import torch from torch._decomp import get_decompositions # default decompositions pulled from SHARK / torch._decomp DEFAULT_DECOMPOSITIONS = [ torch.ops.aten.embedding_dense_backward, torch.ops.aten.native_layer_norm_backward, torch.ops.aten.slice_backward, torch.ops.aten.select_backward, torch.ops.aten.norm.ScalarOpt_dim, torch.ops.aten.native_group_norm, torch.ops.aten.upsample_bilinear2d.vec, torch.ops.aten.split.Tensor, torch.ops.aten.split_with_sizes, torch.ops.aten.native_layer_norm, torch.ops.aten.masked_fill.Tensor, torch.ops.aten.masked_fill.Scalar, torch.ops.aten.t, torch.ops.aten.addmm, # decompositions that aid us in handling nn.BatchNorm2d torch.ops.aten._native_batch_norm_legit_functional, torch.ops.aten._native_batch_norm_legit_no_training, torch.ops.aten._native_batch_norm_legit, torch.ops.aten._native_batch_norm_legit.no_stats, torch.ops.aten.squeeze.dims, # decompositions for miscellaneous ops that are not handled in torch-mlir but have available decompositions torch.ops.aten.soft_margin_loss, torch.ops.aten.im2col, torch.ops.aten._euclidean_dist, torch.ops.aten.index_copy, torch.ops.aten.index_copy_, torch.ops.aten.grid_sampler_2d, torch.ops.aten.log_sigmoid_forward, torch.ops.aten.unsafe_split.Tensor, torch.ops.aten.binary_cross_entropy, torch.ops.aten.dot, torch.ops.aten._adaptive_avg_pool2d, torch.ops.aten._prelu_kernel, torch.ops.aten.full, torch.ops.aten._log_softmax, torch.ops.aten.nll_loss_forward, torch.ops.aten.nll_loss_backward, torch.ops.aten._to_copy, torch.ops.aten._log_softmax_backward_data, torch.ops.aten.lift_fresh_copy.default, torch.ops.aten._unsafe_index.Tensor, torch.ops.aten.linspace.default, torch.ops.aten.triu.default, torch.ops.aten.nan_to_num.default, torch.ops.aten.unbind, torch.ops.aten._scaled_dot_product_flash_attention_for_cpu, ] def get_decomposition_table(): return get_decompositions(DEFAULT_DECOMPOSITIONS)