| function | Symbolic_implemented |
|---|---|
| gather | |
| equal | |
__and__, __iand__, __or__, __ior__, __xor__, __ixor__, __lshift__, __ilshift__, __rshift__, __irshift__ |
|
| min, max | |
| all | |
| any | |
| frac | yes |
| dist | |
| reciprocal | yes |
| neg | yes |
| atan2 | |
| pow | |
| lerp | |
| sign | |
| fmod | yes |
| remainder | yes |
| addbmm | |
| addcmul | |
| addcdiv | |
| multinomial | |
| normal | |
| tensor | |
| _cast_byte | |
| _cast_char | |
| _cast_double | |
| _cast_float | |
| _cast_int | |
| _cast_long | |
| _cast_short | |
| _cast_half | |
| abs | yes |
| acos | yes |
| add | yes |
| addmv | |
| addr | |
| allclose | |
| arange | |
| argmax | |
| argmin | |
| as_strided | |
| asin | yes |
| atan | yes |
| baddbmm | |
| bernoulli | |
| bmm | |
| broadcast_tensors | |
| cat | |
| ceil | yes |
| chunk | |
| clamp | yes |
| contiguous | |
| convolution | |
| conv1d | |
| conv2d | |
| conv3d | |
| conv_transpose1d | |
| conv_transpose2d | |
| conv_transpose3d | |
| cos | yes |
| cosh | yes |
| div | yes |
| dot | |
| empty | |
| resize_ | |
| empty_like | |
| empty_strided | |
| erf | |
| erfc | |
| exp | yes |
| expm1 | yes |
| expand | |
| expand_as | |
| flatten | |
| fill_ | |
| floor | yes |
| full | |
| full_like | |
| index | |
| index_copy_ | |
| index_put | |
| is_floating_point | |
| is_complex | |
| is_nonzero | |
| is_same_size | |
| is_signed | |
| log | yes |
| log10 | yes |
| log1p | yes |
| log2 | yes |
| logsumexp | |
| matmul | |
| mean | |
| mm | yes |
| mul | yes |
| mv | |
| narrow_copy | |
| narrow | |
| ones | |
| ones_like | |
| pin_memory | |
| rand | |
| rand_like | |
| randint | |
| randint_like | |
| randn | |
| randn_like | |
| randperm | |
| range | |
| repeat | |
| reshape | |
| reshape_as | |
| round | yes |
| rsqrt | yes |
| select | |
| sin | yes |
| sinh | yes |
| detach | |
| size | |
| slice | |
| split | |
| squeeze | |
| stack | |
| stride | |
| sum | |
| sqrt | |
| std | |
| prod | |
| t | yes |
| tan | yes |
| tanh | yes |
| tensordot | |
| transpose | |
| trunc | yes |
| type_as | yes |
| unsqueeze | yes |
| var | |
| view_as | |
| zeros | |
| zeros_like | |
| norm | |
| clone | |
| resize_as_ | |
| zero_ | |
| sub | yes |
| addmm | yes |
| numel | |
| unbind | |
| to | |
| storage_offset | |
| set_ | |
| is_contiguous | |
| is_set_to | |
| masked_fill_ | |
| masked_scatter_ | |
| view | |
| put_ | |
| index_add_ | |
| index_fill_ | |
| scatter_ | |
| scatter_add_ | |
| random_ | |
| uniform_ | |
| ne | yes |
| eq | yes |
| ge | yes |
| le | yes |
| gt | yes |
| lt | yes |
| take | |
| index_select | |
| masked_select | |
| nonzero | |
| is_tensor | |
| is_storage | |
| as_tensor | |
| unique | |
| isfinite | |
| isinf | |
| isnan |
| function | Symbolic_implemented |
|---|---|
| median | |
| sort | |
| topk | |
| gels | |
| trtrs | |
| symeig | |
| eig | |
| svd | |
| potrf | |
| potrs | |
| potri | |
| pstrf | |
| qr | |
| geqrf | |
| orgqr | |
| ormqr | |
| btrifact | |
| btrifact_with_info | |
| btrisolve | |
| cumsum | |
| linspace | |
| logspace |
| function | Symbolic_implemented |
|---|---|
| lgamma | |
| digamma | |
| polygamma | |
| erfinv | |
| renorm | |
| histc | |
| bartlett_window | |
| bincount | |
| blackman_window | |
| chain_matmul | |
| cumprod | |
| det | |
| diagflat | |
| diagonal | |
| einsum | |
| eye | |
| hann_window | |
| hamming_window | |
| hinge_embedding_loss | |
| ger | |
| gesv | |
| fft | |
| ifft | |
| rfft | |
| irfft | |
| inverse | |
| kthvalue | |
| logdet | |
| matrix_rank | |
| matrix_power | |
