Repository: truera/trulens
Issue: Error when running IntegratedGradients.attributions(image)
Root cause: Validation Gap

Hello! Would appreciate any help to solve this problem! I'm trying to use the IntegratedGradients() to explain my model.

```
yolo = Load_Yolo_model() # yolo is <class 'tensorflow.python.keras.engine.functional.Functional'> object
model_wrapped = get_model_wrapper(yolo)
ig_computer = IntegratedGradients(model_wrapped, resolution=20)

with PIL.Image.open(image_path).convert('RGB') as img:
    x = np.array(img.resize((416, 416)))
    x_np = np.array(img.resize((416, 416), PIL.Image.ANTIALIAS))[np.newaxis]
    input_attributions = ig_computer.attributions(x_np)

```

But run into a problem:
```
Traceback (most recent call last):
  File "trulens_yolov3.py", line 31, in <module>
    input_attributions = ig_computer.attributions(x_np)
  File "/home/ubuntu/anaconda3/envs/TF23/lib/python3.8/site-packages/trulens/nn/attribution.py", line 264, in attributions
    qoi_grads = self.model.qoi_bprop(
  File "/home/ubuntu/anaconda3/envs/TF23/lib/python3.8/site-packages/trulens/nn/models/tensorflow_v2.py", line 424, in qoi_bprop
    Q = qoi(outputs[0]) if len(outputs) == 1 else qoi(outputs)
  File "/home/ubuntu/anaconda3/envs/TF23/lib/python3.8/site-packages/trulens/nn/quantities.py", line 111, in __call__
    self._assert_cut_contains_only_one_tensor(y)
  File "/home/ubuntu/anaconda3/envs/TF23/lib/python3.8/site-packages/trulens/nn/quantities.py", line 63, in _assert_cut_contains_only_one_tensor
    raise QoiCutSupportError(
trulens.nn.quantities.QoiCutSupportError: Cut provided to quantity of interest was comprised of multiple tensors, but `MaxClassQoI` is only defined for cuts comprised of a single tensor (received a list of 3 tensors).

Either (1) select a slice where the `to_cut` corresponds to a single tensor, or (2) implement/use a `QoI` object that supports lists of tensors, i.e., where the parameter, `x`, to `__call__` is expected/allowed to be a list of 3 tensors.
```

I'm using TensorFlow 2.5  and here is the output of my trained model. Any help would be appreciated!




My network summary from yolo.summary() is:

```
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_1 (InputLayer)            [(None, 416, 416, 3) 0                                            
__________________________________________________________________________________________________
conv2d (Conv2D)                 (None, 416, 416, 32) 864         input_1[0][0]                    
__________________________________________________________________________________________________
batch_normalization (BatchNorma (None, 416, 416, 32) 128         conv2d[0][0]                     
__________________________________________________________________________________________________
leaky_re_lu (LeakyReLU)         (None, 416, 416, 32) 0           batch_normalization[0][0]        
__________________________________________________________________________________________________
zero_padding2d (ZeroPadding2D)  (None, 417, 417, 32) 0           leaky_re_lu[0][0]                
__________________________________________________________________________________________________
conv2d_1 (Conv2D)               (None, 208, 208, 64) 18432       zero_padding2d[0][0]             
__________________________________________________________________________________________________
batch_normalization_1 (BatchNor (None, 208, 208, 64) 256         conv2d_1[0][0]                   
__________________________________________________________________________________________________
leaky_re_lu_1 (LeakyReLU)       (None, 208, 208, 64) 0           batch_normalization_1[0][0]      
__________________________________________________________________________________________________
conv2d_2 (Conv2D)               (None, 208, 208, 32) 2048        leaky_re_lu_1[0][0]              
__________________________________________________________________________________________________
batch_normalization_2 (BatchNor (None, 208, 208, 32) 128         conv2d_2[0][0]                   
__________________________________________________________________________________________________
leaky_re_lu_2 (LeakyReLU)       (None, 208, 208, 32) 0           batch_normalization_2[0][0]      
__________________________________________________________________________________________________
conv2d_3 (Conv2D)               (None, 208, 208, 64) 18432       leaky_re_lu_2[0][0]              
__________________________________________________________________________________________________
batch_normalization_3 (BatchNor (None, 208, 208, 64) 256         conv2d_3[0][0]                   
__________________________________________________________________________________________________
leaky_re_lu_3 (LeakyReLU)       (None, 208, 208, 64) 0           batch_normalization_3[0][0]      
__________________________________________________________________________________________________
tf.__operators__.add (TFOpLambd (None, 208, 208, 64) 0           leaky_re_lu_1[0][0]              
                                                                 leaky_re_lu_3[0][0]              
__________________________________________________________________________________________________
zero_padding2d_1 (ZeroPadding2D (None, 209, 209, 64) 0           tf.__operators__.add[0][0]       
__________________________________________________________________________________________________
conv2d_4 (Conv2D)               (None, 104, 104, 128 73728       zero_padding2d_1[0][0]           
__________________________________________________________________________________________________
batch_normalization_4 (BatchNor (None, 104, 104, 128 512         conv2d_4[0][0]                   
__________________________________________________________________________________________________
leaky_re_lu_4 (LeakyReLU)       (None, 104, 104, 128 0           batch_normalization_4[0][0]      
__________________________________________________________________________________________________
conv2d_5 (Conv2D)               (None, 104, 104, 64) 8192        leaky_re_lu_4[0][0]              
__________________________________________________________________________________________________
batch_normalization_5 (BatchNor (None, 104, 104, 64) 256         conv2d_5[0][0]                   
__________________________________________________________________________________________________
leaky_re_lu_5 (LeakyReLU)       (None, 104, 104, 64) 0           batch_normalization_5[0][0]      
__________________________________________________________________________________________________
conv2d_6 (Conv2D)               (None, 104, 104, 128 73728       leaky_re_lu_5[0][0]              
__________________________________________________________________________________________________
batch_normalization_6 (BatchNor (None, 104, 104, 128 512         conv2d_6[0][0]                   
__________________________________________________________________________________________________
leaky_re_lu_6 (LeakyReLU)       (None, 104, 104, 128 0           batch_normalization_6[0][0]      
__________________________________________________________________________________________________
tf.__operators__.add_1 (TFOpLam (None, 104, 104, 128 0           leaky_re_lu_4[0][0]              
                                                                 leaky_re_lu_6[0][0]              
__________________________________________________________________________________________________
conv2d_7 (Conv2D)               (None, 104, 104, 64) 8192        tf.__operators__.add_1[0][0]     
__________________________________________________________________________________________________
batch_normalization_7 (BatchNor (None, 104, 104, 64) 256         conv2d_7[0][0]                   
__________________________________________________________________________________________________
leaky_re_lu_7 (LeakyReLU)       (None, 104, 104, 64) 0           batch_normalization_7[0][0]      
__________________________________________________________________________________________________
conv2d_8 (Conv2D)               (None, 104, 104, 128 73728       leaky_re_lu_7[0][0]              
__________________________________________________________________________________________________
batch_normalization_8 (BatchNor (None, 104, 104, 128 512         conv2d_8[0][0]                   
