320485, -0.4514938 ,  0.75382567,  1.31791747,
        0.82779958,  0.11432236,  0.4732649 ,  0.56352854,  0.45719911,
        0.68618582,  0.08102478, -0.60819462, -0.5348488 , -0.30054726,
       -0.47880921, -0.48593665,  1.91444741,  1.95720714,  1.28850081,
       -0.17376041, -0.28899098, -0.38571521, -0.29623437,  0.19290348,
        0.53777091, -0.50303271, -0.19159167,  0.47239652, -0.1276774 ,
       -0.46922441,  0.0985919 ,  0.29047466, -0.1362923 , -0.06204193,
       -0.55521201, -0.62714089,  0.14807491,  0.07160851,  0.46365286,
        0.41919798,  0.54975556]), 'low_output_3d': array([ 7.93821628e-01,  7.18894557e-01, -2.81372512e-03,  2.45730132e-01,
        1.87258780e-01, -1.70343833e-01,  8.69262170e-02,  5.70708808e-01,
       -4.05961609e-01,  8.03443200e-01,  7.37376790e-01,  3.73622262e-01,
       -9.10629954e-01, -2.10201374e+00, -1.74373748e+00, -9.78029617e-01,
       -1.52272124e+00,  3.23609722e-02, -1.00934287e+00, -1.72951192e+00,
       -8.79036989e-01, -4.76495181e+00, -4.19118861e+00, -5.20082219e+00,
       -1.59190887e+00, -5.02233072e+00, -4.11093064e+00, -3.12963715e+00,
        7.28575370e-01, -7.09322501e-01, -1.97269000e-01, -2.45740698e+00,
       -2.20784836e+00, -5.49726690e-01,  2.26756294e-01,  4.00441400e-01,
        1.03543158e-01,  6.82514466e-01,  4.81872944e-03, -3.65786369e-01,
        7.86141671e-01, -1.73341638e+00, -2.24334653e+00, -1.00598601e+00,
       -7.18323866e-01, -1.50515958e+00, -9.51473387e-01,  8.86262682e-03,
        4.70123801e-01,  6.02921021e-01, -3.17845272e-01, -1.29657630e+00,
       -9.96059673e-01, -1.14215218e+00, -1.22237889e+00, -2.75313245e+00,
       -3.64993293e+00, -1.69470749e+00,  3.06855844e-01, -9.16321685e-01,
       -1.32960783e+00,  2.43412283e-01,  6.57000836e-01,  6.79646580e-02,
        1.87613539e-01, -3.59794214e-01, -3.34196260e-01,  4.02328539e-01,
        6.18599808e-01,  2.75596678e-01,  7.42686937e-02,  8.03640765e-01]), 'priority_output_3d': array([-1.02860908, -1.02860908, -1.02860908,  0.97218664,  0.97218664,
       -1.02860908, -1.02860908, -1.02860908, -1.02860908, -1.02860908,
       -1.02860908, -1.02860908,  0.97218664,  0.97218664,  0.97218664,
        0.97218664,  0.97218664,  0.97218664,  0.97218664,  0.97218664,
        0.97218664,  0.97218664,  0.97218664,  0.97218664,  0.97218664,
        0.97218664, -1.02860908, -1.02860908, -1.02860908, -1.02860908,
        0.97218664,  0.97218664,  0.97218664, -1.02860908, -1.02860908,
       -1.02860908, -1.02860908, -1.02860908, -1.02860908, -1.02860908,
       -1.02860908,  0.97218664,  0.97218664,  0.97218664,  0.97218664,
        0.97218664,  0.97218664, -1.02860908, -1.02860908, -1.02860908,
        0.97218664,  0.97218664,  0.97218664, -1.02860908,  0.97218664,
        0.97218664,  0.97218664,  0.97218664, -1.02860908,  0.97218664,
        0.97218664, -1.02860908, -1.02860908, -1.02860908,  0.97218664,
        0.97218664,  0.97218664, -1.02860908, -1.02860908, -1.02860908,
       -1.02860908,  0.97218664]), 'high_output_5d': array([ 3.43085352,  0.74774032,  0.07635356, -0.30611401, -0.24030393,
