# - op : rnn # backward : rnn_grad # extra : # attrs : [bool is_test = false] - op : abs backward : abs_grad extra : attrs : [bool use_mkldnn = false] - op : acosh backward : acosh_grad extra : attrs : [bool use_mkldnn = false, bool use_cudnn = false] - op : add (elementwise_add) backward : add_grad (elementwise_add_grad) extra : attrs : [bool use_mkldnn = false, str x_data_format = "", str y_data_format = "", str mkldnn_data_type = "float32", bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f] - 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 : conditional_block backward : conditional_block_grad extra : attrs : ['str[] skip_eager_deletion_vars = {}'] - 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 : dequantize_linear extra : attrs : [float moving_rate = 0.9] - 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 : distributed_push_sparse extra : attrs : ['int[] slots = {}'] - op : divide (elementwise_div) backward : divide_grad (elementwise_div) extra : attrs : [bool use_mkldnn = false, str x_data_format = "", str y_data_format = "", str mkldnn_data_type = "float32", bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f] - 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 : elementwise_pow backward : elementwise_pow_grad extra : attrs : [bool use_mkldnn = false, str x_data_format = "", str y_data_format = "", str mkldnn_data_type = "float32", bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f] - op : elu backward : elu_grad extra : attrs : [bool use_mkldnn = false] - op : embedding (lookup_table_v2) backward : embedding_grad (lookup_table_v2_grad) extra : attrs : [bool is_sparse = false, bool is_distributed = false, bool remote_prefetch = false, int trainer_id = 0, int slot = 0, 'int64_t[] height_sections = {}', 'str[] epmap = {}', 'str[] table_names = {}'] - 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 : exp inputs : x : X outputs : out : Out - op : expand (expand_v2) backward : expand_grad (expand_v2_grad) extra : attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"] - op : expm1 backward : expm1_grad extra : attrs : [bool use_mkldnn = false, bool use_cudnn = false] - op : fake_channel_wise_quantize_abs_max extra : attrs : [int round_type = 1] - op : fake_channel_wise_quantize_dequantize_abs_max extra : attrs : [int round_type = 1] - op : fake_quantize_abs_max extra : attrs : [int round_type = 1] - op : fake_quantize_dequantize_abs_max extra : attrs : [int round_type = 1] - op : fake_quantize_dequantize_moving_average_abs_max extra : attrs : [int round_type = 1] - op : fake_quantize_moving_average_abs_max extra : attrs : [int round_type = 1] - op : fake_quantize_range_abs_max extra : attrs : [int round_type = 1] - 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 : flip inputs : x : X outputs : out : Out - op : floor backward : floor_grad extra : attrs : [bool use_mkldnn = false, bool use_cudnn = false] - op : floor_divide (elementwise_floordiv) extra : attrs : [bool use_mkldnn = false, str x_data_format = "", str y_data_format = "", str mkldnn_data_type = "float32", bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f] - op : fmax (elementwise_fmax) backward : fmax_grad (elementwise_fmax_grad) extra : attrs : [bool use_mkldnn = false, str x_data_format = "", str y_data_format = "", str mkldnn_data_type = "float32", bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f] - op : fmin (elementwise_fmin) backward : fmin_grad (elementwise_fmin_grad) extra : attrs : [bool use_mkldnn = false, str x_data_format = "", str y_data_format = "", str mkldnn_data_type = "float32", bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f] - op : frobenius_norm backward : frobenius_norm_grad extra : attrs : [bool use_mkldnn = false] - op : full (fill_constant) extra : attrs : [bool use_mkldnn = false] - op : gather backward : gather_grad extra : attrs : [bool overwrite = true] - op : gelu backward : gelu_grad extra : attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32", bool use_cudnn = false] - op : grad_add extra : attrs : [bool use_mkldnn = false, str x_data_format = "", str y_data_format = "", str mkldnn_data_type = "float32", bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f] - 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 : heaviside (elementwise_heaviside) backward : heaviside_grad (elementwise_heaviside_grad) extra : attrs : [bool use_mkldnn = false, str x_data_format = "", str y_data_format = "", str mkldnn_data_type = "float32", bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f] - 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 : matmul_with_flatten (mul) backward : matmul_with_flatten_grad (mul_grad) extra : attrs : [bool use_mkldnn = false, float scale_x = 1.0f, 'float[] scale_y = {1.0f}', float scale_out = 1.0f, bool force_fp32_output = false] - op : maximum (elementwise_max) backward : maximum_grad (elementwise_max_grad) extra : attrs : [bool use_mkldnn = false, str x_data_format = "", str y_data_format = "", str mkldnn_data_type = "float32", bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f] - op : maximum (elementwise_min) backward : maximum_grad (elementwise_min_grad) extra : attrs : [bool use_mkldnn = false, str x_data_format = "", str y_data_format = "", str mkldnn_data_type = "float32", bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f] - op : mish backward : mish_grad extra : attrs : [bool use_mkldnn = false] - op : multiply (elementwise_mul) backward : multiply_grad (elementwise_mul_grad) extra : attrs : [bool use_mkldnn = false, str x_data_format = "", str y_data_format = "", str mkldnn_data_type = "float32", bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f] - op : mv inputs : {x : X, vec : Vec} outputs : out : Out - op : nce backward : nce_grad extra : attrs : [int trainer_id = 0, 'int64_t[] height_sections = {}', 'str[] epmap = {}', 'str[] table_names = {}', 'int[] custom_neg_classes = {}'] - 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 : pool2d backward : pool2d_grad extra : attrs : [bool use_mkldnn = false, bool use_quantizer = false, str mkldnn_data_type = "float32", bool is_test = false] - op : pool3d backward : pool3d_grad extra : attrs : [bool use_mkldnn = false] - op : prelu backward : prelu_grad extra : attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32", bool is_test = false] - op : quantize_linear extra : attrs : [float moving_rate = 0.9] - 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 : remainder (elementwise_mod) extra : attrs : [bool use_mkldnn = false, str x_data_format = "", str y_data_format = "", str mkldnn_data_type = "float32", bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f] - op : renorm backward : renorm_grad extra : attrs : [bool use_mkldnn = false, bool use_cudnn = 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 : scale extra : attrs : [bool use_mkldnn = false] - op : seed extra : attrs : [bool deterministic = false, str rng_name = "", bool force_cpu = false] - op : sequence_softmax backward : sequence_softmax_grad extra : attrs : [str data_format = "AnyLayout"] - 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_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 : stack backward : stack_grad extra : attrs : [bool use_mkldnn = false] - op : subtract (elementwise_sub) backward : subtract_grad (elementwise_sub_grad) extra : attrs : [bool use_mkldnn = false, str x_data_format = "", str y_data_format = "", str mkldnn_data_type = "float32", bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f] - 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 : transpose (transpose2) backward : transpose_grad (transpose2_grad) extra : attrs : [bool use_mkldnn = false, str data_format = "AnyLayout", bool use_quantizer = false, str mkldnn_data_type = "float32"] - op : trilinear_interp (trilinear_interp_v2) backward : trilinear_interp_grad (trilinear_interp_v2_grad) extra : attrs : [bool use_mkldnn = false] - op : trunc inputs : input : X outputs : out : Out - op : while backward : while_grad extra : attrs : ['str[] skip_eager_deletion_vars = {}']