__________________________________________________________________________________________________
leaky_re_lu_8 (LeakyReLU)       (None, 104, 104, 128 0           batch_normalization_8[0][0]      
__________________________________________________________________________________________________
tf.__operators__.add_2 (TFOpLam (None, 104, 104, 128 0           tf.__operators__.add_1[0][0]     
                                                                 leaky_re_lu_8[0][0]              
__________________________________________________________________________________________________
zero_padding2d_2 (ZeroPadding2D (None, 105, 105, 128 0           tf.__operators__.add_2[0][0]     
__________________________________________________________________________________________________
conv2d_9 (Conv2D)               (None, 52, 52, 256)  294912      zero_padding2d_2[0][0]           
__________________________________________________________________________________________________
batch_normalization_9 (BatchNor (None, 52, 52, 256)  1024        conv2d_9[0][0]                   
__________________________________________________________________________________________________
leaky_re_lu_9 (LeakyReLU)       (None, 52, 52, 256)  0           batch_normalization_9[0][0]      
__________________________________________________________________________________________________
conv2d_10 (Conv2D)              (None, 52, 52, 128)  32768       leaky_re_lu_9[0][0]              
__________________________________________________________________________________________________
batch_normalization_10 (BatchNo (None, 52, 52, 128)  512         conv2d_10[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_10 (LeakyReLU)      (None, 52, 52, 128)  0           batch_normalization_10[0][0]     
__________________________________________________________________________________________________
conv2d_11 (Conv2D)              (None, 52, 52, 256)  294912      leaky_re_lu_10[0][0]             
__________________________________________________________________________________________________
batch_normalization_11 (BatchNo (None, 52, 52, 256)  1024        conv2d_11[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_11 (LeakyReLU)      (None, 52, 52, 256)  0           batch_normalization_11[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_3 (TFOpLam (None, 52, 52, 256)  0           leaky_re_lu_9[0][0]              
                                                                 leaky_re_lu_11[0][0]             
__________________________________________________________________________________________________
conv2d_12 (Conv2D)              (None, 52, 52, 128)  32768       tf.__operators__.add_3[0][0]     
__________________________________________________________________________________________________
batch_normalization_12 (BatchNo (None, 52, 52, 128)  512         conv2d_12[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_12 (LeakyReLU)      (None, 52, 52, 128)  0           batch_normalization_12[0][0]     
__________________________________________________________________________________________________
conv2d_13 (Conv2D)              (None, 52, 52, 256)  294912      leaky_re_lu_12[0][0]             
__________________________________________________________________________________________________
batch_normalization_13 (BatchNo (None, 52, 52, 256)  1024        conv2d_13[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_13 (LeakyReLU)      (None, 52, 52, 256)  0           batch_normalization_13[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_4 (TFOpLam (None, 52, 52, 256)  0           tf.__operators__.add_3[0][0]     
                                                                 leaky_re_lu_13[0][0]             
__________________________________________________________________________________________________
conv2d_14 (Conv2D)              (None, 52, 52, 128)  32768       tf.__operators__.add_4[0][0]     
__________________________________________________________________________________________________
batch_normalization_14 (BatchNo (None, 52, 52, 128)  512         conv2d_14[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_14 (LeakyReLU)      (None, 52, 52, 128)  0           batch_normalization_14[0][0]     
__________________________________________________________________________________________________
conv2d_15 (Conv2D)              (None, 52, 52, 256)  294912      leaky_re_lu_14[0][0]             
__________________________________________________________________________________________________
batch_normalization_15 (BatchNo (None, 52, 52, 256)  1024        conv2d_15[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_15 (LeakyReLU)      (None, 52, 52, 256)  0           batch_normalization_15[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_5 (TFOpLam (None, 52, 52, 256)  0           tf.__operators__.add_4[0][0]     
                                                                 leaky_re_lu_15[0][0]             
__________________________________________________________________________________________________
conv2d_16 (Conv2D)              (None, 52, 52, 128)  32768       tf.__operators__.add_5[0][0]     
__________________________________________________________________________________________________
batch_normalization_16 (BatchNo (None, 52, 52, 128)  512         conv2d_16[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_16 (LeakyReLU)      (None, 52, 52, 128)  0           batch_normalization_16[0][0]     
__________________________________________________________________________________________________
conv2d_17 (Conv2D)              (None, 52, 52, 256)  294912      leaky_re_lu_16[0][0]             
__________________________________________________________________________________________________
batch_normalization_17 (BatchNo (None, 52, 52, 256)  1024        conv2d_17[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_17 (LeakyReLU)      (None, 52, 52, 256)  0           batch_normalization_17[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_6 (TFOpLam (None, 52, 52, 256)  0           tf.__operators__.add_5[0][0]     
                                                                 leaky_re_lu_17[0][0]             
__________________________________________________________________________________________________
conv2d_18 (Conv2D)              (None, 52, 52, 128)  32768       tf.__operators__.add_6[0][0]     
__________________________________________________________________________________________________
batch_normalization_18 (BatchNo (None, 52, 52, 128)  512         conv2d_18[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_18 (LeakyReLU)      (None, 52, 52, 128)  0           batch_normalization_18[0][0]     
__________________________________________________________________________________________________
conv2d_19 (Conv2D)              (None, 52, 52, 256)  294912      leaky_re_lu_18[0][0]             
__________________________________________________________________________________________________
batch_normalization_19 (BatchNo (None, 52, 52, 256)  1024        conv2d_19[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_19 (LeakyReLU)      (None, 52, 52, 256)  0           batch_normalization_19[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_7 (TFOpLam (None, 52, 52, 256)  0           tf.__operators__.add_6[0][0]     
                                                                 leaky_re_lu_19[0][0]             
__________________________________________________________________________________________________
conv2d_20 (Conv2D)              (None, 52, 52, 128)  32768       tf.__operators__.add_7[0][0]     
__________________________________________________________________________________________________
batch_normalization_20 (BatchNo (None, 52, 52, 128)  512         conv2d_20[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_20 (LeakyReLU)      (None, 52, 52, 128)  0           batch_normalization_20[0][0]     
__________________________________________________________________________________________________
conv2d_21 (Conv2D)              (None, 52, 52, 256)  294912      leaky_re_lu_20[0][0]             
