{
  "torch_npu": 
  {
    "v2.1": [],
    "v2.5": [],
    "v2.6": ["npu_gelu_mul", "npu_clipped_swiglu", "npu_sim_exponential_"],
    "v2.7": ["npu_gelu_mul", "npu_clipped_swiglu", "npu_sim_exponential_"],
    "v2.8": ["npu_gelu_mul", "npu_clipped_swiglu", "npu_sim_exponential_"],
    "v2.9": ["npu_gelu_mul", "npu_clipped_swiglu", "npu_sim_exponential_"],
    "v2.10": ["npu_gelu_mul", "npu_clipped_swiglu", "npu_sim_exponential_"],
    "all_version": [
      "_npu_dropout",
      "copy_memory_",
      "empty_with_format",
      "empty_with_swapped_memory",
      "npu_alloc_float_status",
      "npu_apply_adam",
      "npu_advance_step_flashattn",
      "npu_batch_gather_matmul",
      "npu_batch_gather_matmul_",
      "npu_bert_apply_adam",
      "npu_clear_float_status",
      "npu_cross_entropy_loss",
      "npu_format_cast_",
      "npu_fusion_attention",
      "npu_get_float_status",
      "npu_nms_rotated",
      "npu_random_choice_with_mask",
      "npu_rms_norm",
      "npu_add_rms_norm_cast",
      "npu_moe_compute_expert_tokens",
      "npu_fused_infer_attention_score",
      "npu_mla_prolog",
      "npu_mla_prolog_v2",
      "npu_mla_prolog_v3",
      "npu_mla_prolog_v3_functional",
      "npu_quant_lightning_indexer",
      "npu_lightning_indexer",
      "npu_sparse_flash_attention",
      "npu_lightning_indexer_grad",
      "npu_sparse_flash_attention_grad",
      "npu_sparse_lightning_indexer_grad_kl_loss",
      "npu_kv_quant_sparse_flash_attention",
      "npu_convert_weight_to_int4pack",
      "npu_ffn",
      "npu_geglu",
      "npu_grouped_matmul",
      "npu_moe_finalize_routing",
      "npu_quant_matmul",
      "npu_quant_matmul_reduce_sum",
      "npu_quant_scatter",
      "npu_quantize",
      "npu_dequant_bias",
      "npu_group_quant",
      "npu_dynamic_quant",
      "npu_dynamic_quant_asymmetric",
      "npu_scatter_nd_update_",
      "npu_scatter_pa_kv_cache",
      "npu_stride_copy",
      "npu_gemma_rms_norm",
      "npu_dequant_swiglu_quant",
      "npu_swiglu",
      "npu_gelu",
      "npu_gelu_backward",
      "npu_all_gather_base_mm",
      "npu_mm_reduce_scatter_base",
      "npu_prefetch",
      "npu_quant_scatter_",
      "npu_trans_quant_param",
      "npu_top_k_top_p_sample",
      "scatter_update",
      "scatter_update_",
      "npu_kronecker_quant",
      "npu_group_norm_swish",
      "npu_mrope",
      "npu_grouped_matmul_finalize_routing",
      "npu_grouped_matmul_swiglu_quant_v2",
      "npu_recurrent_gated_delta_rule",
      "npu_recurrent_gated_delta_rule_functional",
      "npu_alltoallv_gmm",
      "npu_gmm_alltoallv",
      "npu_nsa_compress",
      "npu_nsa_compress_infer",
      "npu_nsa_compress_attention",
      "npu_nsa_compress_attention_infer",
      "npu_nsa_select_attention",
      "npu_nsa_select_attention_infer",
      "npu_transpose_batchmatmul",
      "npu_gather_sparse_index",
      "npu_moe_distribute_combine_add_rms_norm",
      "npu_moe_update_expert",
      "npu_dynamic_block_quant",
      "attention_worker_scheduler_",
      "attention_worker_scheduler",
      "ffn_worker_scheduler_",
      "ffn_worker_scheduler"
    ]
  }
  
}