# tf.experimental.numpy.array

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/numpy_ops/np_array_ops.py#L196-L206) |

TensorFlow variant of NumPy's `array`.

    tf.experimental.numpy.array(
        val, dtype=None, copy=True, ndmin=0
    )

Since Tensors are immutable, a copy is made only if val is placed on a

different device than the current one. Even if `copy` is False, a new Tensor
may need to be built to satisfy `dtype` and `ndim`. This is used only if `val`
is an ndarray or a Tensor.

See the NumPy documentation for [`numpy.array`](https://numpy.org/doc/1.16/reference/generated/numpy.array.html).