__________________________________________________________________________________________________
batch_normalization_21 (BatchNo (None, 52, 52, 256)  1024        conv2d_21[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_21 (LeakyReLU)      (None, 52, 52, 256)  0           batch_normalization_21[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_8 (TFOpLam (None, 52, 52, 256)  0           tf.__operators__.add_7[0][0]     
                                                                 leaky_re_lu_21[0][0]             
__________________________________________________________________________________________________
conv2d_22 (Conv2D)              (None, 52, 52, 128)  32768       tf.__operators__.add_8[0][0]     
__________________________________________________________________________________________________
batch_normalization_22 (BatchNo (None, 52, 52, 128)  512         conv2d_22[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_22 (LeakyReLU)      (None, 52, 52, 128)  0           batch_normalization_22[0][0]     
__________________________________________________________________________________________________
conv2d_23 (Conv2D)              (None, 52, 52, 256)  294912      leaky_re_lu_22[0][0]             
__________________________________________________________________________________________________
batch_normalization_23 (BatchNo (None, 52, 52, 256)  1024        conv2d_23[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_23 (LeakyReLU)      (None, 52, 52, 256)  0           batch_normalization_23[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_9 (TFOpLam (None, 52, 52, 256)  0           tf.__operators__.add_8[0][0]     
                                                                 leaky_re_lu_23[0][0]             
__________________________________________________________________________________________________
conv2d_24 (Conv2D)              (None, 52, 52, 128)  32768       tf.__operators__.add_9[0][0]     
__________________________________________________________________________________________________
batch_normalization_24 (BatchNo (None, 52, 52, 128)  512         conv2d_24[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_24 (LeakyReLU)      (None, 52, 52, 128)  0           batch_normalization_24[0][0]     
__________________________________________________________________________________________________
conv2d_25 (Conv2D)              (None, 52, 52, 256)  294912      leaky_re_lu_24[0][0]             
__________________________________________________________________________________________________
batch_normalization_25 (BatchNo (None, 52, 52, 256)  1024        conv2d_25[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_25 (LeakyReLU)      (None, 52, 52, 256)  0           batch_normalization_25[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_10 (TFOpLa (None, 52, 52, 256)  0           tf.__operators__.add_9[0][0]     
                                                                 leaky_re_lu_25[0][0]             
__________________________________________________________________________________________________
zero_padding2d_3 (ZeroPadding2D (None, 53, 53, 256)  0           tf.__operators__.add_10[0][0]    
__________________________________________________________________________________________________
conv2d_26 (Conv2D)              (None, 26, 26, 512)  1179648     zero_padding2d_3[0][0]           
__________________________________________________________________________________________________
batch_normalization_26 (BatchNo (None, 26, 26, 512)  2048        conv2d_26[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_26 (LeakyReLU)      (None, 26, 26, 512)  0           batch_normalization_26[0][0]     
__________________________________________________________________________________________________
conv2d_27 (Conv2D)              (None, 26, 26, 256)  131072      leaky_re_lu_26[0][0]             
__________________________________________________________________________________________________
batch_normalization_27 (BatchNo (None, 26, 26, 256)  1024        conv2d_27[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_27 (LeakyReLU)      (None, 26, 26, 256)  0           batch_normalization_27[0][0]     
__________________________________________________________________________________________________
conv2d_28 (Conv2D)              (None, 26, 26, 512)  1179648     leaky_re_lu_27[0][0]             
__________________________________________________________________________________________________
batch_normalization_28 (BatchNo (None, 26, 26, 512)  2048        conv2d_28[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_28 (LeakyReLU)      (None, 26, 26, 512)  0           batch_normalization_28[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_11 (TFOpLa (None, 26, 26, 512)  0           leaky_re_lu_26[0][0]             
                                                                 leaky_re_lu_28[0][0]             
__________________________________________________________________________________________________
conv2d_29 (Conv2D)              (None, 26, 26, 256)  131072      tf.__operators__.add_11[0][0]    
__________________________________________________________________________________________________
batch_normalization_29 (BatchNo (None, 26, 26, 256)  1024        conv2d_29[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_29 (LeakyReLU)      (None, 26, 26, 256)  0           batch_normalization_29[0][0]     
__________________________________________________________________________________________________
conv2d_30 (Conv2D)              (None, 26, 26, 512)  1179648     leaky_re_lu_29[0][0]             
__________________________________________________________________________________________________
batch_normalization_30 (BatchNo (None, 26, 26, 512)  2048        conv2d_30[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_30 (LeakyReLU)      (None, 26, 26, 512)  0           batch_normalization_30[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_12 (TFOpLa (None, 26, 26, 512)  0           tf.__operators__.add_11[0][0]    
                                                                 leaky_re_lu_30[0][0]             
__________________________________________________________________________________________________
conv2d_31 (Conv2D)              (None, 26, 26, 256)  131072      tf.__operators__.add_12[0][0]    
__________________________________________________________________________________________________
batch_normalization_31 (BatchNo (None, 26, 26, 256)  1024        conv2d_31[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_31 (LeakyReLU)      (None, 26, 26, 256)  0           batch_normalization_31[0][0]     
__________________________________________________________________________________________________
conv2d_32 (Conv2D)              (None, 26, 26, 512)  1179648     leaky_re_lu_31[0][0]             
__________________________________________________________________________________________________
batch_normalization_32 (BatchNo (None, 26, 26, 512)  2048        conv2d_32[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_32 (LeakyReLU)      (None, 26, 26, 512)  0           batch_normalization_32[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_13 (TFOpLa (None, 26, 26, 512)  0           tf.__operators__.add_12[0][0]    
                                                                 leaky_re_lu_32[0][0]             
__________________________________________________________________________________________________
conv2d_33 (Conv2D)              (None, 26, 26, 256)  131072      tf.__operators__.add_13[0][0]    
__________________________________________________________________________________________________
batch_normalization_33 (BatchNo (None, 26, 26, 256)  1024        conv2d_33[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_33 (LeakyReLU)      (None, 26, 26, 256)  0           batch_normalization_33[0][0]     
__________________________________________________________________________________________________
conv2d_34 (Conv2D)              (None, 26, 26, 512)  1179648     leaky_re_lu_33[0][0]             
__________________________________________________________________________________________________
batch_normalization_34 (BatchNo (None, 26, 26, 512)  2048        conv2d_34[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_34 (LeakyReLU)      (None, 26, 26, 512)  0           batch_normalization_34[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_14 (TFOpLa (None, 26, 26, 512)  0           tf.__operators__.add_13[0][0]    
