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https://github.com/zebrajr/pytorch.git
synced 2025-12-06 00:20:18 +01:00
[BE][Ez]: Enable ClangFormat aten/src/core/Formatting.cpp (#154719)
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
PyTorch MergeBot
parent
f57754e815
commit
2f03673ebf
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@ -64,6 +64,7 @@ include_patterns = [
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'aten/src/ATen/xpu/**/*.cpp',
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'aten/src/ATen/core/boxing/**/*.h',
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'aten/src/ATen/core/dispatch/**/*.h',
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'aten/src/ATen/core/Formatting.cpp',
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'aten/src/ATen/native/mps/**/*.metal',
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'aten/src/ATen/native/mps/**/*.mm',
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'aten/src/ATen/native/mps/**/*.h',
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@ -45,14 +45,14 @@ std::string toString(const Scalar& s) {
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namespace at {
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std::ostream& operator<<(std::ostream & out, const DeprecatedTypeProperties& t) {
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std::ostream& operator<<(std::ostream& out, const DeprecatedTypeProperties& t) {
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return out << t.toString();
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}
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enum class FormatType {
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Default, // 'g' format (defaultfloat equivalent)
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Scientific, // 'e' format with precision 4
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Fixed // 'f' format with precision 4
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Default, // 'g' format (defaultfloat equivalent)
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Scientific, // 'e' format with precision 4
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Fixed // 'f' format with precision 4
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};
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struct PrintFormat {
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@ -61,12 +61,12 @@ struct PrintFormat {
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FormatType type;
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PrintFormat(double s, int w, FormatType t = FormatType::Default)
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: scale(s), width(w), type(t) {}
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: scale(s), width(w), type(t) {}
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};
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static PrintFormat __printFormat(const Tensor& self) {
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auto size = self.numel();
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if(size == 0) {
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if (size == 0) {
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return PrintFormat(1., 0);
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}
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@ -74,8 +74,8 @@ static PrintFormat __printFormat(const Tensor& self) {
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auto self_p = self.const_data_ptr<double>();
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for (const auto i : c10::irange(size)) {
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auto z = self_p[i];
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if(std::isfinite(z)) {
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if(z != std::ceil(z)) {
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if (std::isfinite(z)) {
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if (z != std::ceil(z)) {
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intMode = false;
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break;
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}
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@ -83,28 +83,28 @@ static PrintFormat __printFormat(const Tensor& self) {
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}
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int64_t offset = 0;
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while(offset < size && !std::isfinite(self_p[offset])) {
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while (offset < size && !std::isfinite(self_p[offset])) {
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offset = offset + 1;
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}
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double expMin = 1;
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double expMax = 1;
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if(offset != size) {
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if (offset != size) {
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expMin = std::fabs(self_p[offset]);
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expMax = std::fabs(self_p[offset]);
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for (const auto i : c10::irange(offset, size)) {
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double z = std::fabs(self_p[i]);
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if(std::isfinite(z)) {
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if (std::isfinite(z)) {
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expMin = std::min(expMin, z);
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expMax = std::max(expMax, z);
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}
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}
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if(expMin != 0) {
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if (expMin != 0) {
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expMin = std::floor(std::log10(expMin)) + 1;
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} else {
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expMin = 1;
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}
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if(expMax != 0) {
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if (expMax != 0) {
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expMax = std::floor(std::log10(expMax)) + 1;
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} else {
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expMax = 1;
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@ -114,8 +114,8 @@ static PrintFormat __printFormat(const Tensor& self) {
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double scale = 1;
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int sz = 11;
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if(intMode) {
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if(expMax > 9) {
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if (intMode) {
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if (expMax > 9) {
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sz = 11;
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return PrintFormat(scale, sz, FormatType::Scientific);
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} else {
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@ -123,19 +123,19 @@ static PrintFormat __printFormat(const Tensor& self) {
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return PrintFormat(scale, sz, FormatType::Default);
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}
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} else {
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if(expMax-expMin > 4) {
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if (expMax - expMin > 4) {
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sz = 11;
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if(std::fabs(expMax) > 99 || std::fabs(expMin) > 99) {
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if (std::fabs(expMax) > 99 || std::fabs(expMin) > 99) {
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sz = sz + 1;
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}
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return PrintFormat(scale, sz, FormatType::Scientific);
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} else {
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if(expMax > 5 || expMax < 0) {
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if (expMax > 5 || expMax < 0) {
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sz = 7;
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scale = std::pow(10, expMax-1);
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scale = std::pow(10, expMax - 1);
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return PrintFormat(scale, sz, FormatType::Fixed);
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} else {
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if(expMax == 0) {
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if (expMax == 0) {
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sz = 7;
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} else {