       -0.12262669,  1.08529305,  1.28186013,  0.96109604,  1.68590853,
        0.82049719,  0.24463803,  0.26915515, -0.61343158, -0.5668692 ,
       -0.07440348, -0.36259502, -0.25025257, -0.24908226, -0.38827902,
       -0.30085117, -0.386436  ,  0.07685536, -0.51365514,  0.66436156,
        0.02151426, -0.0926582 ,  0.66553631,  1.64256339,  0.18196556,
        0.29196126, -0.63359542, -0.50970055,  0.74347945,  1.23870945,
        0.62348067,  0.55365573,  0.85500748,  0.37646281,  0.18274164,
        0.35737696, -0.10414542, -0.6297744 , -0.57383766, -0.39514902,
        0.37495315,  0.71109134,  1.41311926,  1.4463189 ,  0.81672882,
       -0.29845579, -0.38633569, -0.46010183, -0.39185981, -0.01882181,
        0.24418924, -0.54957331, -0.3120547 ,  0.19433186, -0.26331086,
       -0.52378961,  0.082117  ,  0.05559025, -0.26988097, -0.21325437,
       -0.40819043, -0.39626074,  0.45610495,  0.46116255,  0.25422073,
        0.15376031,  0.25332925]), 'low_output_5d': array([ 0.86909012,  0.80749677,  0.21422077,  0.252387  ,  0.37046874,
        0.07650364,  0.28799096,  0.68568156, -0.11718455,  0.87699948,
        0.27715391, -0.56802764, -0.64970248, -2.01012908, -1.63428184,
       -0.58744965, -1.79860871, -1.02546824, -0.9926242 , -4.22306789,
       -3.80560759, -3.93534411, -3.48586234, -5.42562259, -3.33341254,
       -3.91204331, -3.1628323 , -2.35616582,  0.81545482, -0.67887223,
       -0.63908216, -1.90576727, -1.59841483, -0.23536578,  0.40293744,
        0.54571425,  0.30165081,  0.77759073,  0.22049498, -0.79445333,
       -0.54246703, -1.22916553, -2.09930931, -1.5179469 , -0.80166265,
       -1.0207737 , -0.56561926,  0.22381925,  0.60299625,  0.71216141,
       -0.78197709, -1.44190642, -1.73645564, -2.81041725, -2.36248074,
       -2.04666238, -2.78387187, -1.17659044,  0.171719  , -0.53672301,
       -0.87646243,  0.41662939,  0.7566174 ,  0.0657029 ,  0.16446958,
       -0.07923292, -0.05819027,  0.54726556,  0.72505007,  0.44308639,
        0.27758591,  0.68488414]), 'priority_output_5d': array([-1.02532046, -1.02532046, -1.02532046, -1.02532046, -1.02532046,
       -1.02532046, -1.02532046, -1.02532046, -1.02532046, -1.02532046,
        0.97530483,  0.97530483,  0.97530483,  0.97530483,  0.97530483,
        0.97530483,  0.97530483,  0.97530483,  0.97530483,  0.97530483,
        0.97530483,  0.97530483,  0.97530483,  0.97530483,  0.97530483,
        0.97530483, -1.02532046, -1.02532046, -1.02532046,  0.97530483,
        0.97530483,  0.97530483, -1.02532046, -1.02532046, -1.02532046,
       -1.02532046, -1.02532046, -1.02532046, -1.02532046,  0.97530483,
        0.97530483,  0.97530483,  0.97530483,  0.97530483,  0.97530483,
       -1.02532046, -1.02532046, -1.02532046, -1.02532046, -1.02532046,
        0.97530483,  0.97530483,  0.97530483,  0.97530483,  0.97530483,
        0.97530483,  0.97530483,  0.97530483,  0.97530483,  0.97530483,
        0.97530483, -1.02532046, -1.02532046,  0.97530483,  0.97530483,
       -1.02532046, -1.02532046, -1.02532046, -1.02532046, -1.02532046,
       -1.02532046,  0.97530483])} of rank 0.",
