# tf.keras.backend.shape

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| [![](https://www.tensorflow.org/images/tf_logo_32px.png) TensorFlow 1 version](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/backend/shape) | [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.0.0/tensorflow/python/keras/backend.py#L1129-L1159) |

Returns the symbolic shape of a tensor or variable.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.keras.backend.shape`](https://www.tensorflow.org/api_docs/python/tf/keras/backend/shape)

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    tf.keras.backend.shape(
        x
    )

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| ## Arguments ||
|---|---|
| `x` | A tensor or variable. |

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| ## Returns ||
|---|---|
| A symbolic shape (which is itself a tensor). ||

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#### Examples:

        # TensorFlow example
        >>> from keras import backend as K
        >>> tf_session = K.get_session()
        >>> val = np.array([[1, 2], [3, 4]])
        >>> kvar = K.variable(value=val)
        >>> input = keras.backend.placeholder(shape=(2, 4, 5))
        >>> K.shape(kvar)
        <tf.Tensor 'Shape_8:0' shape=(2,) dtype=int32>
        >>> K.shape(input)
        <tf.Tensor 'Shape_9:0' shape=(3,) dtype=int32>
        # To get integer shape (Instead, you can use K.int_shape(x))
        >>> K.shape(kvar).eval(session=tf_session)
        array([2, 2], dtype=int32)
        >>> K.shape(input).eval(session=tf_session)
        array([2, 4, 5], dtype=int32)