/usr/local/lib64/python3.6/site-packages/torch/include/torch/csrc/jit/passes
NameSizeModeActions
quantization/-0755rm
utils/-0755rm
annotate_warns.h1920644editdlrm
bailout_graph.h11290644editdlrm
batch_mm.h1630644editdlrm
canonicalize.h4920644editdlrm
canonicalize_graph_fuser_ops.h1770644editdlrm
clear_profiling.h3340644editdlrm
clear_undefinedness.h8890644editdlrm
common_subexpression_elimination.h1940644editdlrm
concat_opt.h4810644editdlrm
constant_pooling.h1770644editdlrm
constant_propagation.h12870644editdlrm
create_autodiff_subgraphs.h5520644editdlrm
create_functional_graphs.h3230644editdlrm
cuda_graph_fuser.h8600644editdlrm
dead_code_elimination.h15840644editdlrm
decompose_ops.h1680644editdlrm
erase_number_types.h8130644editdlrm
fixup_trace_scope_blocks.h16730644editdlrm
fold_conv_bn.h9950644editdlrm
freeze_module.h12360644editdlrm
frozen_conv_add_relu_fusion.h2330644editdlrm
frozen_conv_folding.h8720644editdlrm
frozen_graph_optimizations.h4350644editdlrm
frozen_ops_to_mkldnn.h4140644editdlrm
fuse_linear.h5260644editdlrm
fuse_relu.h2730644editdlrm
graph_fuser.h12510644editdlrm
graph_rewrite_helper.h17850644editdlrm
guard_elimination.h3900644editdlrm
hoist_conv_packed_params.h2110644editdlrm
inliner.h1990644editdlrm
inline_autodiff_subgraphs.h2750644editdlrm
inline_forked_closures.h2410644editdlrm
inline_fork_wait.h5470644editdlrm
inplace_check.h1680644editdlrm
insert_guards.h4530644editdlrm
integer_value_refinement.h2340644editdlrm
lift_closures.h2360644editdlrm
liveness.h6630644editdlrm
loop_unrolling.h10060644editdlrm
lower_grad_of.h3480644editdlrm
lower_graph.h7500644editdlrm
lower_tuples.h6660644editdlrm
metal_rewrite.h6060644editdlrm
normalize_ops.h5360644editdlrm
onnx.h9670644editdlrm
pass_manager.h46350644editdlrm
peephole.h5070644editdlrm
peephole_alias_sensitive.h3550644editdlrm
peephole_dict_idioms.h10000644editdlrm
peephole_list_idioms.h20030644editdlrm
peephole_non_tensor.h3420644editdlrm
prepack_folding.h3580644editdlrm
remove_dropout.h2800644editdlrm
remove_exceptions.h9540644editdlrm
remove_expands.h1750644editdlrm
remove_inplace_ops.h2960644editdlrm
remove_mutation.h26740644editdlrm
remove_redundant_profiles.h1960644editdlrm
requires_grad_analysis.h2600644editdlrm
restore_mutation.h18870644editdlrm
shape_analysis.h4630644editdlrm
specialize_autogradzero.h6560644editdlrm
subgraph_rewrite.h41120644editdlrm
symbolic_shape_analysis.h6410644editdlrm
tensorexpr_fuser.h20770644editdlrm
update_differentiable_graph_requires_grad.h7400644editdlrm
value_refinement_utils.h26690644editdlrm
variadic_ops.h9930644editdlrm
vulkan_rewrite.h5760644editdlrm
xnnpack_rewrite.h9170644editdlrm
Edit: /usr/local/lib64/python3.6/site-packages/torch/include/torch/csrc/jit/passes/tensorexpr_fuser.h (2077B)
#pragma once #include #include #include namespace torch { namespace jit { struct Graph; // Run TensorExpressions-based fuser. // // If shape checks are disabled it is the responsibilty of // the caller to ensure that the resultant subgraph is correctly // annotated with shapes by the time "getOperation" is called // on the node. TORCH_API void FuseTensorExprs( std::shared_ptr& graph, size_t min_group_size = 2, bool disable_shape_checks = false); TORCH_API void setTensorExprFuserEnabled(bool val); TORCH_API bool tensorExprFuserEnabled(); TORCH_API bool setTexprReductionsEnabled(bool value); TORCH_API bool texprReductionsEnabled(); TORCH_API void RemoveProfileNodesAndSpecializeTypes( std::shared_ptr& graph); TORCH_API void RemoveTensorTypeSpecializations(std::shared_ptr& graph); TORCH_API void removeTensorTypeSpecializations(Block* block); using tensor_type_converter_t = c10::function_ref; // inserts a TypeCheck pattern // // around the guarded node that has a Subgraph attribute, this inserts a pattern // // if TypeCheck(...): // guarded_node // else: // FallbackGraph(...) // // The TypeCheck includes the types of all Tensor inputs to the guarded_node, // as processed by the type_converter, a lambda // TensorTypePtr(const TensorTypePtr& t). This allows to erase irrelevant // aspects of the type. // // The Fallback graph will have the same subgraph as the guarded node (with the // expectation that the guarded_node's subgraph will then be optimized. TORCH_API void insertTypeGuard( Node* guarded_node, tensor_type_converter_t type_converter, c10::Symbol kind); TORCH_API bool usedOnlyInSize(Value* v); TORCH_API Value* broadcastSizes(at::ArrayRef sizes, AliasDb* db); namespace tensorexpr { TORCH_API const OperatorSet& supported_eltwise_set(); TORCH_API bool isSupported(Node* node); } // namespace tensorexpr } // namespace jit } // namespace torch