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sz = static_cast<int>(expMax) + 6;
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@ -147,9 +147,9 @@ static PrintFormat __printFormat(const Tensor& self) {
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}
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// Precompiled format specs
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static constexpr auto FMT_G = FMT_COMPILE("{:>{}g}");
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static constexpr auto FMT_E4 = FMT_COMPILE("{:>{}.4e}");
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static constexpr auto FMT_F4 = FMT_COMPILE("{:>{}.4f}");
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static constexpr auto FMT_G = FMT_COMPILE("{:>{}g}");
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static constexpr auto FMT_E4 = FMT_COMPILE("{:>{}.4e}");
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static constexpr auto FMT_F4 = FMT_COMPILE("{:>{}.4f}");
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// Print a single value directly into the stream buffer with no temporaries
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static void printValue(std::ostream& stream, double v, const PrintFormat& pf) {
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@ -157,7 +157,7 @@ static void printValue(std::ostream& stream, double v, const PrintFormat& pf) {
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double val = v / pf.scale;
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switch (pf.type) {
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case FormatType::Default:
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fmt::format_to(out_it, FMT_G, val, pf.width);
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fmt::format_to(out_it, FMT_G, val, pf.width);
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break;
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case FormatType::Scientific:
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fmt::format_to(out_it, FMT_E4, val, pf.width);
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@ -168,57 +168,60 @@ static void printValue(std::ostream& stream, double v, const PrintFormat& pf) {
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}
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}
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static void __printMatrix(std::ostream& stream, const Tensor& self, int64_t linesize, int64_t indent) {
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static void __printMatrix(
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std::ostream& stream,
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const Tensor& self,
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int64_t linesize,
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int64_t indent) {
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auto printFmt = __printFormat(self);
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int64_t nColumnPerLine = (linesize - indent) / (printFmt.width + 1);
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int64_t firstColumn = 0;
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int64_t lastColumn = -1;
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while(firstColumn < self.size(1)) {
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if(firstColumn + nColumnPerLine <= self.size(1)) {
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while (firstColumn < self.size(1)) {
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if (firstColumn + nColumnPerLine <= self.size(1)) {
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lastColumn = firstColumn + nColumnPerLine - 1;
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} else {
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lastColumn = self.size(1) - 1;
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}
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if(nColumnPerLine < self.size(1)) {
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if(firstColumn != 0) {
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stream.put('\n');
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if (nColumnPerLine < self.size(1)) {
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if (firstColumn != 0) {
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stream.put('\n');
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}
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fmt::print(
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stream,
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"Columns {} to {}{:>{}s}",
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firstColumn + 1,
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lastColumn + 1,
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"", // empty string to pad
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indent // width to pad to
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"", // empty string to pad
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indent // width to pad to
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);
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}
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if(printFmt.scale != 1) {
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fmt::print(stream, "{} *\n{:>{}s}",
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printFmt.scale, "", indent);
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if (printFmt.scale != 1) {
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fmt::print(stream, "{} *\n{:>{}s}", printFmt.scale, "", indent);
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}
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for (const auto l : c10::irange(self.size(0))) {
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Tensor row = self.select(0, l);
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const double *row_ptr = row.const_data_ptr<double>();
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const double* row_ptr = row.const_data_ptr<double>();
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for (const auto c : c10::irange(firstColumn, lastColumn+1)) {
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for (const auto c : c10::irange(firstColumn, lastColumn + 1)) {
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printValue(stream, row_ptr[c], printFmt);
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if(c == lastColumn) {
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if (c == lastColumn) {
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stream.put('\n');
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if(l != self.size(0)-1) {
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if(printFmt.scale != 1) {
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if (l != self.size(0) - 1) {
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if (printFmt.scale != 1) {
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fmt::print(stream, "{:>{}s} ", "", indent);
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} else {
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fmt::print(stream, "{:>{}s}", "", indent);
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}
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}
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} else {
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stream.put(' ');
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stream.put(' ');
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}
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}
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}
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@ -226,18 +229,21 @@ static void __printMatrix(std::ostream& stream, const Tensor& self, int64_t line
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}
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}
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static void __printTensor(std::ostream& stream, Tensor& self, int64_t linesize) {
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std::vector<int64_t> counter(self.ndimension()-2, 0);
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static void __printTensor(
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std::ostream& stream,
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Tensor& self,
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int64_t linesize) {
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std::vector<int64_t> counter(self.ndimension() - 2, 0);
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counter[0] = -1;
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bool start = true;
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bool finished = false;
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while(true) {
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for(int64_t i = 0; self.ndimension()-2; i++) {
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while (true) {
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for (int64_t i = 0; self.ndimension() - 2; i++) {
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counter[i] = counter[i] + 1;
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if(counter[i] >= self.size(i)) {
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if(i == self.ndimension()-3) {