| mode | |
| mvlgamma | |
| permute | |
| pixel_shuffle | |
| pinverse | |
| slogdet | |
| smm | |
| sspaddmm | |
| stft | |
| flip | |
| rot90 | |
| where | |
| poisson | |
| sparse_coo_tensor | |
| sparse_resize_ | |
| sparse_resize_and_clear_ | |
| sparse_mask | |
| to_dense | |
| sparse_dim | |
| dense_dim | |
| coalesce | |
| is_coalesced | |
| indices | |
| values | |
| hspmm | |
| copy_sparse_to_sparse_ | |
| to_sparse | |
| meshgrid | |
| cauchy_ | |
| log_normal_ | |
| exponential_ | |
| geometric_ | |
| diag | |
| cross | |
| triu | |
| tril | |
| trace | |
| argsort | |
| btriunpack |
| function | Symbolic_implemented |
|---|---|
| binary_cross_entropy | |
| mse_loss | |
| nll_loss | |
| nll_loss2d | |
| smooth_l1_loss | |
| elu | |
| glu | |
| hardtanh | |
| leaky_relu | |
| log_sigmoid | |
| softplus | |
| softshrink | |
| threshold | |
| avg_pool2d | |
| avg_pool3d | |
| max_pool2d_with_indices | |
| max_pool3d_with_indices | |
| max_unpool2d | |
| max_unpool3d | |
| upsample_linear1d | |
| upsample_bilinear2d | |
| upsample_trilinear3d | |
| upsample_nearest1d | |
| upsample_nearest2d | |
| upsample_nearest3d | |
| dropout | |
| feature_dropout | |
| avg_pool1d | |
| batch_norm | |
| bilinear | |
| binary_cross_entropy_with_logits | |
| embedding | |
| group_norm | |
| instance_norm | |
| linear | |
| log_softmax | |
| max_pool1d_with_indices | |
| max_pool1d | |
| max_pool2d | |
| max_pool3d | |
| relu | yes |
| prelu | |
| sigmoid | yes |
| softmax | |
| max_unpool1d | |
| relu6 | |
| logsigmoid | |
| tanhshrink | |
| softsign | |
| softmin | |
| dropout2d | |
| dropout3d | |
| cross_entropy | |
| interpolate | |
| upsample | |
| upsample_nearest | |
| upsample_bilinear |
| function | Symbolic_implemented |
|---|---|
| l1_loss | |
| multi_margin_loss | |
| multilabel_margin_loss | |
| soft_margin_loss | |
| ctc_loss | |
| grid_sampler | |
| grid_sampler_2d | |
| grid_sampler_3d | |
| layer_norm | |
| lstm | |
| gru | |
| rnn_tanh | |
| rnn_relu | |
| lstm_cell | |
| gru_cell | |
| rnn_tanh_cell | |
| rnn_relu_cell | |
| _pack_padded_sequence | |
| _pad_packed_sequence | |
| torch.nn.utils.rnn.packedsequence | |
| torch.nn.utils.rnn.pack_padded_sequence | |
| torch.nn.utils.rnn.pad_packed_sequence | |
| torch.nn.utils.rnn.pad_sequence | |
| torch.nn.utils.rnn.pack_sequence |
| function | Symbolic_implemented |
|---|---|
| unfold | |
| adaptive_avg_pool2d | |
| adaptive_avg_pool3d | |
| adaptive_max_pool2d | |
| adaptive_max_pool3d | |
| fractional_max_pool2d | |
| alpha_dropout | |
| feature_alpha_dropout | |
| adaptive_avg_pool1d | |
| adaptive_max_pool1d | |
| cosine_embedding_loss | |
| embedding_bag | |
| kl_div | |
| margin_ranking_loss | |
| pairwise_distance | |
| pdist | |
| rrelu | |
| hardshrink | |
| selu | |
| celu | |
| triplet_margin_loss | |
| torch.nn.utils.clip_grad_norm_ | |
| torch.nn.utils.clip_grad_value_ | |
| torch.nn.utils.parameters_to_vector | |
| torch.nn.utils.vector_to_parameters | |
| torch.nn.utils.weight_norm | |
| torch.nn.utils.remove_weight_norm | |
| torch.nn.utils.spectral_norm | |
| torch.nn.utils.remove_spectral_norm | |
| fold | |
| lp_pool1d | |
| lp_pool2d | |
| gumbel_softmax | |
| local_response_norm | |
| normalize | |
| cosine_similarity | |
| poisson_nll_loss | |
| multilabel_soft_margin_loss | |
| pad | |
| grid_sample | |
| affine_grid | |
| torch.nn.parallel.data_parallel | |
| calculate_gain | |
| constant_ | |
| dirac_ | |
| xavier_uniform_ | |
| xavier_normal_ | |
| kaiming_uniform_ | |
| kaiming_normal_ | |
| orthogonal_ | |
| sparse_ |