o "j@sddlZddlZddlmZddlmZddlmZeejZ ia ia da da d ad Zgd Zd d ZddZdddZddZddZdS)N) get_logger)"retrive_unique_id_for_process_mesh)_get_idx_in_axisF*) %IcCstS)N_enable_random_controlrrh/var/www/html/Deteccion_Ine/venv/lib/python3.10/site-packages/paddle/distributed/auto_parallel/random.pyis_enable_auto_rand_ctrl#srcCsdadS)NTrrrrrenable_auto_rand_ctrl(srcCst|a|adS)aEnable auto parallel random control. Random control maintain the randomness when tensor is distributed across devices on a Mesh(any order). * Independency: If tensor is **Sharded** on a Mesh dimension, Devices along that Mesh dimension should have Different randomness. * Consistency: Meanwhile if the tensor is **Replicated** on another Mesh dimension, randomness of Devices along that Mesh dimension should be Consistent. For instance: rank0 ~ rank7 consist a Mesh of shape of [2, 4]; A 2D tensor is distributed in that Mesh using dims_mapping [-1, 1]. Randomness for rank0-rank1-rank2-rank3 (rank4-rank5-rank6-rank7) should be Independent; Randomness for rank0 and rank4 (rank1 and rank5, ...) should be Consistent. This function should be called only once before auto parallel compiles the computation graph (e.g. auto_parallel.engine.prepare() or fit()). This seed only affects how randomness-relative **operators** (dropout, fuse op with dropout inside, etc) are execute amonge mesh, and would NOT affect other processe like Parameter initialization. Examples: # seed relative to training step auto_parallel_random_seed((step + 13) * 257) ... engine.prepare() N)r _basic_seed _basic_name)seednamerrrparallel_manual_seed-src Cst|jdkrtdt|t}t}|r|d7}t|j|j}|d|}|t |d7}t t|jD]&}||vr@d}n t |j|j||}|d|d|7}|t ||d7}q7|t vrlt ||ksjJ|S|t vs{Jd ||t |t |<|S) NzIAuto Parallel Random Control for Mesh's rank > 4 is NOT supported! Got {}_zmesh:rZ_dim:zMSeed Confilt! current seed: {}, current sharding expr: {}, generated seed: {})lenshapeNotImplementedErrorformatstrrrrZ process_ids _mesh_offsetranger _dim_offsets_rng_name_to_seedvalues) rankZ dims_mapping process_meshZseed_Zname_ unique_idZ sharding_expriZ relative_idxrrrdeterminate_rngJsH r+cCshtsdStD](\}}|tvrt||ksJq td|d|tjj |||t|<q dS)NzInit Auto Parallel RNG: z , with seed ) rr%items_inited_rng_name_to_seed_loggerinfopaddleZ frameworkrandomZset_random_seed_generator)Zrng_namerrrrinit_auto_parallel_rngs r2)r)loggingr0Zutils.log_utilsrr(rZ static.utilsrINFOr.r%r-rrrr"r$rrrr+r2rrrrs$       6