I’m not getting something here. I reproduced a segment of code from my notebook. This is for the **linear_activation_forward** function for the linear->activation layer in an N-layer deep neural network.

if activation == “sigmoid”:

#(≈ 2 lines of code)

# Z, linear_cache = …

# A, activation_cache = …

```
# YOUR CODE STARTS HERE
Moderator Edit: Solution code Removed
# YOUR CODE ENDS HERE
```

With sigmoid: A = (array([[0.96890023, 0.11013289]]), array([[ 3.43896131, -2.08938436]]))

With ReLU: A = (array([[3.43896131, 0. ]]), array([[ 3.43896131, -2.08938436]]))

Error: Datatype mismatch with sigmoid activation in variable 0. Got type: <class ‘numpy.ndarray’> but expected type <class ‘tuple’>

Error: Wrong shape with sigmoid activation for variable 0.

Error: Wrong shape with sigmoid activation for variable 0.

Error: Wrong shape with sigmoid activation for variable 1.

Error: Wrong shape with sigmoid activation for variable 2.

Error: Wrong shape with sigmoid activation for variable 1.

Error: Wrong output with sigmoid activation for variable 0.

Error: Wrong output with sigmoid activation for variable 0.

Error: Wrong output with sigmoid activation for variable 1.

Error: Wrong output with sigmoid activation for variable 2.

Error: Wrong output with sigmoid activation for variable 1.

Error: Datatype mismatch with relu activation in variable 0. Got type: <class ‘numpy.ndarray’> but expected type <class ‘tuple’>

Error: Wrong shape with relu activation for variable 0.

Error: Wrong shape with relu activation for variable 0.

Error: Wrong shape with relu activation for variable 1.

Error: Wrong shape with relu activation for variable 2.

Error: Wrong shape with relu activation for variable 1.

Error: Wrong output with relu activation for variable 0.

Error: Wrong output with relu activation for variable 0.

Error: Wrong output with relu activation for variable 1.

Error: Wrong output with relu activation for variable 2.

Error: Wrong output with relu activation for variable 1.

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