                                                                 leaky_re_lu_34[0][0]             
__________________________________________________________________________________________________
conv2d_35 (Conv2D)              (None, 26, 26, 256)  131072      tf.__operators__.add_14[0][0]    
__________________________________________________________________________________________________
batch_normalization_35 (BatchNo (None, 26, 26, 256)  1024        conv2d_35[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_35 (LeakyReLU)      (None, 26, 26, 256)  0           batch_normalization_35[0][0]     
__________________________________________________________________________________________________
conv2d_36 (Conv2D)              (None, 26, 26, 512)  1179648     leaky_re_lu_35[0][0]             
__________________________________________________________________________________________________
batch_normalization_36 (BatchNo (None, 26, 26, 512)  2048        conv2d_36[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_36 (LeakyReLU)      (None, 26, 26, 512)  0           batch_normalization_36[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_15 (TFOpLa (None, 26, 26, 512)  0           tf.__operators__.add_14[0][0]    
                                                                 leaky_re_lu_36[0][0]             
__________________________________________________________________________________________________
conv2d_37 (Conv2D)              (None, 26, 26, 256)  131072      tf.__operators__.add_15[0][0]    
__________________________________________________________________________________________________
batch_normalization_37 (BatchNo (None, 26, 26, 256)  1024        conv2d_37[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_37 (LeakyReLU)      (None, 26, 26, 256)  0           batch_normalization_37[0][0]     
__________________________________________________________________________________________________
conv2d_38 (Conv2D)              (None, 26, 26, 512)  1179648     leaky_re_lu_37[0][0]             
__________________________________________________________________________________________________
batch_normalization_38 (BatchNo (None, 26, 26, 512)  2048        conv2d_38[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_38 (LeakyReLU)      (None, 26, 26, 512)  0           batch_normalization_38[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_16 (TFOpLa (None, 26, 26, 512)  0           tf.__operators__.add_15[0][0]    
                                                                 leaky_re_lu_38[0][0]             
__________________________________________________________________________________________________
conv2d_39 (Conv2D)              (None, 26, 26, 256)  131072      tf.__operators__.add_16[0][0]    
__________________________________________________________________________________________________
batch_normalization_39 (BatchNo (None, 26, 26, 256)  1024        conv2d_39[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_39 (LeakyReLU)      (None, 26, 26, 256)  0           batch_normalization_39[0][0]     
__________________________________________________________________________________________________
conv2d_40 (Conv2D)              (None, 26, 26, 512)  1179648     leaky_re_lu_39[0][0]             
__________________________________________________________________________________________________
batch_normalization_40 (BatchNo (None, 26, 26, 512)  2048        conv2d_40[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_40 (LeakyReLU)      (None, 26, 26, 512)  0           batch_normalization_40[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_17 (TFOpLa (None, 26, 26, 512)  0           tf.__operators__.add_16[0][0]    
                                                                 leaky_re_lu_40[0][0]             
__________________________________________________________________________________________________
conv2d_41 (Conv2D)              (None, 26, 26, 256)  131072      tf.__operators__.add_17[0][0]    
__________________________________________________________________________________________________
batch_normalization_41 (BatchNo (None, 26, 26, 256)  1024        conv2d_41[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_41 (LeakyReLU)      (None, 26, 26, 256)  0           batch_normalization_41[0][0]     
__________________________________________________________________________________________________
conv2d_42 (Conv2D)              (None, 26, 26, 512)  1179648     leaky_re_lu_41[0][0]             
__________________________________________________________________________________________________
batch_normalization_42 (BatchNo (None, 26, 26, 512)  2048        conv2d_42[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_42 (LeakyReLU)      (None, 26, 26, 512)  0           batch_normalization_42[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_18 (TFOpLa (None, 26, 26, 512)  0           tf.__operators__.add_17[0][0]    
                                                                 leaky_re_lu_42[0][0]             
__________________________________________________________________________________________________
zero_padding2d_4 (ZeroPadding2D (None, 27, 27, 512)  0           tf.__operators__.add_18[0][0]    
__________________________________________________________________________________________________
conv2d_43 (Conv2D)              (None, 13, 13, 1024) 4718592     zero_padding2d_4[0][0]           
__________________________________________________________________________________________________
batch_normalization_43 (BatchNo (None, 13, 13, 1024) 4096        conv2d_43[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_43 (LeakyReLU)      (None, 13, 13, 1024) 0           batch_normalization_43[0][0]     
__________________________________________________________________________________________________
conv2d_44 (Conv2D)              (None, 13, 13, 512)  524288      leaky_re_lu_43[0][0]             
__________________________________________________________________________________________________
batch_normalization_44 (BatchNo (None, 13, 13, 512)  2048        conv2d_44[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_44 (LeakyReLU)      (None, 13, 13, 512)  0           batch_normalization_44[0][0]     
__________________________________________________________________________________________________
conv2d_45 (Conv2D)              (None, 13, 13, 1024) 4718592     leaky_re_lu_44[0][0]             
__________________________________________________________________________________________________
batch_normalization_45 (BatchNo (None, 13, 13, 1024) 4096        conv2d_45[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_45 (LeakyReLU)      (None, 13, 13, 1024) 0           batch_normalization_45[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_19 (TFOpLa (None, 13, 13, 1024) 0           leaky_re_lu_43[0][0]             
                                                                 leaky_re_lu_45[0][0]             
__________________________________________________________________________________________________
conv2d_46 (Conv2D)              (None, 13, 13, 512)  524288      tf.__operators__.add_19[0][0]    
__________________________________________________________________________________________________
batch_normalization_46 (BatchNo (None, 13, 13, 512)  2048        conv2d_46[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_46 (LeakyReLU)      (None, 13, 13, 512)  0           batch_normalization_46[0][0]     
__________________________________________________________________________________________________
conv2d_47 (Conv2D)              (None, 13, 13, 1024) 4718592     leaky_re_lu_46[0][0]             
__________________________________________________________________________________________________
batch_normalization_47 (BatchNo (None, 13, 13, 1024) 4096        conv2d_47[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_47 (LeakyReLU)      (None, 13, 13, 1024) 0           batch_normalization_47[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_20 (TFOpLa (None, 13, 13, 1024) 0           tf.__operators__.add_19[0][0]    
                                                                 leaky_re_lu_47[0][0]             
