```
cost = tf.reduce_mean(tf.keras.losses.categorical_crossentropy(y_true = labels,y_pred = logits,from_logits=True))
```

I am trying this code but it keeps showing

```
AssertionError: Test does not match. Did you get the mean of your cost functions?
```

can someone spot the error and guide me.

Thanks in advance.

Did you transpose the *labels* and *logits* first? The instructions tell you what the shapes need to be, which implies a transpose.

2 Likes

I did a transpose and still got the same error. Please what am I doing wrong?

*{moderator edit - solution code removed}*

```
cost -> tf.Tensor(0.4981846, shape=(), dtype=float32)
```

Then I got this error:

`AssertionError: Test does not match. Did you get the reduce sum of your cost functions?`

What you need there are transpose operations, not reshapes. Those are not the same thing, even if the shapes end up the same. Try it on a simple example and watch what happens. Transpose is a very specific mathematical operation.

1 Like

Hi, please, Iām having a similar problem. I did tf transposes on labels and logits, then crossentropy and then reduce sum, but I get tf.Tensor(1.6142862, shape=(), dtype=float32) and the same message: AssertionError: Test does not match. Did you get the reduce sum of your cost functions?

[SOLVED] I tried with different values for the two extra parameters of crossentropy and it worked with:

**from_logits=True**