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if (counter[i] >= self.size(i)) {
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if (i == self.ndimension() - 3) {
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finished = true;
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break;
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}
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@ -246,10 +252,10 @@ static void __printTensor(std::ostream& stream, Tensor& self, int64_t linesize)
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break;
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}
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}
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if(finished) {
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if (finished) {
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break;
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}
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if(start) {
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if (start) {
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start = false;
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} else {
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stream.put('\n');
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@ -257,21 +263,24 @@ static void __printTensor(std::ostream& stream, Tensor& self, int64_t linesize)
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stream.put('(');
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Tensor tensor = self;
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for (const auto i : c10::irange(self.ndimension()-2)) {
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for (const auto i : c10::irange(self.ndimension() - 2)) {
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tensor = tensor.select(0, counter[i]);
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fmt::print(stream, "{},", counter[i]+1);
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fmt::print(stream, "{},", counter[i] + 1);
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}
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fmt::print(stream, ".,.) = \n");
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__printMatrix(stream, tensor, linesize, 1);
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}
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}
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void print(const Tensor & t, int64_t linesize) {
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void print(const Tensor& t, int64_t linesize) {
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print(std::cout, t, linesize);
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}
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std::ostream& print(std::ostream& stream, const Tensor & tensor_, int64_t linesize) {
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if(!tensor_.defined()) {
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std::ostream& print(
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std::ostream& stream,
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const Tensor& tensor_,
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int64_t linesize) {
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if (!tensor_.defined()) {
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fmt::print(stream, "[ Tensor (undefined) ]");
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return stream;
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}
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@ -299,15 +308,16 @@ std::ostream& print(std::ostream& stream, const Tensor & tensor_, int64_t linesi
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tensor = tensor_.to(kCPU, kDouble).contiguous();
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}
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if(tensor.ndimension() == 0) {
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fmt::print(stream,
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"{}\n[ {}{{}}",
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tensor.const_data_ptr<double>()[0],
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tensor_.toString());
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} else if(tensor.ndimension() == 1) {
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if (tensor.ndimension() == 0) {
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fmt::print(
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stream,
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"{}\n[ {}{{}}",
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tensor.const_data_ptr<double>()[0],
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tensor_.toString());
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} else if (tensor.ndimension() == 1) {
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if (tensor.numel() > 0) {
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auto printFmt = __printFormat(tensor);
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if(printFmt.scale != 1) {
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if (printFmt.scale != 1) {
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fmt::print(stream, "{} *\n", printFmt.scale);
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}
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const double* tensor_p = tensor.const_data_ptr<double>();
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@ -317,12 +327,16 @@ std::ostream& print(std::ostream& stream, const Tensor & tensor_, int64_t linesi
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}
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}
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fmt::print(stream, "[ {}{{{}}}", tensor_.toString(), tensor.size(0));
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} else if(tensor.ndimension() == 2) {
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} else if (tensor.ndimension() == 2) {
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if (tensor.numel() > 0) {
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__printMatrix(stream, tensor, linesize, 0);
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}
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fmt::print(stream, "[ {}{{{},{}}}",
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tensor_.toString(), tensor.size(0), tensor.size(1));
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fmt::print(
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stream,
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"[ {}{{{},{}}}",
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tensor_.toString(),
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tensor.size(0),
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tensor.size(1));
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} else {
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if (tensor.numel() > 0) {
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__printTensor(stream, tensor, linesize);
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@ -338,10 +352,14 @@ std::ostream& print(std::ostream& stream, const Tensor & tensor_, int64_t linesi
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if (tensor_.is_quantized()) {
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fmt::print(stream, ", qscheme: {}", toString(tensor_.qscheme()));
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if (tensor_.qscheme() == c10::kPerTensorAffine) {
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fmt::print(stream, ", scale: {}, zero_point: {}",
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tensor_.q_scale(), tensor_.q_zero_point());
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} else if (tensor_.qscheme() == c10::kPerChannelAffine ||
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tensor_.qscheme() == c10::kPerChannelAffineFloatQParams) {
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fmt::print(
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stream,
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", scale: {}, zero_point: {}",
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tensor_.q_scale(),
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tensor_.q_zero_point());
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} else if (
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tensor_.qscheme() == c10::kPerChannelAffine ||
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tensor_.qscheme() == c10::kPerChannelAffineFloatQParams) {
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fmt::print(stream, ", scales: ");
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print(stream, tensor_.q_per_channel_scales(), linesize);
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fmt::print(stream, ", zero_points: ");
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@ -363,4 +381,4 @@ std::ostream& print(std::ostream& stream, const Tensor & tensor_, int64_t linesi
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return stream;
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}
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}
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} // namespace at
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