	"stack": "---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[53], line 3
      1 model = build_model()
----> 3 history = model.fit(data_generator(), steps_per_epoch=100, epochs=10)

File c:\\Users\\arisa\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\keras\\src\\utils\\traceback_utils.py:122, in filter_traceback.<locals>.error_handler(*args, **kwargs)
    119     filtered_tb = _process_traceback_frames(e.__traceback__)
    120     # To get the full stack trace, call:
    121     # `keras.config.disable_traceback_filtering()`
--> 122     raise e.with_traceback(filtered_tb) from None
    123 finally:
    124     del filtered_tb

File c:\\Users\\arisa\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\optree\\ops.py:594, in tree_map(func, tree, is_leaf, none_is_leaf, namespace, *rests)
    592 leaves, treespec = _C.flatten(tree, is_leaf, none_is_leaf, namespace)
    593 flat_args = [leaves] + [treespec.flatten_up_to(r) for r in rests]
--> 594 return treespec.unflatten(map(func, *flat_args))

ValueError: When passing a dataset to a Keras model, the arrays must be at least rank 1. Received: {'high_output_1d': array([ 8.79217299e+00,  8.84339892e-01,  7.55902042e-01,  1.11906540e-01,
       -2.26649447e-02, -4.11701868e-01, -5.68778841e-01,  5.85432460e-01,
       -5.02327334e-01,  1.52637873e+00,  2.23464977e+00,  2.29235950e-01,
        1.50940229e+00, -5.23579976e-01, -4.16326501e-01,  4.92877190e-02,
        5.42060489e-02,  3.12979719e-01,  1.40941909e-01, -4.95542371e-03,
        1.96429079e-01, -5.32675319e-01,  1.02765435e+00, -2.93751310e-01,
        1.92111487e+00,  9.38977297e-01, -4.44392048e-01,  6.52754685e-02,
        4.67296064e+00, -2.50815330e-02,  1.56193473e+00, -5.70026099e-01,
       -2.85948033e-01,  3.00088762e-01,  1.20186367e+00,  1.22634695e+00,
       -3.80834498e-01,  1.00077118e+00,  1.12641743e-01, -4.37100319e-02,
        1.45405367e+00,  6.49528231e-01, -5.61224631e-01, -4.32377906e-01,
       -8.13504326e-02, -3.33933058e-01, -3.46453842e-01, -2.39538075e-01,
        6.51959971e-01,  2.52093706e+00, -2.39324606e-01, -4.79073157e-04,
       -1.70394678e-01, -5.42552270e-01, -4.43487031e-01,  1.45189491e+00,
       -3.76486529e-01,  1.70622454e-01,  1.33705161e+00,  2.82900771e-01,
       -3.17095428e-01, -6.55754874e-02,  1.70774551e-01, -1.04341810e-01,
        3.98202705e-01, -4.68149980e-01, -5.94507569e-01, -4.16240397e-01,
       -1.55905947e-01,  2.03732870e-01, -4.72319210e-01,  1.31966277e+00]), 'low_output_1d': array([ 0.62222168,  0.50641497, -0.6090518 , -0.22490433,  0.38988916,
       -0.07180503, -0.47035044,  0.82141432, -1.17004721,  0.63709271,
        0.53498097, -0.02723523,  0.53917205, -1.0045638 , -3.09418541,
       -0.23573305, -2.10687079, -0.55468606,  0.48654386, -0.7127193 ,
       -1.20487145, -1.63227043,  0.66007135, -8.21289095, -1.79706476,
       -4.60779591, -1.94973754, -5.44184606,  0.52137756, -1.70102634,
        0.5151494 , -1.56606524, -2.86856769, -1.21492057, -0.25423014,
        0.01421622, -0.44466742,  0.45018618,  0.619783  , -1.17005953,
        0.6103516 ,  0.61889233, -1.75820998, -2.11729097, -0.39898939,