__________________________________________________________________________________________________
conv2d_48 (Conv2D)              (None, 13, 13, 512)  524288      tf.__operators__.add_20[0][0]    
__________________________________________________________________________________________________
batch_normalization_48 (BatchNo (None, 13, 13, 512)  2048        conv2d_48[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_48 (LeakyReLU)      (None, 13, 13, 512)  0           batch_normalization_48[0][0]     
__________________________________________________________________________________________________
conv2d_49 (Conv2D)              (None, 13, 13, 1024) 4718592     leaky_re_lu_48[0][0]             
__________________________________________________________________________________________________
batch_normalization_49 (BatchNo (None, 13, 13, 1024) 4096        conv2d_49[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_49 (LeakyReLU)      (None, 13, 13, 1024) 0           batch_normalization_49[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_21 (TFOpLa (None, 13, 13, 1024) 0           tf.__operators__.add_20[0][0]    
                                                                 leaky_re_lu_49[0][0]             
__________________________________________________________________________________________________
conv2d_50 (Conv2D)              (None, 13, 13, 512)  524288      tf.__operators__.add_21[0][0]    
__________________________________________________________________________________________________
batch_normalization_50 (BatchNo (None, 13, 13, 512)  2048        conv2d_50[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_50 (LeakyReLU)      (None, 13, 13, 512)  0           batch_normalization_50[0][0]     
__________________________________________________________________________________________________
conv2d_51 (Conv2D)              (None, 13, 13, 1024) 4718592     leaky_re_lu_50[0][0]             
__________________________________________________________________________________________________
batch_normalization_51 (BatchNo (None, 13, 13, 1024) 4096        conv2d_51[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_51 (LeakyReLU)      (None, 13, 13, 1024) 0           batch_normalization_51[0][0]     
__________________________________________________________________________________________________
tf.__operators__.add_22 (TFOpLa (None, 13, 13, 1024) 0           tf.__operators__.add_21[0][0]    
                                                                 leaky_re_lu_51[0][0]             
__________________________________________________________________________________________________
conv2d_52 (Conv2D)              (None, 13, 13, 512)  524288      tf.__operators__.add_22[0][0]    
__________________________________________________________________________________________________
batch_normalization_52 (BatchNo (None, 13, 13, 512)  2048        conv2d_52[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_52 (LeakyReLU)      (None, 13, 13, 512)  0           batch_normalization_52[0][0]     
__________________________________________________________________________________________________
conv2d_53 (Conv2D)              (None, 13, 13, 1024) 4718592     leaky_re_lu_52[0][0]             
__________________________________________________________________________________________________
batch_normalization_53 (BatchNo (None, 13, 13, 1024) 4096        conv2d_53[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_53 (LeakyReLU)      (None, 13, 13, 1024) 0           batch_normalization_53[0][0]     
__________________________________________________________________________________________________
conv2d_54 (Conv2D)              (None, 13, 13, 512)  524288      leaky_re_lu_53[0][0]             
__________________________________________________________________________________________________
batch_normalization_54 (BatchNo (None, 13, 13, 512)  2048        conv2d_54[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_54 (LeakyReLU)      (None, 13, 13, 512)  0           batch_normalization_54[0][0]     
__________________________________________________________________________________________________
conv2d_55 (Conv2D)              (None, 13, 13, 1024) 4718592     leaky_re_lu_54[0][0]             
__________________________________________________________________________________________________
batch_normalization_55 (BatchNo (None, 13, 13, 1024) 4096        conv2d_55[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_55 (LeakyReLU)      (None, 13, 13, 1024) 0           batch_normalization_55[0][0]     
__________________________________________________________________________________________________
conv2d_56 (Conv2D)              (None, 13, 13, 512)  524288      leaky_re_lu_55[0][0]             
__________________________________________________________________________________________________
batch_normalization_56 (BatchNo (None, 13, 13, 512)  2048        conv2d_56[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_56 (LeakyReLU)      (None, 13, 13, 512)  0           batch_normalization_56[0][0]     
__________________________________________________________________________________________________
conv2d_59 (Conv2D)              (None, 13, 13, 256)  131072      leaky_re_lu_56[0][0]             
__________________________________________________________________________________________________
batch_normalization_58 (BatchNo (None, 13, 13, 256)  1024        conv2d_59[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_58 (LeakyReLU)      (None, 13, 13, 256)  0           batch_normalization_58[0][0]     
__________________________________________________________________________________________________
tf.image.resize (TFOpLambda)    (None, 26, 26, 256)  0           leaky_re_lu_58[0][0]             
__________________________________________________________________________________________________
tf.concat (TFOpLambda)          (None, 26, 26, 768)  0           tf.image.resize[0][0]            
                                                                 tf.__operators__.add_18[0][0]    
__________________________________________________________________________________________________
conv2d_60 (Conv2D)              (None, 26, 26, 256)  196608      tf.concat[0][0]                  
__________________________________________________________________________________________________
batch_normalization_59 (BatchNo (None, 26, 26, 256)  1024        conv2d_60[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_59 (LeakyReLU)      (None, 26, 26, 256)  0           batch_normalization_59[0][0]     
__________________________________________________________________________________________________
conv2d_61 (Conv2D)              (None, 26, 26, 512)  1179648     leaky_re_lu_59[0][0]             
__________________________________________________________________________________________________
batch_normalization_60 (BatchNo (None, 26, 26, 512)  2048        conv2d_61[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_60 (LeakyReLU)      (None, 26, 26, 512)  0           batch_normalization_60[0][0]     
__________________________________________________________________________________________________
conv2d_62 (Conv2D)              (None, 26, 26, 256)  131072      leaky_re_lu_60[0][0]             
__________________________________________________________________________________________________
batch_normalization_61 (BatchNo (None, 26, 26, 256)  1024        conv2d_62[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_61 (LeakyReLU)      (None, 26, 26, 256)  0           batch_normalization_61[0][0]     
__________________________________________________________________________________________________
conv2d_63 (Conv2D)              (None, 26, 26, 512)  1179648     leaky_re_lu_61[0][0]             
__________________________________________________________________________________________________
batch_normalization_62 (BatchNo (None, 26, 26, 512)  2048        conv2d_63[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_62 (LeakyReLU)      (None, 26, 26, 512)  0           batch_normalization_62[0][0]     
__________________________________________________________________________________________________
conv2d_64 (Conv2D)              (None, 26, 26, 256)  131072      leaky_re_lu_62[0][0]             
