- api : abs
  backward : abs_grad
  extra :
    attrs : [bool use_cudnn = false, bool use_mkldnn = false]

- api : addmm
  backward : addmm_grad
  extra :
    attrs : [bool use_mkldnn = false]

- api : affine_grid
  backward : affine_grid_grad
  extra :
    attrs : [bool use_cudnn = true]

- api : angle
  backward : angle_grad
  extra :
    attrs : [bool use_cudnn = false, bool use_mkldnn = false]

- api : atan2
  inputs :
    {x : X1, y : X2}
  outputs :
    out : Out

- api : batch_norm
  backward : batch_norm_grad
  extra :
    attrs : [bool use_mkldnn = false, bool fuse_with_relu = false]

- api : bernoulli
  inputs :
    x : X
  outputs :
    out : Out

- api : bicubic_interp (bicubic_interp_v2)
  backward : bicubic_interp_grad (bicubic_interp_v2_grad)
  extra :
    attrs : [bool use_mkldnn = false]

- api : bilinear_interp (bilinear_interp_v2)
  backward : bilinear_interp_grad (bilinear_interp_v2_grad)
  extra :
    attrs : [bool use_mkldnn = false]

- api : cholesky
  inputs :
    x : X
  outputs :
    out : Out

- api : cholesky_solve
  inputs :
    {x : X, y : Y}
  outputs :
    out : Out

- api : clip
  backward : clip_grad
  extra :
    attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"]

- api : concat
  backward : concat_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_quantizer = false, str mkldnn_data_type = "float32"]

- api : conv2d
  backward : conv2d_grad
  extra :
    attrs : [bool is_test = false, bool use_cudnn = true, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false,
             bool use_quantizer = false, str mkldnn_data_type = "float32", bool fuse_relu = false,
             str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f, bool use_addto = false,
             bool fuse_residual_connection = false, float Scale_in = 1.0f, float Scale_out = 1.0f,
             float Scale_in_eltwise = 1.0f, 'float[] Scale_weights = {1.0f}', bool force_fp32_output = false,
             int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false]

- api : conv2d_fusion
  extra :
    attrs : [bool is_test = false, bool use_cudnn = false, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false,
             bool use_quantizer = false, str mkldnn_data_type = "float32", bool fuse_relu = false,
             str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f, bool use_addto = false,
             bool fuse_residual_connection = false, float Scale_in = 1.0f, float Scale_out = 1.0f,
             float Scale_in_eltwise = 1.0f, 'float[] Scale_weights = {1.0f}', bool force_fp32_output = false,
             int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false]

- api : conv2d_transpose
  backward : conv2d_transpose_grad
  extra :
    attrs : [bool is_test = false, bool use_cudnn = true, bool use_mkldnn = false, bool force_fp32_output = false,
             str mkldnn_data_type = "float32", bool fuse_relu = false,
             str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f,
             int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB()]

- api : conv3d
  backward : conv3d_grad
  extra :
    attrs : [bool is_test = false, bool use_cudnn = true, bool use_mkldnn = false, str mkldnn_data_type = "float32", bool fuse_relu = false,
             str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f,
             bool use_addto = false, bool fuse_residual_connection = false, bool force_fp32_output = false,
             int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false]

- api : conv3d_transpose
  backward : conv3d_transpose_grad
  extra :
    attrs : [bool use_cudnn = true, bool use_mkldnn = false, int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB()]

- api : cross
  inputs :
    {x : X, y : Y}
  attrs :
    axis : dim
  outputs :
    out : Out

- api : data_norm
  backward : data_norm_grad
  extra :
    attrs : [bool use_mkldnn = false]

- api : depthwise_conv2d
  backward : depthwise_conv2d_grad
  extra :
    attrs : [bool is_test = false, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false,
             bool use_quantizer = false, str mkldnn_data_type = "float32", bool fuse_relu = false,
             str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f, bool use_addto = false,
             bool fuse_residual_connection = false, float Scale_in = 1.0f, float Scale_out = 1.0f,
             float Scale_in_eltwise = 1.0f, 'float[] Scale_weights = {1.0f}', bool force_fp32_output = false,
             int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false]