       -1.10658574, -1.24708922, -0.59100492,  0.1219168 ,  0.32716717,
        0.08521251, -0.11573405, -0.72660666, -1.14529386, -0.07100378,
       -0.42453936, -3.48321905, -3.22402981, -0.13042889, -0.30978229,
       -1.84511656, -0.22848678,  0.41075251, -0.49965728,  0.72595419,
       -0.6290018 , -0.74311692,  0.01713297,  0.35140018,  0.28823087,
       -0.48991381,  0.84596564]), 'priority_output_1d': array([-1.00722611, -1.00722611, -1.00722611,  0.99282573, -1.00722611,
        0.99282573,  0.99282573, -1.00722611,  0.99282573, -1.00722611,
       -1.00722611, -1.00722611, -1.00722611,  0.99282573,  0.99282573,
       -1.00722611,  0.99282573,  0.99282573, -1.00722611,  0.99282573,
        0.99282573,  0.99282573, -1.00722611,  0.99282573, -1.00722611,
        0.99282573,  0.99282573,  0.99282573, -1.00722611,  0.99282573,
       -1.00722611,  0.99282573,  0.99282573,  0.99282573, -1.00722611,
       -1.00722611,  0.99282573, -1.00722611, -1.00722611, -1.00722611,
       -1.00722611, -1.00722611,  0.99282573,  0.99282573, -1.00722611,
        0.99282573,  0.99282573, -1.00722611, -1.00722611, -1.00722611,
        0.99282573,  0.99282573,  0.99282573,  0.99282573,  0.99282573,
       -1.00722611,  0.99282573,  0.99282573, -1.00722611, -1.00722611,
        0.99282573,  0.99282573, -1.00722611,  0.99282573, -1.00722611,
        0.99282573,  0.99282573, -1.00722611, -1.00722611, -1.00722611,
       -1.00722611, -1.00722611]), 'high_output_2d': array([ 5.93195112e+00,  1.38234890e+00,  5.47186882e-01, -1.17218450e-01,
       -2.10999641e-01, -4.82114627e-01, -3.49111146e-02,  2.12775865e-01,
       -6.00258826e-02,  2.69754835e+00,  1.36209487e+00,  8.17323170e-01,
        8.56678929e-01, -5.60081087e-01, -4.85337476e-01,  3.05186246e-01,
       -1.57429203e-01,  2.29069439e-02,  2.47855747e-02, -1.98658097e-01,
       -5.83157454e-02, -2.20404574e-01,  5.47992380e-01, -3.99916353e-01,
        1.49107851e+00,  4.59156859e-01, -5.04896006e-01,  1.49296426e+00,
        3.06132334e+00,  7.16719071e-01,  8.93288131e-01, -5.92448812e-01,
       -3.94478346e-01,  3.10091035e-02,  1.77167650e+00,  6.59421187e-01,
        2.47216135e-01,  5.54774159e-01,  5.19199504e-02,  5.43345110e-01,
        9.98295765e-01,  2.57443410e-01, -5.86315178e-01, -4.96523500e-01,
       -2.09686055e-01, -4.27918512e-01, -4.36644091e-01,  2.18096856e-01,
        2.55430992e+00,  1.56160491e+00, -5.44706096e-02, -1.95538584e-01,
       -3.13950652e-01, -5.73302643e-01,  3.94407937e-01,  8.16602752e-01,
       -4.57573496e-01, -7.63000604e-02,  7.36569889e-01,  1.94529970e-03,
       -4.16184577e-01, -3.65386694e-02,  2.37737179e-01, -8.60126399e-03,
        8.22977813e-02, -5.21452613e-01, -6.09509643e-01, -2.16428747e-01,
        2.45915781e-01, -5.32258238e-02,  5.66537814e-01,  8.31274632e-01]), 'low_output_2d': array([ 0.73460625,  0.64671157, -0.19990256,  0.09165671,  0.5582711 ,
       -0.39642705, -0.09463135,  0.52442862, -0.67282313,  0.74589302,
        0.66839252,  0.2416831 ,  0.67157345, -2.66241052, -2.08606292,
       -0.65998524, -1.98286003, -0.15864018,  0.08001662, -1.6989241 ,
