op_compat.yaml

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

- op : acosh
  backward : acosh_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

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

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

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

- op : asinh
  backward : asinh_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

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

- op : atanh
  backward : atanh_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

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

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

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

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

- op : ceil
  backward : ceil_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

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

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

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

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

- op : 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]

- op : 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]

- op : 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()]

- op : 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]

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

- op : cos
  backward : cos_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : cosh
  backward : cosh_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

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

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

- op : 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]

- op : 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()]

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

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

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

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

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

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

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

- op : elu
  backward : elu_grad
  extra :
    attrs : [bool use_mkldnn = false]

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

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

- op : exp
  backward : exp_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : expm1
  backward : expm1_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

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

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

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

- op : floor
  backward : floor_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : frobenius_norm
  backward : frobenius_norm_grad
  extra :
    attrs : [bool use_mkldnn = false]

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

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

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

- op : hard_swish
  backward : hard_swish_grad
  extra :
    attrs : [bool use_mkldnn = false]

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

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

- op : leaky_relu
  backward : leaky_relu_grad
  extra :
    attrs : [bool use_mkldnn = false]

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

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

- op : log
  backward : log_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : log10
  backward : log10_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : log1p
  backward : log1p_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : log2
  backward : log2_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

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

- op : logsigmoid
  backward : logsigmoid_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

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

- op : matmul (matmul_v2)
  backward : matmul_grad (matmul_v2_grad)
  extra :
    attrs : [bool use_mkldnn = false, 'int[] fused_reshape_Out = {}', 'int[] fused_transpose_Out = {}',
             str mkldnn_data_type = "float32", 'int[] fused_reshape_X = {}', 'int[] fused_reshape_Y = {}',
             'int[] fused_transpose_X = {}', 'int[] fused_transpose_Y = {}',]

- op : mish
  backward : mish_grad
  extra :
    attrs : [bool use_mkldnn = false]

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

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

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

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

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

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

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

- op : reciprocal
  backward : reciprocal_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : reduce_all
  extra :
    attrs : [bool use_mkldnn = false]

- op : reduce_amax
  backward : reduce_amax_grad
  extra :
    attrs : [bool use_mkldnn = false]

- op : reduce_amin
  backward : reduce_amin_grad
  extra :
    attrs : [bool use_mkldnn = false]

- op : reduce_any
  extra :
    attrs : [bool use_mkldnn = false]

- op : reduce_max
  backward : reduce_max_grad
  extra :
    attrs : [bool use_mkldnn = false]

- op : reduce_mean
  backward : reduce_mean_grad
  extra :
    attrs : [bool use_mkldnn = false]

- op : reduce_min
  backward : reduce_min_grad
  extra :
    attrs : [bool use_mkldnn = false]

- op : reduce_prod
  backward : reduce_prod_grad
  extra :
    attrs : [bool use_mkldnn = false]

- op : reduce_sum
  backward : reduce_sum_grad
  extra :
    attrs : [bool use_mkldnn = false]

- op : relu
  backward : relu_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : relu6
  backward : relu6_grad
  extra :
    attrs : [bool use_mkldnn = false]

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

- op : rnn
  backward : rnn_grad
  extra :
    attrs : [bool is_test = false]

- op : round
  backward : round_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : rsqrt
  backward : rsqrt_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : seed
  extra :
    attrs : [bool deterministic = false, str rng_name = "", bool force_cpu = false]

- op : shape
  extra :
    attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"]

- op : shuffle_channel
  backward : shuffle_channel_grad
  extra :
    attrs : [bool use_mkldnn = false]

- op : sigmoid
  backward : sigmoid_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : silu
  backward : silu_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : sin
  backward : sin_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : sinh
  backward : sinh_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : slice
  backward : slice_grad
  extra :
    attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"]

- op : softmax
  backward : softmax_grad
  extra :
    attrs : [bool use_cudnn = false, bool use_mkldnn = false, str mkldnn_data_type = "float32", bool is_test = false]

- op : softplus
  backward : softplus_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false, str fuse_activation_type = "", float fuse_activation_alpha = 0.0f,
             float fuse_activation_beta = 0.0f, float fuse_activation_scale = 1.0f]

- op : softsign
  backward : softsign_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

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

- op : sqrt
  backward : sqrt_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : square
  backward : square_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : squeeze (squeeze2)
  backward : squeeze_grad (squeeze2_grad)
  extra :
    attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"]

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

- op : swish
  backward : swish_grad
  extra :
    attrs : [bool use_mkldnn = false]

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

- op : tan
  backward : tan_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : tanh
  backward : tanh_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

- op : tanh_shrink
  backward : tanh_shrink_grad
  extra :
    attrs : [bool use_mkldnn = false, bool use_cudnn = false]

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

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

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