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[BE][Ez]: Enable ClangFormat aten/src/core/Formatting.cpp (#154719)

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Follow up to #152830 . Noticed the file was excluded from fromatting, opt in to clang-format since it's really close anyway.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/154719
Approved by: https://github.com/jansel
This commit is contained in:
Aaron Gokaslan 2025-05-30 19:52:38 +00:00 committed by PyTorch MergeBot
parent f57754e815
commit 2f03673ebf
2 changed files with 88 additions and 69 deletions
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1
.lintrunner.toml
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@ -64,6 +64,7 @@ include_patterns = [
'aten/src/ATen/xpu/**/*.cpp', 'aten/src/ATen/xpu/**/*.cpp',
'aten/src/ATen/core/boxing/**/*.h', 'aten/src/ATen/core/boxing/**/*.h',
'aten/src/ATen/core/dispatch/**/*.h', 'aten/src/ATen/core/dispatch/**/*.h',
'aten/src/ATen/core/Formatting.cpp',
'aten/src/ATen/native/mps/**/*.metal', 'aten/src/ATen/native/mps/**/*.metal',
'aten/src/ATen/native/mps/**/*.mm', 'aten/src/ATen/native/mps/**/*.mm',
'aten/src/ATen/native/mps/**/*.h', 'aten/src/ATen/native/mps/**/*.h',

124
aten/src/ATen/core/Formatting.cpp
View File

@ -45,7 +45,7 @@ std::string toString(const Scalar& s) {
namespace at { namespace at {
std::ostream& operator<<(std::ostream & out, const DeprecatedTypeProperties& t) { std::ostream& operator<<(std::ostream& out, const DeprecatedTypeProperties& t) {
return out << t.toString(); return out << t.toString();
} }
@ -66,7 +66,7 @@ struct PrintFormat {
static PrintFormat __printFormat(const Tensor& self) { static PrintFormat __printFormat(const Tensor& self) {
auto size = self.numel(); auto size = self.numel();
if(size == 0) { if (size == 0) {
return PrintFormat(1., 0); return PrintFormat(1., 0);
} }
@ -74,8 +74,8 @@ static PrintFormat __printFormat(const Tensor& self) {
auto self_p = self.const_data_ptr<double>(); auto self_p = self.const_data_ptr<double>();
for (const auto i : c10::irange(size)) { for (const auto i : c10::irange(size)) {
auto z = self_p[i]; auto z = self_p[i];
if(std::isfinite(z)) { if (std::isfinite(z)) {
if(z != std::ceil(z)) { if (z != std::ceil(z)) {
intMode = false; intMode = false;
break; break;
} }
@ -83,28 +83,28 @@ static PrintFormat __printFormat(const Tensor& self) {
} }
int64_t offset = 0; int64_t offset = 0;
while(offset < size && !std::isfinite(self_p[offset])) { while (offset < size && !std::isfinite(self_p[offset])) {
offset = offset + 1; offset = offset + 1;
} }
double expMin = 1; double expMin = 1;
double expMax = 1; double expMax = 1;
if(offset != size) { if (offset != size) {
expMin = std::fabs(self_p[offset]); expMin = std::fabs(self_p[offset]);
expMax = std::fabs(self_p[offset]); expMax = std::fabs(self_p[offset]);
for (const auto i : c10::irange(offset, size)) { for (const auto i : c10::irange(offset, size)) {
double z = std::fabs(self_p[i]); double z = std::fabs(self_p[i]);
if(std::isfinite(z)) { if (std::isfinite(z)) {
expMin = std::min(expMin, z); expMin = std::min(expMin, z);
expMax = std::max(expMax, z); expMax = std::max(expMax, z);
} }
} }
if(expMin != 0) { if (expMin != 0) {
expMin = std::floor(std::log10(expMin)) + 1; expMin = std::floor(std::log10(expMin)) + 1;
} else { } else {
expMin = 1; expMin = 1;
} }
if(expMax != 0) { if (expMax != 0) {
expMax = std::floor(std::log10(expMax)) + 1; expMax = std::floor(std::log10(expMax)) + 1;
} else { } else {
expMax = 1; expMax = 1;
@ -114,8 +114,8 @@ static PrintFormat __printFormat(const Tensor& self) {
double scale = 1; double scale = 1;
int sz = 11; int sz = 11;
if(intMode) { if (intMode) {
if(expMax > 9) { if (expMax > 9) {
sz = 11; sz = 11;
return PrintFormat(scale, sz, FormatType::Scientific); return PrintFormat(scale, sz, FormatType::Scientific);
} else { } else {
@ -123,19 +123,19 @@ static PrintFormat __printFormat(const Tensor& self) {
return PrintFormat(scale, sz, FormatType::Default); return PrintFormat(scale, sz, FormatType::Default);
} }
} else { } else {
if(expMax-expMin > 4) { if (expMax - expMin > 4) {
