parameters: (input_x, output, origin_shape=None, kernel_name="cus_fused_abs_max1")
return_statement: return tik_instance
docstring: CusFusedAbsMax1
docstring_summary: CusFusedAbsMax1
docstring_tokens: CusFusedAbsMax1
function: def cus_fused_abs_max1(input_x, output, origin_shape=None, kernel_name="cus_fused_abs_max1"):
      """CusFusedAbsMax1"""
      input_x_shape = input_x.get("shape")
      output_shape = output.get("shape")
      dtype = input_x.get("dtype")
  
      tik_instance = _get_tik_instance()
  
      ori_shape = tuple(origin_shape)
      input_info = (tuple(input_x_shape), dtype)
      input_x = tik_instance.Tensor("float32", input_x_shape, name="input_x", scope=tik.scope_gm)
      res = tik_instance.Tensor("float32", output_shape, name="res", scope=tik.scope_gm)
  
      _error_feedback(input_info)
  
      if input_info == ((1, 128, 128), "float32"):
          tik_instance, res = shape0(tik_instance, input_x_shape, input_x, res)
      elif input_info == ((2, 128, 128), "float32"):
          tik_instance, res = shape1(tik_instance, input_x_shape, ori_shape, input_x, res)
      elif input_info == ((4, 128, 128), "float32"):
          tik_instance, res = shape2(tik_instance, input_x_shape, input_x, res)
      elif input_info == ((8, 128, 128), "float32"):
          tik_instance, res = shape3(tik_instance, input_x_shape, ori_shape, input_x, res)
      elif input_info == ((16, 128, 128), "float32"):
          tik_instance, res = shape4(tik_instance, input_x_shape, input_x, res)
      elif input_info == ((32, 128, 128), "float32"):
          tik_instance, res = shape5(tik_instance, input_x_shape, input_x, res)
      elif input_info == ((5, 128, 128), "float32"):
          tik_instance, res = shape6(tik_instance, ori_shape, input_x, res)
      elif input_info == ((9, 128, 128), "float32"):
          tik_instance, res = shape7(tik_instance, input_x_shape, input_x, res)
      elif input_info == ((18, 128, 128), "float32"):
          tik_instance, res = shape8(tik_instance, input_x_shape, input_x, res)
      elif input_info == ((36, 128, 128), "float32"):
          tik_instance, res = shape9(tik_instance, input_x_shape, input_x, res)
      elif input_info == ((1, 64, 64), "float32"):
          tik_instance, res = shape10(tik_instance, input_x_shape, input_x, res)
      elif input_info == ((32, 64), "float32"):
          input_x = tik_instance.Tensor("float32", input_x_shape, name="input_x", scope=tik.scope_gm)
          res = tik_instance.Tensor("float32", output_shape, name="res", scope=tik.scope_gm)
          input_x_ub = tik_instance.Tensor("float32", (32 * 64,), name="input_x_ub", scope=tik.scope_ubuf)
          tik_instance.data_move(input_x_ub, input_x, 0, 1, 256, 0, 0)
          tik_instance.vmax(64, input_x_ub, input_x_ub, input_x_ub[1024], 16, 1, 1, 1, 8, 8, 8)
          tik_instance.vmax(64, input_x_ub, input_x_ub, input_x_ub[512], 8, 1, 1, 1, 8, 8, 8)
          tik_instance.vmax(64, input_x_ub, input_x_ub, input_x_ub[256], 4, 1, 1, 1, 8, 8, 8)
          tik_instance.vmax(64, input_x_ub, input_x_ub, input_x_ub[128], 2, 1, 1, 1, 8, 8, 8)
          tik_instance.vmax(64, input_x_ub, input_x_ub, input_x_ub[64], 1, 1, 1, 1, 8, 8, 8)
          tik_instance.data_move(res[0], input_x_ub, 0, 1, 1, 0, 0)
  