       -1.22777353, -0.97650242, -5.11315829, -5.971045  , -2.06402195,
       -3.23485916, -5.0190101 , -3.86788442,  0.65806784, -1.02868661,
        0.65334081, -2.39117122, -2.63411308, -0.84146959,  0.06939908,
        0.27314382, -0.07513852,  0.60403519, -0.19094916, -0.62569477,
        0.72559712, -0.36975717, -2.82820373, -1.34462207, -0.22531267,
       -1.36886125, -1.31274648, -0.18620538,  0.35488613,  0.51066653,
        0.3270284 , -0.78666465, -1.25822529, -0.71969117, -0.67043215,
       -1.06784349, -4.47822764, -2.18461189,  0.16336144, -0.62637131,
       -1.75632453,  0.08893772,  0.57410592, -0.11687458,  0.14413867,
       -0.33238227, -0.58863737,  0.27535756,  0.52905884,  0.12669226,
       -0.10947951,  0.90442287]), 'priority_output_2d': array([-1.03916644, -1.03916644, -1.03916644,  0.96230975, -1.03916644,
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       -1.03916644, -1.03916644, -1.03916644,  0.96230975,  0.96230975,
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        0.96230975, -1.03916644,  0.96230975,  0.96230975,  0.96230975,
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       -1.03916644,  0.96230975,  0.96230975, -1.03916644, -1.03916644,
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       -1.03916644,  0.96230975,  0.96230975,  0.96230975,  0.96230975,
        0.96230975,  0.96230975, -1.03916644, -1.03916644, -1.03916644,
       -1.03916644,  0.96230975,  0.96230975,  0.96230975, -1.03916644,
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        0.96230975, -1.03916644, -1.03916644, -1.03916644,  0.96230975,
        0.96230975,  0.96230975, -1.03916644, -1.03916644,  0.96230975,
       -1.03916644, -1.03916644]), 'high_output_3d': array([ 4.71621415,  1.19804116,  0.31770009, -0.22501563, -0.30162026,
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        1.29344201,  0.53835938,  0.57050691, -0.58676546, -0.52571156,
        0.12002325, -0.25786155, -0.110555  , -0.10902045, -0.29153914,
       -0.17690129, -0.28912251,  0.31835806, -0.4559358 ,  1.08871261,
        0.24579327,  0.09608714,  1.09025297,  2.37135817,  0.4561815 ,
        0.60041093, -0.61320485, -0.4514938 ,  0.75382567,  1.31791747,
        0.82779958,  0.11432236,  0.4732649 ,  0.56352854,  0.45719911,
        0.68618582,  0.08102478, -0.60819462, -0.5348488 , -0.30054726,
       -0.47880921, -0.48593665,  1.91444741,  1.95720714,  1.28850081,
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       -0.55521201, -0.62714089,  0.14807491,  0.07160851,  0.46365286,
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       -9.96059673e-01, -1.14215218e+00, -1.22237889e+00, -2.75313245e+00,
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       -1.32960783e+00,  2.43412283e-01,  6.57000836e-01,  6.79646580e-02,
        1.87613539e-01, -3.59794214e-01, -3.34196260e-01,  4.02328539e-01,
        6.18599808e-01,  2.75596678e-01,  7.42686937e-02,  8.03640765e-01]), 'priority_output_3d': array([-1.02860908, -1.02860908, -1.02860908,  0.97218664,  0.97218664,
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}