mirror of
https://github.com/zebrajr/pytorch.git
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73ee7fda4c
Summary: Removing the deprecated functions in `torch/csrc/variable_tensor_functions.h` (like `torch::CPU`) and corresponding implementations from `torch/csrc/torch.cpp` from master after the release. ezyang gchanan soumith Pull Request resolved: https://github.com/pytorch/pytorch/pull/15003 Differential Revision: D13418086 Pulled By: goldsborough fbshipit-source-id: a0accdf6f7b0efa1ec07ac7b74b86ff2da37543f
76 lines
2.2 KiB
C++
76 lines
2.2 KiB
C++
#include <torch/csrc/python_headers.h>
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#include <torch/csrc/jit/interpreter.h>
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#include <torch/csrc/autograd/edge.h>
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#include <torch/csrc/autograd/function.h>
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#include <torch/csrc/autograd/profiler.h>
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#include <torch/csrc/autograd/variable.h>
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#include <torch/csrc/jit/operator.h>
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#include <torch/csrc/jit/custom_operator.h>
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#include <torch/csrc/jit/graph_executor.h>
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#include <torch/csrc/jit/ir.h>
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#include <torch/csrc/jit/pybind_utils.h>
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#include <typeinfo>
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#include <torch/csrc/autograd/python_engine.h>
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#include <torch/csrc/autograd/python_variable.h>
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#include <torch/csrc/jit/pybind.h>
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#include <torch/csrc/utils/auto_gil.h>
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#include <torch/csrc/Exceptions.h>
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namespace py = pybind11;
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namespace torch { namespace jit {
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namespace {
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// Note: const_cast is used twice below to acquire a handle to a pyobject.
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Operation createPythonOperation(const Node* op_) {
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AutoGIL gil;
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const PythonOp* op = static_cast<const PythonOp*>(op_);
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// NOLINTNEXTLINE(cppcoreguidelines-pro-type-const-cast)
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const py::function func = py::reinterpret_borrow<const py::function>(py::handle(const_cast<PythonOp*>(op)->pyobj.get()));
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size_t num_inputs = 0;
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for(auto arg_type : op->cconv) {
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if(arg_type == 'd')
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num_inputs++;
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}
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JIT_ASSERT(op->outputs().size() == 1);
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return [=](Stack & stack) {
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AutoGIL gil;
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py::tuple py_inputs(op->cconv.size());
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size_t i = 0;
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size_t next_scalar = 0;
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size_t next_tensor = 0;
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for (auto arg_type : op->cconv) {
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if (arg_type == 'c') {
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// NOLINTNEXTLINE(cppcoreguidelines-pro-type-const-cast)
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py_inputs[i] = py::reinterpret_borrow<const py::object>(const_cast<PythonOp*>(op)->scalar_args[next_scalar++].get());
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} else if (arg_type == 'd') {
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py_inputs[i] = toPyObject(std::move(peek(stack, next_tensor, num_inputs)));
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next_tensor++;
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}
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i++;
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}
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drop(stack, num_inputs);
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try {
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py::object py_output(func(*py_inputs));
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stack.push_back(returnToIValue(op->output()->type(), py_output));
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} catch (py::error_already_set & e) {
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throw std::runtime_error(e.what());
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}
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return 0;
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};
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}
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RegisterOperators reg({
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Operator(prim::PythonOp, createPythonOperation)
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});
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}}} // torch::jit::anon
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