      tik_instance.BuildCCE(kernel_name=kernel_name, inputs=[input_x], outputs=[res])
      return tik_instance
function_tokens: def cus_fused_abs_max1 ( input_x , output , origin_shape = None , kernel_name = "cus_fused_abs_max1" ) : input_x_shape = input_x . get ( "shape" ) output_shape = output . get ( "shape" ) dtype = input_x . get ( "dtype" ) tik_instance = _get_tik_instance ( ) ori_shape = tuple ( origin_shape ) input_info = ( tuple ( input_x_shape ) , dtype ) input_x = tik_instance . Tensor ( "float32" , input_x_shape , name = "input_x" , scope = tik . scope_gm ) res = tik_instance . Tensor ( "float32" , output_shape , name = "res" , scope = tik . scope_gm ) _error_feedback ( input_info ) if input_info == ( ( 1 , 128 , 128 ) , "float32" ) : tik_instance , res = shape0 ( tik_instance , input_x_shape , input_x , res ) elif input_info == ( ( 2 , 128 , 128 ) , "float32" ) : tik_instance , res = shape1 ( tik_instance , input_x_shape , ori_shape , input_x , res ) elif input_info == ( ( 4 , 128 , 128 ) , "float32" ) : tik_instance , res = shape2 ( tik_instance , input_x_shape , input_x , res ) elif input_info == ( ( 8 , 128 , 128 ) , "float32" ) : tik_instance , res = shape3 ( tik_instance , input_x_shape , ori_shape , input_x , res ) elif input_info == ( ( 16 , 128 , 128 ) , "float32" ) : tik_instance , res = shape4 ( tik_instance , input_x_shape , input_x , res ) elif input_info == ( ( 32 , 128 , 128 ) , "float32" ) : tik_instance , res = shape5 ( tik_instance , input_x_shape , input_x , res ) elif input_info == ( ( 5 , 128 , 128 ) , "float32" ) : tik_instance , res = shape6 ( tik_instance , ori_shape , input_x , res ) elif input_info == ( ( 9 , 128 , 128 ) , "float32" ) : tik_instance , res = shape7 ( tik_instance , input_x_shape , input_x , res ) elif input_info == ( ( 18 , 128 , 128 ) , "float32" ) : tik_instance , res = shape8 ( tik_instance , input_x_shape , input_x , res ) elif input_info == ( ( 36 , 128 , 128 ) , "float32" ) : tik_instance , res = shape9 ( tik_instance , input_x_shape , input_x , res ) elif input_info == ( ( 1 , 64 , 64 ) , "float32" ) : tik_instance , res = shape10 ( tik_instance , input_x_shape , input_x , res ) elif input_info == ( ( 32 , 64 ) , "float32" ) : input_x = tik_instance . Tensor ( "float32" , input_x_shape , name = "input_x" , scope = tik . scope_gm ) res = tik_instance . Tensor ( "float32" , output_shape , name = "res" , scope = tik . scope_gm ) input_x_ub = tik_instance . Tensor ( "float32" , ( 32 * 64 , ) , name = "input_x_ub" , scope = tik . scope_ubuf ) tik_instance . data_move ( input_x_ub , input_x , 0 , 1 , 256 , 0 , 0 ) tik_instance . vmax ( 64 , input_x_ub , input_x_ub , input_x_ub [ 1024 ] , 16 , 1 , 1 , 1 , 8 , 8 , 8 ) tik_instance . vmax ( 64 , input_x_ub , input_x_ub , input_x_ub [ 512 ] , 8 , 1 , 1 , 1 , 8 , 8 , 8 ) tik_instance . vmax ( 64 , input_x_ub , input_x_ub , input_x_ub [ 256 ] , 4 , 1 , 1 , 1 , 8 , 8 , 8 ) tik_instance . vmax ( 64 , input_x_ub , input_x_ub , input_x_ub [ 128 ] , 2 , 1 , 1 , 1 , 8 , 8 , 8 ) tik_instance . vmax ( 64 , input_x_ub , input_x_ub , input_x_ub [ 64 ] , 1 , 1 , 1 , 1 , 8 , 8 , 8 ) tik_instance . data_move ( res [ 0 ] , input_x_ub , 0 , 1 , 1 , 0 , 0 ) tik_instance . BuildCCE ( kernel_name = kernel_name , inputs = [ input_x ] , outputs = [ res ] ) return tik_instance