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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/keras-team/keras/tree/v2.15.0/keras/backend.py#L1289-L1350) |

Returns whether `x` is a Keras tensor.

    tf.keras.backend.is_keras_tensor(
        x
    )

A "Keras tensor" is a tensor that was returned by a Keras layer,
(`Layer` class) or by `Input`.

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| ## Args ||
|---|---|
| `x` | A candidate tensor. |

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| ## Returns ||
|---|---|
| A boolean: Whether the argument is a Keras tensor. ||

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| ## Raises ||
|---|---|
| `ValueError` | In case `x` is not a symbolic tensor. |

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#### Examples:

    np_var = np.array([1, 2])
    # A numpy array is not a symbolic tensor.
    tf.keras.backend.is_keras_tensor(np_var)
    Traceback (most recent call last):

    ValueError: Unexpectedly found an instance of type
    `<class 'numpy.ndarray'>`.
    Expected a symbolic tensor instance.
    keras_var = tf.keras.backend.variable(np_var)
    # A variable created with the keras backend is not a Keras tensor.
    tf.keras.backend.is_keras_tensor(keras_var)
    False
    keras_placeholder = tf.keras.backend.placeholder(shape=(2, 4, 5))
    # A placeholder is a Keras tensor.
    tf.keras.backend.is_keras_tensor(keras_placeholder)
    True
    keras_input = tf.keras.layers.Input([10])
    # An Input is a Keras tensor.
    tf.keras.backend.is_keras_tensor(keras_input)
    True
    keras_layer_output = tf.keras.layers.Dense(10)(keras_input)
    # Any Keras layer output is a Keras tensor.
    tf.keras.backend.is_keras_tensor(keras_layer_output)
    True