# TypeError: Could not interpret layer identifier: 'relu6'. Did you mean 'relu'?

- **ID:** `tensorflow/keras-layer-call-argument-mismatch`
- **Domain:** tensorflow
- **Category:** type_error
- **Error Code:** `EKLI`
- **Verification:** ai_generated
- **Fix Rate:** 90%

## Root Cause

The string identifier passed to a Keras layer (e.g., activation='relu6') is not a recognized activation function name; TensorFlow does not have a built-in 'relu6' activation.

## Version Compatibility

| Version | Status | Introduced | Deprecated |
|---------|--------|------------|------------|
| 2.4 | active | — | — |
| 2.5 | active | — | — |
| 2.6 | active | — | — |
| 2.7 | active | — | — |

## Workarounds

1. **Use the correct Keras activation: change 'relu6' to 'relu' if that works, or define a custom activation function: 'def relu6(x): return tf.nn.relu6(x)' and pass it as activation=relu6.** (95% success)
   ```
   Use the correct Keras activation: change 'relu6' to 'relu' if that works, or define a custom activation function: 'def relu6(x): return tf.nn.relu6(x)' and pass it as activation=relu6.
   ```
2. **Import from tf.keras.activations: 'from tensorflow.keras.activations import relu6' if available, but note that relu6 is not in the public API; use tf.nn.relu6 directly in a Lambda layer.** (80% success)
   ```
   Import from tf.keras.activations: 'from tensorflow.keras.activations import relu6' if available, but note that relu6 is not in the public API; use tf.nn.relu6 directly in a Lambda layer.
   ```

## Dead Ends

- **Use 'relu6' as a custom activation function without registering it** — Keras only recognizes registered activations; passing an unregistered string will always raise this error. (100% fail)
- **Spell it as 'ReLU6' with different capitalization** — Keras activation names are case-insensitive but must match exactly; 'ReLU6' is also not a built-in activation. (90% fail)