__________________________________________________________________________________________________
batch_normalization_63 (BatchNo (None, 26, 26, 256)  1024        conv2d_64[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_63 (LeakyReLU)      (None, 26, 26, 256)  0           batch_normalization_63[0][0]     
__________________________________________________________________________________________________
conv2d_67 (Conv2D)              (None, 26, 26, 128)  32768       leaky_re_lu_63[0][0]             
__________________________________________________________________________________________________
batch_normalization_65 (BatchNo (None, 26, 26, 128)  512         conv2d_67[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_65 (LeakyReLU)      (None, 26, 26, 128)  0           batch_normalization_65[0][0]     
__________________________________________________________________________________________________
tf.image.resize_1 (TFOpLambda)  (None, 52, 52, 128)  0           leaky_re_lu_65[0][0]             
__________________________________________________________________________________________________
tf.concat_1 (TFOpLambda)        (None, 52, 52, 384)  0           tf.image.resize_1[0][0]          
                                                                 tf.__operators__.add_10[0][0]    
__________________________________________________________________________________________________
conv2d_68 (Conv2D)              (None, 52, 52, 128)  49152       tf.concat_1[0][0]                
__________________________________________________________________________________________________
batch_normalization_66 (BatchNo (None, 52, 52, 128)  512         conv2d_68[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_66 (LeakyReLU)      (None, 52, 52, 128)  0           batch_normalization_66[0][0]     
__________________________________________________________________________________________________
conv2d_69 (Conv2D)              (None, 52, 52, 256)  294912      leaky_re_lu_66[0][0]             
__________________________________________________________________________________________________
batch_normalization_67 (BatchNo (None, 52, 52, 256)  1024        conv2d_69[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_67 (LeakyReLU)      (None, 52, 52, 256)  0           batch_normalization_67[0][0]     
__________________________________________________________________________________________________
conv2d_70 (Conv2D)              (None, 52, 52, 128)  32768       leaky_re_lu_67[0][0]             
__________________________________________________________________________________________________
batch_normalization_68 (BatchNo (None, 52, 52, 128)  512         conv2d_70[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_68 (LeakyReLU)      (None, 52, 52, 128)  0           batch_normalization_68[0][0]     
__________________________________________________________________________________________________
conv2d_71 (Conv2D)              (None, 52, 52, 256)  294912      leaky_re_lu_68[0][0]             
__________________________________________________________________________________________________
batch_normalization_69 (BatchNo (None, 52, 52, 256)  1024        conv2d_71[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_69 (LeakyReLU)      (None, 52, 52, 256)  0           batch_normalization_69[0][0]     
__________________________________________________________________________________________________
conv2d_72 (Conv2D)              (None, 52, 52, 128)  32768       leaky_re_lu_69[0][0]             
__________________________________________________________________________________________________
batch_normalization_70 (BatchNo (None, 52, 52, 128)  512         conv2d_72[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_70 (LeakyReLU)      (None, 52, 52, 128)  0           batch_normalization_70[0][0]     
__________________________________________________________________________________________________
conv2d_73 (Conv2D)              (None, 52, 52, 256)  294912      leaky_re_lu_70[0][0]             
__________________________________________________________________________________________________
conv2d_65 (Conv2D)              (None, 26, 26, 512)  1179648     leaky_re_lu_63[0][0]             
__________________________________________________________________________________________________
conv2d_57 (Conv2D)              (None, 13, 13, 1024) 4718592     leaky_re_lu_56[0][0]             
__________________________________________________________________________________________________
batch_normalization_71 (BatchNo (None, 52, 52, 256)  1024        conv2d_73[0][0]                  
__________________________________________________________________________________________________
batch_normalization_64 (BatchNo (None, 26, 26, 512)  2048        conv2d_65[0][0]                  
__________________________________________________________________________________________________
batch_normalization_57 (BatchNo (None, 13, 13, 1024) 4096        conv2d_57[0][0]                  
__________________________________________________________________________________________________
leaky_re_lu_71 (LeakyReLU)      (None, 52, 52, 256)  0           batch_normalization_71[0][0]     
__________________________________________________________________________________________________
leaky_re_lu_64 (LeakyReLU)      (None, 26, 26, 512)  0           batch_normalization_64[0][0]     
__________________________________________________________________________________________________
leaky_re_lu_57 (LeakyReLU)      (None, 13, 13, 1024) 0           batch_normalization_57[0][0]     
__________________________________________________________________________________________________
conv2d_74 (Conv2D)              (None, 52, 52, 18)   4626        leaky_re_lu_71[0][0]             
__________________________________________________________________________________________________
conv2d_66 (Conv2D)              (None, 26, 26, 18)   9234        leaky_re_lu_64[0][0]             
__________________________________________________________________________________________________
conv2d_58 (Conv2D)              (None, 13, 13, 18)   18450       leaky_re_lu_57[0][0]             
__________________________________________________________________________________________________
tf.compat.v1.shape (TFOpLambda) (4,)                 0           conv2d_74[0][0]                  
__________________________________________________________________________________________________
tf.compat.v1.shape_1 (TFOpLambd (4,)                 0           conv2d_66[0][0]                  
__________________________________________________________________________________________________
tf.compat.v1.shape_2 (TFOpLambd (4,)                 0           conv2d_58[0][0]                  
__________________________________________________________________________________________________
tf.__operators__.getitem_1 (Sli ()                   0           tf.compat.v1.shape[0][0]         
__________________________________________________________________________________________________
tf.__operators__.getitem_5 (Sli ()                   0           tf.compat.v1.shape_1[0][0]       
__________________________________________________________________________________________________
tf.__operators__.getitem_9 (Sli ()                   0           tf.compat.v1.shape_2[0][0]       
__________________________________________________________________________________________________
tf.range (TFOpLambda)           (None,)              0           tf.__operators__.getitem_1[0][0] 
__________________________________________________________________________________________________
tf.range_1 (TFOpLambda)         (None,)              0           tf.__operators__.getitem_1[0][0] 
__________________________________________________________________________________________________
tf.range_2 (TFOpLambda)         (None,)              0           tf.__operators__.getitem_5[0][0] 
__________________________________________________________________________________________________
tf.range_3 (TFOpLambda)         (None,)              0           tf.__operators__.getitem_5[0][0] 
__________________________________________________________________________________________________
tf.range_4 (TFOpLambda)         (None,)              0           tf.__operators__.getitem_9[0][0] 