sz = 11; sz = 11;
if(std::fabs(expMax) > 99 || std::fabs(expMin) > 99) { if (std::fabs(expMax) > 99 || std::fabs(expMin) > 99) {
sz = sz + 1; sz = sz + 1;
} }
return PrintFormat(scale, sz, FormatType::Scientific); return PrintFormat(scale, sz, FormatType::Scientific);
} else { } else {
if(expMax > 5 || expMax < 0) { if (expMax > 5 || expMax < 0) {
sz = 7; sz = 7;
scale = std::pow(10, expMax-1); scale = std::pow(10, expMax - 1);
return PrintFormat(scale, sz, FormatType::Fixed); return PrintFormat(scale, sz, FormatType::Fixed);
} else { } else {
if(expMax == 0) { if (expMax == 0) {
sz = 7; sz = 7;
} else { } else {
sz = static_cast<int>(expMax) + 6; sz = static_cast<int>(expMax) + 6;
@ -168,22 +168,26 @@ static void printValue(std::ostream& stream, double v, const PrintFormat& pf) {
} }
} }
static void __printMatrix(std::ostream& stream, const Tensor& self, int64_t linesize, int64_t indent) { static void __printMatrix(
std::ostream& stream,
const Tensor& self,
int64_t linesize,
int64_t indent) {
auto printFmt = __printFormat(self); auto printFmt = __printFormat(self);
int64_t nColumnPerLine = (linesize - indent) / (printFmt.width + 1); int64_t nColumnPerLine = (linesize - indent) / (printFmt.width + 1);
int64_t firstColumn = 0; int64_t firstColumn = 0;
int64_t lastColumn = -1; int64_t lastColumn = -1;
while(firstColumn < self.size(1)) { while (firstColumn < self.size(1)) {
if(firstColumn + nColumnPerLine <= self.size(1)) { if (firstColumn + nColumnPerLine <= self.size(1)) {
lastColumn = firstColumn + nColumnPerLine - 1; lastColumn = firstColumn + nColumnPerLine - 1;
} else { } else {
lastColumn = self.size(1) - 1; lastColumn = self.size(1) - 1;
} }
if(nColumnPerLine < self.size(1)) { if (nColumnPerLine < self.size(1)) {
if(firstColumn != 0) { if (firstColumn != 0) {
stream.put('\n'); stream.put('\n');
} }
fmt::print( fmt::print(
@ -196,22 +200,21 @@ static void __printMatrix(std::ostream& stream, const Tensor& self, int64_t line
); );
} }
if(printFmt.scale != 1) { if (printFmt.scale != 1) {
fmt::print(stream, "{} *\n{:>{}s}", fmt::print(stream, "{} *\n{:>{}s}", printFmt.scale, "", indent);
printFmt.scale, "", indent);
} }
for (const auto l : c10::irange(self.size(0))) { for (const auto l : c10::irange(self.size(0))) {
Tensor row = self.select(0, l); Tensor row = self.select(0, l);
const double *row_ptr = row.const_data_ptr<double>(); const double* row_ptr = row.const_data_ptr<double>();
for (const auto c : c10::irange(firstColumn, lastColumn+1)) { for (const auto c : c10::irange(firstColumn, lastColumn + 1)) {
printValue(stream, row_ptr[c], printFmt); printValue(stream, row_ptr[c], printFmt);
if(c == lastColumn) { if (c == lastColumn) {
stream.put('\n'); stream.put('\n');
if(l != self.size(0)-1) { if (l != self.size(0) - 1) {
if(printFmt.scale != 1) { if (printFmt.scale != 1) {
fmt::print(stream, "{:>{}s} ", "", indent); fmt::print(stream, "{:>{}s} ", "", indent);
} else { } else {
fmt::print(stream, "{:>{}s}", "", indent); fmt::print(stream, "{:>{}s}", "", indent);
@ -226,18 +229,21 @@ static void __printMatrix(std::ostream& stream, const Tensor& self, int64_t line
} }
} }
static void __printTensor(std::ostream& stream, Tensor& self, int64_t linesize) { static void __printTensor(
std::vector<int64_t> counter(self.ndimension()-2, 0); std::ostream& stream,
Tensor& self,
int64_t linesize) {
std::vector<int64_t> counter(self.ndimension() - 2, 0);
counter[0] = -1; counter[0] = -1;
bool start = true; bool start = true;
bool finished = false; bool finished = false;
while(true) { while (true) {
for(int64_t i = 0; self.ndimension()-2; i++) { for (int64_t i = 0; self.ndimension() - 2; i++) {
counter[i] = counter[i] + 1; counter[i] = counter[i] + 1;
if(counter[i] >= self.size(i)) { if (counter[i] >= self.size(i)) {
if(i == self.ndimension()-3) { if (i == self.ndimension() - 3) {
finished = true; finished = true;
break; break;
} }
@ -246,10 +252,10 @@ static void __printTensor(std::ostream& stream, Tensor& self, int64_t linesize)
break; break;
} }
} }
if(finished) { if (finished) {
break; break;
} }
if(start) { if (start) {
