Hello. Is there any useful documentation I can take a look at to help me return the metrics as a numpy numeric type?

Thank you.

Hello. Is there any useful documentation I can take a look at to help me return the metrics as a numpy numeric type?

Thank you.

There’s a flag called `run_eagerly`

in Model `compile`

method. You can set this to `True`

and get a hold of numpy arrays if they’re passed as inputs. Use this to return numpy type output as well. Here’s an example

```
xs = np.asarray(...)
ys = np.asarray(...)
def custom_mean_absolute_error(y_true, y_pred):
return np.mean(np.abs(y_true - y_pred))
model = Model(...)
model.compile(loss=...,
optimizer=...,
run_eagerly=True,
metrics=[custom_mean_absolute_error, ...])
model.fit(xs, ys, epochs=...)
```

If you want to return the result of an existing metric funciton output as numpy, use `.numpy()`

after it.

Here’s an example:

`tf.keras.metrics.mean_squared_error(...).numpy()`