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jax.numpy.ravel

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jax.numpy.ravel#

jax.numpy.ravel(a, order='C')[source]#

Flatten array into a 1-dimensional shape.

JAX implementation of numpy.ravel(), implemented in terms of jax.lax.reshape().

ravel(arr, order=order) is equivalent to reshape(arr, -1, order=order).

Parameters:

  • a (jax.typing.ArrayLike) – array to be flattened.

  • order (str) – 'F' or 'C', specifies whether the reshape should apply column-major (fortran-style, "F") or row-major (C-style, "C") order; default is "C". JAX does not support order=”A” or order=”K”.

Returns:

flattened copy of input array.

Return type:

Array

Notes

Unlike numpy.ravel(), jax.numpy.ravel() will return a copy rather than a view of the input array. However, under JIT, the compiler will optimize-away such copies when possible, so this doesn’t have performance impacts in practice.

See also

  • jax.Array.ravel(): equivalent functionality via an array method.

  • jax.numpy.reshape(): general array reshape.

Examples

>>> x = jnp.array([[1, 2, 3],
...                [4, 5, 6]])

By default, ravel in C-style, row-major order

>>> jnp.ravel(x)
Array([1, 2, 3, 4, 5, 6], dtype=int32)

Optionally ravel in Fortran-style, column-major:

>>> jnp.ravel(x, order='F')
Array([1, 4, 2, 5, 3, 6], dtype=int32)

For convenience, the same functionality is availabel via the jax.Array.ravel() method:

>>> x.ravel()
Array([1, 2, 3, 4, 5, 6], dtype=int32)
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