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