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Use irange in a few places in torch/csrc (#55100)

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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/55100

Test Plan: Sandcastle

Reviewed By: ngimel

Differential Revision: D27447708

fbshipit-source-id: 4f21133bd76f29d73a51befcae649ab55637b36e
This commit is contained in:
Richard Barnes
2021-06-03 00:57:50 -07:00
committed by Facebook GitHub Bot
parent 18642e664a
commit f914ab193e
7 changed files with 38 additions and 29 deletions
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5
torch/csrc/autograd/python_engine.cpp
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@ -11,6 +11,7 @@
#include <torch/csrc/utils/pycfunction_helpers.h>
#include <ATen/BatchedTensorImpl.h>
#include <ATen/VmapMode.h>
#include <c10/util/irange.h>
#include <pybind11/pybind11.h>
#ifndef _WIN32
@ -182,7 +183,7 @@ PyObject *THPEngine_run_backward(PyObject *self, PyObject *args, PyObject *kwarg
roots.reserve(num_tensors);
variable_list grads;
grads.reserve(num_tensors);
for (int i = 0; i < num_tensors; i++) {
for(const auto i : c10::irange(num_tensors)) {
PyObject *_tensor = PyTuple_GET_ITEM(tensors, i);
THPUtils_assert(THPVariable_Check(_tensor), "element %d of tensors "
"tuple is not a Tensor", i);
@ -267,7 +268,7 @@ PyObject *THPEngine_run_backward(PyObject *self, PyObject *args, PyObject *kwarg
int num_inputs = PyTuple_GET_SIZE(inputs);
THPObjectPtr py_outputs {PyTuple_New(num_inputs)};
if (!py_outputs) return nullptr;
for (int i = 0; i < num_inputs; i++) {
for(const auto i : c10::irange(num_inputs)) {
THPUtils_assert(allow_unreachable || outputs[i].defined(), "One of the "
"differentiated Tensors appears to not have been used "
"in the graph. Set allow_unused=True if this is the "