- api : depthwise_conv2d_transpose
  backward : depthwise_conv2d_transpose_grad
  extra :
    attrs : [bool is_test = false, bool use_cudnn = false, bool use_mkldnn = false, bool force_fp32_output = false,
             str mkldnn_data_type = "float32", bool fuse_relu = false,
             str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f,
             int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB()]

- api : diag (diag_v2)
  backward : diag_grad (diag_v2_grad)
  inputs :
    x : X
  outputs :
    out : Out

- api : diagonal
  inputs :
    x : Input
  outputs :
    out : Out

- api : digamma
  inputs :
    x : X
  outputs :
    out : Out

- api : dist
  inputs :
    {x : X, y : Y}
  outputs :
    out : Out

- api : dot
  inputs :
    {x : X, y : Y}
  outputs :
    out : Out

- api : dropout
  backward : dropout_grad
  extra :
    attrs : [bool fix_seed = false, int seed = 0]

- api : dropout_nd
  backward : dropout_nd_grad
  extra :
    attrs : [bool fix_seed = false, int seed = 0]

- api : erf
  inputs :
    x : X
  outputs :
    out : Out

- api : erfinv
  inputs :
    x : X
  outputs :
    out : Out

- api : fft_c2c
  inputs: {x: X}
  outputs: {out: Out}

- api : fft_c2r
  inputs: {x: X}
  outputs: {out: Out}

- api : fft_r2c
  inputs: {x: X}
  outputs: {out: Out}

- api : gelu
  backward : gelu_grad
  extra :
    attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32", bool use_cudnn = false]

- api : grid_sampler
  backward : grid_sampler_grad
  extra :
    attrs : [bool use_cudnn = true]

- api : gru
  backward : gru_grad
  extra :
    attrs : [bool is_test = false]

- api : inplace_abn
  backward : inplace_abn_grad
  extra :
    attrs : [bool use_mkldnn = false, bool fuse_with_relu = false]

- api : layer_norm
  backward : layer_norm_grad
  extra :
    attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32", bool is_test = false]

- api : lgamma
  inputs :
    x : X
  outputs :
    out : Out

- api : linear_interp (linear_interp_v2)
  backward : linear_interp_grad (linear_interp_v2_grad)
  extra :
    attrs : [bool use_mkldnn = false]

- api : log_softmax
  backward : log_softmax_grad
  extra :
    attrs : [bool use_mkldnn = false]

- api : lrn
  backward : lrn_grad
  extra :
    attrs : [bool use_mkldnn = false, bool is_test = false]

- api : mv
  inputs :
    {x : X, vec : Vec}
  outputs :
    out : Out

- api : nearest_interp (nearest_interp_v2)
  backward : nearest_interp_grad (nearest_interp_v2_grad)
  extra :
    attrs : [bool use_mkldnn = false]

- api : pad2d
  backward : pad2d_grad
  extra :
    attrs : [bool use_mkldnn = false]

- api : pad3d
  backward : pad3d_grad
  extra :
    attrs : [bool use_mkldnn = false]

- api : partial_sum
  backward : partial_sum_grad
  extra :
    attrs : [bool use_mkldnn = false]

- api : poisson
  inputs :
    x : X
  outputs :
    out : Out

- api : prelu
  backward : prelu_grad
  extra :
    attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32", bool is_test = false]

- api : renorm
  backward : renorm_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- api : solve
  inputs :
    {x : X, y : Y}
  outputs :
    out : Out

- api : stack
  backward : stack_grad
  extra :
    attrs : [bool use_mkldnn = false]

- api : sync_batch_norm
  backward : sync_batch_norm_grad
  extra :
    attrs : [bool use_mkldnn = false, bool fuse_with_relu = false]

- api : trace
  inputs :
    x : Input
  outputs :
    out : Out

- api : trilinear_interp (trilinear_interp_v2)
  backward : trilinear_interp_grad (trilinear_interp_v2_grad)
  extra :
    attrs : [bool use_mkldnn = false]

- api : trunc
  inputs :
    x : X
  outputs :
    out : Out