__________________________________________________________________________________________________
tf.range_5 (TFOpLambda)         (None,)              0           tf.__operators__.getitem_9[0][0] 
__________________________________________________________________________________________________
tf.meshgrid (TFOpLambda)        [(None, None), (None 0           tf.range[0][0]                   
                                                                 tf.range_1[0][0]                 
__________________________________________________________________________________________________
tf.meshgrid_1 (TFOpLambda)      [(None, None), (None 0           tf.range_2[0][0]                 
                                                                 tf.range_3[0][0]                 
__________________________________________________________________________________________________
tf.meshgrid_2 (TFOpLambda)      [(None, None), (None 0           tf.range_4[0][0]                 
                                                                 tf.range_5[0][0]                 
__________________________________________________________________________________________________
tf.stack_2 (TFOpLambda)         (None, None, 2)      0           tf.meshgrid[0][0]                
                                                                 tf.meshgrid[0][1]                
__________________________________________________________________________________________________
tf.stack_5 (TFOpLambda)         (None, None, 2)      0           tf.meshgrid_1[0][0]              
                                                                 tf.meshgrid_1[0][1]              
__________________________________________________________________________________________________
tf.stack_8 (TFOpLambda)         (None, None, 2)      0           tf.meshgrid_2[0][0]              
                                                                 tf.meshgrid_2[0][1]              
__________________________________________________________________________________________________
tf.__operators__.getitem (Slici ()                   0           tf.compat.v1.shape[0][0]         
__________________________________________________________________________________________________
tf.expand_dims (TFOpLambda)     (None, None, 1, 2)   0           tf.stack_2[0][0]                 
__________________________________________________________________________________________________
tf.__operators__.getitem_4 (Sli ()                   0           tf.compat.v1.shape_1[0][0]       
__________________________________________________________________________________________________
tf.expand_dims_2 (TFOpLambda)   (None, None, 1, 2)   0           tf.stack_5[0][0]                 
__________________________________________________________________________________________________
tf.__operators__.getitem_8 (Sli ()                   0           tf.compat.v1.shape_2[0][0]       
__________________________________________________________________________________________________
tf.expand_dims_4 (TFOpLambda)   (None, None, 1, 2)   0           tf.stack_8[0][0]                 
__________________________________________________________________________________________________
tf.reshape (TFOpLambda)         (None, None, None, 3 0           conv2d_74[0][0]                  
                                                                 tf.__operators__.getitem[0][0]   
                                                                 tf.__operators__.getitem_1[0][0] 
                                                                 tf.__operators__.getitem_1[0][0] 
__________________________________________________________________________________________________
tf.expand_dims_1 (TFOpLambda)   (1, None, None, 1, 2 0           tf.expand_dims[0][0]             
__________________________________________________________________________________________________
tf.reshape_3 (TFOpLambda)       (None, None, None, 3 0           conv2d_66[0][0]                  
                                                                 tf.__operators__.getitem_4[0][0] 
                                                                 tf.__operators__.getitem_5[0][0] 
                                                                 tf.__operators__.getitem_5[0][0] 
__________________________________________________________________________________________________
tf.expand_dims_3 (TFOpLambda)   (1, None, None, 1, 2 0           tf.expand_dims_2[0][0]           
__________________________________________________________________________________________________
tf.reshape_6 (TFOpLambda)       (None, None, None, 3 0           conv2d_58[0][0]                  
                                                                 tf.__operators__.getitem_8[0][0] 
                                                                 tf.__operators__.getitem_9[0][0] 
                                                                 tf.__operators__.getitem_9[0][0] 
__________________________________________________________________________________________________
tf.expand_dims_5 (TFOpLambda)   (1, None, None, 1, 2 0           tf.expand_dims_4[0][0]           
__________________________________________________________________________________________________
tf.split (TFOpLambda)           [(None, None, None,  0           tf.reshape[0][0]                 
__________________________________________________________________________________________________
tf.tile (TFOpLambda)            (None, None, None, 3 0           tf.expand_dims_1[0][0]           
                                                                 tf.__operators__.getitem[0][0]   
__________________________________________________________________________________________________
tf.split_1 (TFOpLambda)         [(None, None, None,  0           tf.reshape_3[0][0]               
__________________________________________________________________________________________________
tf.tile_1 (TFOpLambda)          (None, None, None, 3 0           tf.expand_dims_3[0][0]           
                                                                 tf.__operators__.getitem_4[0][0] 
__________________________________________________________________________________________________
tf.split_2 (TFOpLambda)         [(None, None, None,  0           tf.reshape_6[0][0]               
__________________________________________________________________________________________________
tf.tile_2 (TFOpLambda)          (None, None, None, 3 0           tf.expand_dims_5[0][0]           
                                                                 tf.__operators__.getitem_8[0][0] 
__________________________________________________________________________________________________
tf.math.sigmoid (TFOpLambda)    (None, None, None, 3 0           tf.split[0][0]                   
__________________________________________________________________________________________________
tf.cast (TFOpLambda)            (None, None, None, 3 0           tf.tile[0][0]                    
__________________________________________________________________________________________________
tf.math.exp (TFOpLambda)        (None, None, None, 3 0           tf.split[0][1]                   
__________________________________________________________________________________________________
tf.math.sigmoid_3 (TFOpLambda)  (None, None, None, 3 0           tf.split_1[0][0]                 
__________________________________________________________________________________________________
tf.cast_1 (TFOpLambda)          (None, None, None, 3 0           tf.tile_1[0][0]                  
__________________________________________________________________________________________________
tf.math.exp_1 (TFOpLambda)      (None, None, None, 3 0           tf.split_1[0][1]                 
__________________________________________________________________________________________________
tf.math.sigmoid_6 (TFOpLambda)  (None, None, None, 3 0           tf.split_2[0][0]                 
__________________________________________________________________________________________________
tf.cast_2 (TFOpLambda)          (None, None, None, 3 0           tf.tile_2[0][0]                  
