jax.numpy.frombuffer#

jax.numpy.frombuffer(buffer,dtype=<class'float'>,count=-1,offset=0)[source]#

Convert a buffer into a 1-D JAX array.

JAX implementation ofnumpy.frombuffer().

Parameters:

• buffer (bytes |Any) – an object containing the data. It must be either a bytes object witha length that is an integer multiple of the dtype element size, orit must be an object exporting thePython buffer interface.

• dtype (DTypeLike) – optional. Desired data type for the array. Default isfloat64.This specifies the dtype used to parse the buffer, but note that after parsing,64-bit values will be cast to 32-bit JAX arrays if thejax_enable_x64flag is set toFalse.

• count (int) – optional integer specifying the number of items to read from the buffer.If -1 (default), all items from the buffer are read.

• offset (int) – optional integer specifying the number of bytes to skip at the beginningof the buffer. Default is 0.

Returns:

A 1-D JAX array representing the interpreted data from the buffer.

Return type:

Array

See also

• jax.numpy.fromstring(): convert a string of text into 1-D JAX array.

Examples

Using a bytes buffer:

>>>buf=b"\x00\x01\x02\x03\x04">>>jnp.frombuffer(buf,dtype=jnp.uint8)Array([0, 1, 2, 3, 4], dtype=uint8)>>>jnp.frombuffer(buf,dtype=jnp.uint8,offset=1)Array([1, 2, 3, 4], dtype=uint8)

Constructing a JAX array via the Python buffer interface, using Python’sbuilt-inarray module.

>>>fromarrayimportarray>>>pybuffer=array('i',[0,1,2,3,4])>>>jnp.frombuffer(pybuffer,dtype=jnp.int32)Array([0, 1, 2, 3, 4], dtype=int32)