# In the open-source build, these are generated into # torch/csrc/{autgrad,jit}/generated. In fbcode, this distinction is # not currently relevant so they are combined into one list. from __future__ import absolute_import, division, print_function, unicode_literals GENERATED_CPP = [ "Functions.cpp", "THCUNN.cpp", "THNN.cpp", "VariableType_0.cpp", "VariableType_1.cpp", "VariableType_2.cpp", "VariableType_3.cpp", "VariableType_4.cpp", "register_aten_ops_0.cpp", "register_aten_ops_1.cpp", "register_aten_ops_2.cpp", "python_functions.cpp", "python_nn_functions.cpp", "python_torch_functions.cpp", "python_variable_methods.cpp", ] # copied from https://github.com/pytorch/pytorch/blob/master/tools/cpp_build/libtorch/CMakeLists.txt torch_sources_no_python_default = [ ":generate-code=Functions.cpp", ":generate-code=register_aten_ops_0.cpp", ":generate-code=register_aten_ops_1.cpp", ":generate-code=register_aten_ops_2.cpp", ":generate-code=VariableType_0.cpp", ":generate-code=VariableType_1.cpp", ":generate-code=VariableType_2.cpp", ":generate-code=VariableType_3.cpp", ":generate-code=VariableType_4.cpp", "torch/csrc/autograd/VariableTypeManual.cpp", "torch/csrc/autograd/anomaly_mode.cpp", "torch/csrc/autograd/engine.cpp", "torch/csrc/autograd/function.cpp", "torch/csrc/autograd/functions/accumulate_grad.cpp", "torch/csrc/autograd/functions/basic_ops.cpp", "torch/csrc/autograd/functions/comm.cpp", "torch/csrc/autograd/functions/tensor.cpp", "torch/csrc/autograd/functions/utils.cpp", "torch/csrc/autograd/grad_mode.cpp", "torch/csrc/autograd/input_buffer.cpp", "torch/csrc/autograd/profiler.cpp", "torch/csrc/autograd/saved_variable.cpp", "torch/csrc/autograd/variable.cpp", "torch/csrc/Exceptions.cpp", "torch/csrc/jit/autodiff.cpp", "torch/csrc/jit/constants.cpp", "torch/csrc/jit/node_hashing.cpp", "torch/csrc/jit/export.cpp", "torch/csrc/jit/graph_executor.cpp", "torch/csrc/jit/import.cpp", "torch/csrc/jit/interpreter.cpp", "torch/csrc/jit/ir.cpp", "torch/csrc/jit/operator.cpp", "torch/csrc/jit/passes/alias_analysis.cpp", "torch/csrc/jit/passes/batch_mm.cpp", "torch/csrc/jit/passes/canonicalize_ops.cpp", "torch/csrc/jit/passes/canonicalize.cpp", "torch/csrc/jit/passes/common_subexpression_elimination.cpp", "torch/csrc/jit/passes/constant_propagation.cpp", "torch/csrc/jit/passes/constant_pooling.cpp", "torch/csrc/jit/passes/create_autodiff_subgraphs.cpp", "torch/csrc/jit/passes/dead_code_elimination.cpp", "torch/csrc/jit/passes/erase_number_types.cpp", "torch/csrc/jit/passes/graph_fuser.cpp", "torch/csrc/jit/passes/inline_autodiff_subgraphs.cpp", "torch/csrc/jit/passes/inplace_check.cpp", "torch/csrc/jit/passes/loop_unrolling.cpp", "torch/csrc/jit/passes/lower_grad_of.cpp", "torch/csrc/jit/passes/lower_tuples.cpp", "torch/csrc/jit/passes/peephole.cpp", "torch/csrc/jit/passes/python_print.cpp", "torch/csrc/jit/passes