2Vh 6dZddlZddlmZddZdZdZdZy) z!!!DO NOT USE!!! Distribution related class for Tensorflow backend. This is just a prototype and we might want to unify it with other backends in the future. N)dtensorc|r|jnd}tjj|}g}g}|D]B}|jj dk(r|j |2|j |D|t|dkDr|n|}|Dcgc]=}|jj d|jjdd?c}Scc}w)aReturn all the available devices based on the device type. Note that this should return the global devices in a distributed setting. Args: device_type: string of `"cpu"`, `"gpu"` or `"tpu"`. Default to `gpu` or `tpu` if available when device_type is not provided. Otherwise will return the `cpu` devices. Return: List of devices that are available for distribute computation. N) device_typecpur:) uppertfconfiglist_logical_devicesrlowerappendlennamesplit)r tf_devices cpu_devices other_devicesdevices ]/home/dcms/DCMS/lib/python3.12/site-packages/keras/src/backend/tensorflow/distribution_lib.py list_devicesr s*5+##%$K //K/HJKM)    # # % .   v &   ( ) &)-&81&<]+ !      # # % &a (9(9#(>r(B'CD  sACcyN)value tensor_layouts rdistribute_valuer0sctt|j|j}t j ||j jS)zConvert the DeviceMesh to Tensorflow backend specific Mesh. Args: device_mesh: DeviceMesh instance to convert. Returns: A `tf.dtensor.Mesh` instance. ) mesh_dims local_devices)listzip axis_namesshapercreate_distributed_meshdevicesflatten) device_meshr s r_to_backend_meshr*5sHS//1B1BCDI  * *;+>+>+F+F+H rc|j td|jDcgc]}|r|ntj}}|jj }tj ||Scc}w)zConvert the TensorLayout to Tensorflow backend specific Sharding. Args: tensor_layout: TensorLayout instance to convert. Returns: A `tf.dtensor.Layout` instance. zDCannot create sharding when device mesh is not set for TensorLayout.)sharding_specsmesh)r) ValueErroraxesr UNSHARDED backend_meshLayout)raxisr, dtensor_meshs r_to_backend_layoutr5Ds{  (   9F8J8J04'+++N!,,99L >>l KK sA0r) __doc__ tensorflowr tensorflow.experimentalrrrr*r5rrrr9s(+ F Lr