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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/33834 This changes how we report Tracebacks to make them more clear when there are both serialized and non-serialized ranges. It now looks like: ``` Traceback (most recent call last): File "foo.py", line 25, in <module> s2(a, b) File "/scratch/zdevito/pytorch/torch/nn/modules/module.py", line 550, in __call__ result = self.forward(*input, **kwargs) RuntimeError: The following operation failed in the TorchScript interpreter. Traceback of TorchScript, serialized code (most recent call last): File "code/__torch__.py", line 7, in forward x: Tensor, y: Tensor) -> Tensor: return (self).bar(x, y, ) ~~~~~~~~~ <--- HERE def bar(self: __torch__.Moo, x: Tensor, File "code/__torch__.py", line 11, in bar x: Tensor, y: Tensor) -> Tensor: _0 = (self).baz(x, y, ) ~~~~~~~~~ <--- HERE _1 = torch.ones([3], dtype=None, layout=None, device=None, pin_memory=None) return torch.add(_0, _1, alpha=1) File "code/__torch__.py", line 17, in baz x: Tensor, y: Tensor) -> Tensor: return torch.add(x, y, alpha=1) ~~~~~~~~~ <--- HERE Traceback of TorchScript, original code (most recent call last): File "foo.py", line 11, in forward def forward(self, x, y): return self.bar(x, y) ~~~~~~~~ <--- HERE File "foo.py", line 9, in bar def bar(self, x, y): return self.baz(x, y) + torch.ones(3) ~~~~~~~~ <--- HERE File "foo.py", line 7, in baz def baz(self, x, y): return x + y ~~~~~ <--- HERE RuntimeError: The size of tensor a (4) must match the size of tensor b (5) at non-singleton dimension 1 ``` It follows Python convension of having the most important information last and reading from the bottom up. Changes: * Moved the error message to the end, to copy Python * Report original traceback separate from serialized traceback * Make sure root functions have names in the interpreter trace. Test Plan: Imported from OSS Differential Revision: D20126136 Pulled By: zdevito fbshipit-source-id: fd01f9985e5d74e04c4d064c02e8bc320f4fac13
132 lines
4.2 KiB
C++
132 lines
4.2 KiB
C++
#include <torch/csrc/jit/frontend/source_range.h>
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#include <torch/csrc/jit/serialization/source_range_serialization.h>
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namespace torch {
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namespace jit {
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c10::optional<SourceRange> Source::findSourceRangeThatGenerated(
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const SourceRange& range) {
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if (!gen_ranges_) {
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return c10::nullopt;
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}
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return gen_ranges_->findSourceRangeThatGenerated(range);
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}
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C10_EXPORT void SourceRange::highlight(std::ostream& out) const {
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// Retrieve original SourceRange, if present.
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if (auto orig_source_range = findSourceRangeThatGenerated()) {
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orig_source_range->highlight(out);
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out << "Serialized ";
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}
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print_with_context(out, CONTEXT, true, "");
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}
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C10_EXPORT void format_stack_trace(std::ostream& out, const std::vector<StackEntry>& entries) {
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bool has_orig_ranges = false;
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std::vector<SourceRange> orig_ranges;
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// gather original ranges. if we have a situation where we do not have orig
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// ranges for some frames, we still want to report them for the frames we do
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// have,
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// so substitute the current range for that frame
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for (const StackEntry& entry : entries) {
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if (auto orig_source_range = entry.range.findSourceRangeThatGenerated()) {
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orig_ranges.emplace_back(std::move(orig_source_range.value()));
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has_orig_ranges = true;
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} else {
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orig_ranges.emplace_back(entry.range);
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}
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}
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out << "Traceback of TorchScript";
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if (has_orig_ranges) {
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out << ", serialized code";
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}
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out << " (most recent call last):\n";
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for (const StackEntry& entry : entries) {
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entry.range.print_with_context(
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out, SourceRange::CONTEXT, true, entry.filename);
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}
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if (has_orig_ranges) {
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out << "\nTraceback of TorchScript, original code (most recent call last):\n";
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auto it = entries.begin();
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for (const SourceRange& range : orig_ranges) {
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range.print_with_context(
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out, SourceRange::CONTEXT, true, (*it++).filename);
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}
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}
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}
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C10_EXPORT void SourceRange::print_with_context(
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std::ostream& out,
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size_t context,
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bool highlight,
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const std::string& funcname) const {
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// This is an empty SourceRange, used as a sentinel value.
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if (!source_) {
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return;
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}
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const std::string& str = source_->text();
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if (size() == str.size()) {
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// this is just the entire file, not a subset, so print it out.
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// primarily used to print out python stack traces
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out << str;
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return;
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}
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size_t begin_line = start(); // beginning of line to highlight
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size_t end_line = start(); // end of line to highlight
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while (begin_line > 0 && str[begin_line - 1] != '\n')
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--begin_line;
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while (end_line < str.size() && str[end_line] != '\n')
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++end_line;
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AT_ASSERT(begin_line == 0 || str[begin_line - 1] == '\n');
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AT_ASSERT(end_line == str.size() || str[end_line] == '\n');
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size_t begin_highlight = begin_line; // beginning of context, CONTEXT lines
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// before the highlight line
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for (size_t i = 0; begin_highlight > 0; --begin_highlight) {
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if (str[begin_highlight - 1] == '\n')
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++i;
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if (i >= context) {
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break;
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}
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}
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AT_ASSERT(begin_highlight == 0 || str[begin_highlight - 1] == '\n');
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size_t end_highlight =
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end_line; // end of context, CONTEXT lines after the highlight line
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for (size_t i = 0; end_highlight < str.size(); ++end_highlight) {
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if (str[end_highlight] == '\n')
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++i;
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if (i >= context) {
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break;
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}
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}
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AT_ASSERT(end_highlight == str.size() || str[end_highlight] == '\n');
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if (auto flc = file_line_col()) {
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std::string filename;
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size_t line, col;
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std::tie(filename, line, col) = *flc;
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out << " File \"" << filename << "\", line " << line;
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if (funcname != "") {
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out << ", in " << funcname;
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}
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out << "\n";
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}
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out << str.substr(begin_highlight, end_line - begin_highlight) << "\n";
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if (highlight) {
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out << std::string(start() - begin_line, ' ');
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size_t len = std::min(size(), end_line - start());
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out << std::string(len, '~')
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<< (len < size() ? "... <--- HERE" : " <--- HERE");
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}
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auto line_substr = str.substr(end_line, end_highlight - end_line);
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out << line_substr;
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if (!line_substr.empty() && line_substr.back() != '\n')
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out << "\n";
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}
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} // namespace jit
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} // namespace torch
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