/remove_expands.cpp", "torch/csrc/jit/passes/requires_grad_analysis.cpp", "torch/csrc/jit/passes/shape_analysis.cpp", "torch/csrc/jit/passes/specialize_undef.cpp", "torch/csrc/jit/passes/utils/subgraph_utils.cpp", "torch/csrc/jit/register_prim_ops.cpp", "torch/csrc/jit/register_special_ops.cpp", "torch/csrc/jit/scope.cpp", "torch/csrc/jit/script/compiler.cpp", "torch/csrc/jit/script/parser.cpp", "torch/csrc/jit/import_method.cpp", "torch/csrc/jit/hooks_for_testing.cpp", "torch/csrc/jit/script/builtin_functions.cpp", "torch/csrc/jit/script/lexer.cpp", "torch/csrc/jit/script/module.cpp", "torch/csrc/jit/tracer.cpp", "torch/csrc/utils/tensor_flatten.cpp", "torch/csrc/utils/variadic.cpp", ] def torch_vars(): r = {} # We start torch_sources with all cpp files, and exclude some. # This is a much better approach than listing all of them manually because # the number of excluded files is small and doesn"t change very frequently r["torch_sources"] = ( native.glob( ["torch/csrc/**/*.cpp"], exclude=[ # remove anything that has "generic" in it"s path "torch/csrc/**/generic/**/*.cpp", # distributed only uses Module.cpp # so remove all other files and just include that "torch/csrc/distributed/**/*.cpp", ], ) + [ "torch/csrc/distributed/Module.cpp", "torch/csrc/distributed/c10d/init.cpp", "torch/csrc/distributed/c10d/ddp.cpp", ] + [":generate-code=" + x for x in GENERATED_CPP] ) r["torch_sources_no_python"] = ( torch_sources_no_python_default + ["torch/csrc/cuda/comm.cpp", "torch/csrc/cuda/nccl.cpp"] + native.glob(["torch/csrc/jit/fuser/**/*.cpp"]) ) r["torch_sources_no_python_cpu"] = torch_sources_no_python_default + native.glob( ["torch/csrc/jit/fuser/**/*.cpp"], exclude=["torch/csrc/jit/fuser/cuda/*.cpp"] ) r["torch_csrc_flags"] = { "compiler_flags": [ "-D_THP_CORE", "-DUSE_C10D", "-DUSE_CUDNN", "-DUSE_DISTRIBUTED", "-DUSE_NCCL", "-DUSE_NUMPY", "-DUSE_SCALARS", "-DTH_INDEX_BASE=0", "-DNO_CUDNN_DESTROY_HANDLE", "-DPYTORCH_ONNX_CAFFE2_BUNDLE", "-Wno-write-strings", "-Wno-format", "-Wno-strict-aliasing", "-Wno-non-virtual-dtor", "-Wno-shadow-compatible-local", "-Wno-empty-body", ], "compiler_specific_flags": { "clang": [ "-Wno-absolute-value", "-Wno-expansion-to-defined", "-Wno-pessimizing-move", "-Wno-return-type-c-linkage", "-Wno-unknown-pragmas", ] }, "headers": native.glob(["torch/csrc/**/*.h", "torch/csrc/generic/*.cpp"]), "preprocessor_flags": [ "-Icaffe2", "-Icaffe2/torch/csrc/api/include", "-Icaffe2/torch/csrc", "-Icaffe2/torch/csrc/nn", "-Icaffe2/torch/lib", "-DUSE_CPU_FUSER_FBCODE=1", "-DUSE_CUDA_FUSER_FBCODE=1", ], } r["torch_csrc_flags_cpu"] = dict(r["torch_csrc_flags"]) r["torch_csrc_flags_cpu"]["preprocessor_flags"] = [ "-Icaffe2", "-Icaffe2/torch/csrc/api/include", "-Icaffe2/torch/csrc", "-Icaffe2/torch/csrc/nn", "-Icaffe2/torch/lib", "-DUSE_CPU_FUSER_FBCODE=1", "-DUSE_CUDA_FUSER_FBCODE=0", ] return r