Working on cell 10 in machine learning for classifying cats and dogs. I have been going around in circles trying to get the probabilities into the right form so I can pass them into plot images, but I am now so lost I can’t think straight. At one time I could print the probabilities and they were tuples so I could then use them to predict, but I tweaked some of the numbers in the model, and now I get a bunch of 1.0.

Can someone help me out here? I’m getting frustrated and need a point in the right direction.

**Your code so far**

```
probability_model = tf.keras.Sequential([model, tf.keras.layers.Softmax()])
print(type(probability_model))
predictions = probability_model.predict(test_data_gen)#predictions is numpy.ndarray
probabilities = []#type=array
for p in predictions:
print(np.round(p))
probabilities.append((p))
print(predictions)
print(probabilities)
print(test_data_gen)
img = []
for i in test_data_gen[4]:
img.append(i)
#plotImages(img)
```

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**Challenge:** Cat and Dog Image Classifier

**Link to the challenge:**