__________________________________________________________________________________________________
tf.math.exp_2 (TFOpLambda)      (None, None, None, 3 0           tf.split_2[0][1]                 
__________________________________________________________________________________________________
tf.__operators__.add_23 (TFOpLa (None, None, None, 3 0           tf.math.sigmoid[0][0]            
                                                                 tf.cast[0][0]                    
__________________________________________________________________________________________________
tf.math.multiply_1 (TFOpLambda) (None, None, None, 3 0           tf.math.exp[0][0]                
__________________________________________________________________________________________________
tf.__operators__.add_24 (TFOpLa (None, None, None, 3 0           tf.math.sigmoid_3[0][0]          
                                                                 tf.cast_1[0][0]                  
__________________________________________________________________________________________________
tf.math.multiply_4 (TFOpLambda) (None, None, None, 3 0           tf.math.exp_1[0][0]              
__________________________________________________________________________________________________
tf.__operators__.add_25 (TFOpLa (None, None, None, 3 0           tf.math.sigmoid_6[0][0]          
                                                                 tf.cast_2[0][0]                  
__________________________________________________________________________________________________
tf.math.multiply_7 (TFOpLambda) (None, None, None, 3 0           tf.math.exp_2[0][0]              
__________________________________________________________________________________________________
tf.math.multiply (TFOpLambda)   (None, None, None, 3 0           tf.__operators__.add_23[0][0]    
__________________________________________________________________________________________________
tf.math.multiply_2 (TFOpLambda) (None, None, None, 3 0           tf.math.multiply_1[0][0]         
__________________________________________________________________________________________________
tf.math.multiply_3 (TFOpLambda) (None, None, None, 3 0           tf.__operators__.add_24[0][0]    
__________________________________________________________________________________________________
tf.math.multiply_5 (TFOpLambda) (None, None, None, 3 0           tf.math.multiply_4[0][0]         
__________________________________________________________________________________________________
tf.math.multiply_6 (TFOpLambda) (None, None, None, 3 0           tf.__operators__.add_25[0][0]    
__________________________________________________________________________________________________
tf.math.multiply_8 (TFOpLambda) (None, None, None, 3 0           tf.math.multiply_7[0][0]         
__________________________________________________________________________________________________
tf.concat_2 (TFOpLambda)        (None, None, None, 3 0           tf.math.multiply[0][0]           
                                                                 tf.math.multiply_2[0][0]         
__________________________________________________________________________________________________
tf.math.sigmoid_1 (TFOpLambda)  (None, None, None, 3 0           tf.split[0][2]                   
__________________________________________________________________________________________________
tf.math.sigmoid_2 (TFOpLambda)  (None, None, None, 3 0           tf.split[0][3]                   
__________________________________________________________________________________________________
tf.concat_4 (TFOpLambda)        (None, None, None, 3 0           tf.math.multiply_3[0][0]         
                                                                 tf.math.multiply_5[0][0]         
__________________________________________________________________________________________________
tf.math.sigmoid_4 (TFOpLambda)  (None, None, None, 3 0           tf.split_1[0][2]                 
__________________________________________________________________________________________________
tf.math.sigmoid_5 (TFOpLambda)  (None, None, None, 3 0           tf.split_1[0][3]                 
__________________________________________________________________________________________________
tf.concat_6 (TFOpLambda)        (None, None, None, 3 0           tf.math.multiply_6[0][0]         
                                                                 tf.math.multiply_8[0][0]         
__________________________________________________________________________________________________
tf.math.sigmoid_7 (TFOpLambda)  (None, None, None, 3 0           tf.split_2[0][2]                 
__________________________________________________________________________________________________
tf.math.sigmoid_8 (TFOpLambda)  (None, None, None, 3 0           tf.split_2[0][3]                 
__________________________________________________________________________________________________
tf.concat_3 (TFOpLambda)        (None, None, None, 3 0           tf.concat_2[0][0]                
                                                                 tf.math.sigmoid_1[0][0]          
                                                                 tf.math.sigmoid_2[0][0]          
__________________________________________________________________________________________________
tf.concat_5 (TFOpLambda)        (None, None, None, 3 0           tf.concat_4[0][0]                
                                                                 tf.math.sigmoid_4[0][0]          
                                                                 tf.math.sigmoid_5[0][0]          
__________________________________________________________________________________________________
tf.concat_7 (TFOpLambda)        (None, None, None, 3 0           tf.concat_6[0][0]                
                                                                 tf.math.sigmoid_7[0][0]          
                                                                 tf.math.sigmoid_8[0][0]          
==================================================================================================
Total params: 61,576,342
Trainable params: 61,523,734
Non-trainable params: 52,608
__________________________________________________________________________________________________
```

Hi,
The error
```
Either (1) select a slice where the `to_cut` corresponds to a single tensor, or (2) implement/use a `QoI` object that supports lists of tensors, i.e., where the parameter, `x`, to `__call__` is expected/allowed to be a list of 3 tensors.
```

implies that your model has 3 output tensors. In order to deal with this, you will need to use the DoI/QoI framework.

generally you need to be able to run gradients w.r.t. some output dy/dx. where y should be a scalar. (usually you do something like max(softmax) for multiclass. 

try:
```
from trulens.nn.attribution import InternalInfluence
from trulens.nn.distributions import LinearDoi
from trulens.nn.quantities import QoI
from trulens.nn.slices import Cut, InputCut, OutputCut, Slice

class MyQoI(QoI):
    def def __init__(self,*args):
        """
        save anything you need
        """

    def __call__(self, y: TensorLike) -> TensorLike:
         # y is your output tensors, you can add debug statements here to see what is coming here.
         # I assume you have 3 tensors here so here is some pseudocode - 
         return tf.max_idx(tf.softmax(y[idx_of_tensor_that_represents yhat output))


```
```
yolo = Load_Yolo_model() # yolo is <class 'tensorflow.python.keras.engine.functional.Functional'> object
model_wrapped = get_model_wrapper(yolo)

# The LinearDoi is equivalent to using integratedgradients
my_ig = InternalInfluence(model, 
    Slice(InputCut(), OutputCut()), 
    MyQoI(),
    LinearDoi(resolution=20))

with PIL.Image.open(image_path).convert('RGB') as img:
    x = np.array(img.resize((416, 416)))
    x_np = np.array(img.resize((416, 416), PIL.Image.ANTIALIAS))[np.newaxis]
    input_attributions = my_ig.attributions(x_np)
```

you could also replace the OutputCut in Slice with Cut(layer_name) where layer_name can come from model.summary()
The QoI call will get the output of that layer.

example:
```
my_ig = InternalInfluence(model, 
    Slice(InputCut(), Cut('tf.math.sigmoid_8')), 
    MyQoI(),
    LinearDoi(resolution=20))
```