parameters: (dout, input_x, alpha, quant_max, dx, dalpha, neg_trunc,
                                                 channel_axis, kernel_name="fake_learned_scale_quant_perchannel_grad_d")
docstring: FakeLearnedScaleQuantPerChannelGradD
docstring_summary: FakeLearnedScaleQuantPerChannelGradD
docstring_tokens: FakeLearnedScaleQuantPerChannelGradD
function: def fake_learned_scale_quant_perchannel_grad_d(dout, input_x, alpha, quant_max, dx, dalpha, neg_trunc,
                                                 channel_axis, kernel_name="fake_learned_scale_quant_perchannel_grad_d"):
      """FakeLearnedScaleQuantPerChannelGradD"""
      dout_data, input_data, alpha_data, quant_max_data = \
          fake_learned_scale_quant_perchannel_grad_d_param(input_x, alpha, quant_max, channel_axis, kernel_name)
  
      res = fake_learned_scale_quant_perchannel_grad_d_compute(dout_data, input_data, alpha_data, quant_max_data,
                                                               neg_trunc, kernel_name)
  
      with tvm.target.cce():
          sch = generic.auto_schedule(res)
  
      tensor_list = [dout_data, input_data, alpha_data, quant_max_data] + list(res)
      config = {"print_ir": False,
                "name": kernel_name,
                "tensor_list": tensor_list}
  
      te.lang.cce.cce_build_code(sch, config)
function_tokens: def fake_learned_scale_quant_perchannel_grad_d ( dout , input_x , alpha , quant_max , dx , dalpha , neg_trunc , channel_axis , kernel_name = "fake_learned_scale_quant_perchannel_grad_d" ) : dout_data , input_data , alpha_data , quant_max_data = fake_learned_scale_quant_perchannel_grad_d_param ( input_x , alpha , quant_max , channel_axis , kernel_name ) res = fake_learned_scale_quant_perchannel_grad_d_compute ( dout_data , input_data , alpha_data , quant_max_data , neg_trunc , kernel_name ) with tvm . target . cce ( ) : sch = generic . auto_schedule ( res ) tensor_list = [ dout_data , input_data , alpha_data , quant_max_data ] + list ( res ) config = { "print_ir" : False , "name" : kernel_name , "tensor_list" : tensor_list } te . lang . cce . cce_build_code ( sch , config )