start = false; start = false;
} else { } else {
stream.put('\n'); stream.put('\n');
@ -257,21 +263,24 @@ static void __printTensor(std::ostream& stream, Tensor& self, int64_t linesize)
stream.put('('); stream.put('(');
Tensor tensor = self; Tensor tensor = self;
for (const auto i : c10::irange(self.ndimension()-2)) { for (const auto i : c10::irange(self.ndimension() - 2)) {
tensor = tensor.select(0, counter[i]); tensor = tensor.select(0, counter[i]);
fmt::print(stream, "{},", counter[i]+1); fmt::print(stream, "{},", counter[i] + 1);
} }
fmt::print(stream, ".,.) = \n"); fmt::print(stream, ".,.) = \n");
__printMatrix(stream, tensor, linesize, 1); __printMatrix(stream, tensor, linesize, 1);
} }
} }
void print(const Tensor & t, int64_t linesize) { void print(const Tensor& t, int64_t linesize) {
print(std::cout, t, linesize); print(std::cout, t, linesize);
} }
std::ostream& print(std::ostream& stream, const Tensor & tensor_, int64_t linesize) { std::ostream& print(
if(!tensor_.defined()) { std::ostream& stream,
const Tensor& tensor_,
int64_t linesize) {
if (!tensor_.defined()) {
fmt::print(stream, "[ Tensor (undefined) ]"); fmt::print(stream, "[ Tensor (undefined) ]");
return stream; return stream;
} }
@ -299,15 +308,16 @@ std::ostream& print(std::ostream& stream, const Tensor & tensor_, int64_t linesi
tensor = tensor_.to(kCPU, kDouble).contiguous(); tensor = tensor_.to(kCPU, kDouble).contiguous();
} }
if(tensor.ndimension() == 0) { if (tensor.ndimension() == 0) {
fmt::print(stream, fmt::print(
stream,
"{}\n[ {}{{}}", "{}\n[ {}{{}}",
tensor.const_data_ptr<double>()[0], tensor.const_data_ptr<double>()[0],
tensor_.toString()); tensor_.toString());
} else if(tensor.ndimension() == 1) { } else if (tensor.ndimension() == 1) {
if (tensor.numel() > 0) { if (tensor.numel() > 0) {
auto printFmt = __printFormat(tensor); auto printFmt = __printFormat(tensor);
if(printFmt.scale != 1) { if (printFmt.scale != 1) {
fmt::print(stream, "{} *\n", printFmt.scale); fmt::print(stream, "{} *\n", printFmt.scale);
} }
const double* tensor_p = tensor.const_data_ptr<double>(); const double* tensor_p = tensor.const_data_ptr<double>();
@ -317,12 +327,16 @@ std::ostream& print(std::ostream& stream, const Tensor & tensor_, int64_t linesi
} }
} }
fmt::print(stream, "[ {}{{{}}}", tensor_.toString(), tensor.size(0)); fmt::print(stream, "[ {}{{{}}}", tensor_.toString(), tensor.size(0));
} else if(tensor.ndimension() == 2) { } else if (tensor.ndimension() == 2) {
if (tensor.numel() > 0) { if (tensor.numel() > 0) {
__printMatrix(stream, tensor, linesize, 0); __printMatrix(stream, tensor, linesize, 0);
} }
fmt::print(stream, "[ {}{{{},{}}}", fmt::print(
tensor_.toString(), tensor.size(0), tensor.size(1)); stream,
"[ {}{{{},{}}}",
tensor_.toString(),
tensor.size(0),
tensor.size(1));
} else { } else {
if (tensor.numel() > 0) { if (tensor.numel() > 0) {
__printTensor(stream, tensor, linesize); __printTensor(stream, tensor, linesize);
@ -338,9 +352,13 @@ std::ostream& print(std::ostream& stream, const Tensor & tensor_, int64_t linesi
if (tensor_.is_quantized()) { if (tensor_.is_quantized()) {
fmt::print(stream, ", qscheme: {}", toString(tensor_.qscheme())); fmt::print(stream, ", qscheme: {}", toString(tensor_.qscheme()));
if (tensor_.qscheme() == c10::kPerTensorAffine) { if (tensor_.qscheme() == c10::kPerTensorAffine) {
fmt::print(stream, ", scale: {}, zero_point: {}", fmt::print(
tensor_.q_scale(), tensor_.q_zero_point()); stream,
} else if (tensor_.qscheme() == c10::kPerChannelAffine || ", scale: {}, zero_point: {}",
tensor_.q_scale(),
tensor_.q_zero_point());
} else if (
tensor_.qscheme() == c10::kPerChannelAffine ||
tensor_.qscheme() == c10::kPerChannelAffineFloatQParams) { tensor_.qscheme() == c10::kPerChannelAffineFloatQParams) {
fmt::print(stream, ", scales: "); fmt::print(stream, ", scales: ");
print(stream, tensor_.q_per_channel_scales(), linesize); print(stream, tensor_.q_per_channel_scales(), linesize);
@ -363,4 +381,4 @@ std::ostream& print(std::ostream& stream, const Tensor & tensor_, int64_t linesi
return stream; return stream;
} }
} } // namespace at