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use irange for loops (#66234)

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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66234

Modified loops in files under fbsource/fbcode/caffe2/ from the format

`for(TYPE var=x0;var<x_max;x++)`

to the format

`for(const auto var: irange(xmax))`

This was achieved by running r-barnes's loop upgrader script (D28874212) with some modification to exclude all files under /torch/jit and a number of reversions or unused variable suppression warnings added by hand.

bypass_size_limit
allow-large-files

Test Plan: Sandcastle

Reviewed By: ngimel

Differential Revision: D30652629

fbshipit-source-id: 0ae6c4bbbb554bad42e372792a6430e1acf15e3e
This commit is contained in:
Richard Barnes
2021-10-15 13:48:39 -07:00
committed by Facebook GitHub Bot
parent b5b7d6a3a6
commit 687c2267d4
487 changed files with 22184 additions and 21930 deletions
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11
test/cpp/api/tensor.cpp
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@ -1,6 +1,7 @@
#include <gtest/gtest.h>
#include <test/cpp/api/support.h>
#include <c10/util/irange.h>
#include <torch/torch.h>
#include <cmath>
@ -263,7 +264,7 @@ TEST(TensorTest, AtTensorCtorSingleDim) {
tensor = at::tensor(v);
ASSERT_EQ(tensor.numel(), v.size());
ASSERT_EQ(tensor.dtype(), at::kInt);
for (size_t i = 0; i < v.size(); ++i) {
for (const auto i : c10::irange(v.size())) {
ASSERT_TRUE(exactly_equal(tensor[i], v.at(i)));
}
@ -271,7 +272,7 @@ TEST(TensorTest, AtTensorCtorSingleDim) {
tensor = at::tensor(w);
ASSERT_EQ(tensor.numel(), w.size());
ASSERT_EQ(tensor.dtype(), at::kDouble);
for (size_t i = 0; i < w.size(); ++i) {
for (const auto i : c10::irange(w.size())) {
ASSERT_TRUE(almost_equal(tensor[i], w.at(i)));
}
@ -282,7 +283,7 @@ TEST(TensorTest, AtTensorCtorSingleDim) {
tensor = at::tensor(x);
ASSERT_EQ(tensor.numel(), x.size());
ASSERT_EQ(tensor.dtype(), at::kComplexDouble);
for (size_t i = 0; i < x.size(); ++i) {
for (const auto i : c10::irange(x.size())) {
ASSERT_TRUE(almost_equal(tensor[i], x.at(i)));
}
}
@ -913,8 +914,8 @@ TEST(TensorTest, FromBlobWithStrides) {
ASSERT_EQ(tensor.numel(), 9);
const std::vector<int64_t> expected_strides = {1, 3};
ASSERT_EQ(tensor.strides(), expected_strides);
for (int64_t i = 0; i < tensor.size(0); ++i) {
for (int64_t j = 0; j < tensor.size(1); ++j) {
for (const auto i : c10::irange(tensor.size(0))) {
for (const auto j : c10::irange(tensor.size(1))) {
// NOTE: This is column major because the strides are swapped.
EXPECT_EQ(tensor[i][j].item<int32_t>(), 1 + (j * tensor.size(1)) + i);
}