Files
pytorch/torch/utils/_traceback.py
zabboud 7f9fafed53 Resolve docstring errors in throughput_benchmark.py, weak.py, _traceback.py, file_baton.py, _contextlib.py, _device.py, cpp_backtrace.py, bundled_inputs.py, run_cpu.py, hooks.py, mobile_optimizer.py, _freeze.py, __init__.py, mkldnn.py, dlpack.py (#113311)
Fixes #112633

Fixed errors relating to pydocstyle in the following files. The remaining errors are not covered in this issue. `torch/utils/dlpack.py` was not modified as the errors are relating to the function signature in the first line in the docstring which must be maintained as is for proper Sphinx interpretation.

```python
def from_dlpack(ext_tensor: Any) -> 'torch.Tensor':
    """from_dlpack(ext_tensor) -> Tensor
         .....
    """
```

pydocstyle torch/utils/_contextlib.py --count
before: 4
after: 0

pydocstyle torch/backends/mps/__init__.py --count
before: 8
after: 1

**remaining errors**
```
torch/backends/mps/__init__.py:1 at module level:
        D104: Missing docstring in public package
```

pydocstyle torch/backends/xeon/run_cpu.py --count
before: 13
after: 1

**remaining errors**
```
torch/backends/xeon/run_cpu.py:864 in public function `main`:
        D103: Missing docstring in public function
```

pydocstyle torch/backends/cpu/__init__.py --count
before: 2
after: 1

**remaining errors**
```
torch/backends/cpu/__init__.py:1 at module level:
        D104: Missing docstring in public package
```

pydocstyle torch/utils/cpp_backtrace.py --count
before: 4
after: 1

**remaining errors**
```
torch/utils/cpp_backtrace.py:1 at module level:
        D100: Missing docstring in public module
```

pydocstyle torch/utils/bundled_inputs.py --count
before: 8
after: 1

**remaining errors**
```
torch/utils/bundled_inputs.py:1 at module level:
        D100: Missing docstring in public module
```

pydocstyle torch/utils/file_baton.py --count
before: 8
after: 1

**remaining errors**
```
torch/utils/file_baton.py:1 at module level:
        D100: Missing docstring in public module
```

pydocstyle torch/utils/mobile_optimizer.py --count
before: 6
after: 1

**remaining errors**
```
torch/utils/mobile_optimizer.py:8 in public class `LintCode`:
        D101: Missing docstring in public class
```

pydocstyle torch/backends/opt_einsum/__init__.py --count
before: 7
after: 5

**remaining errors**
```
torch/backends/opt_einsum/__init__.py:1 at module level:
        D104: Missing docstring in public package
torch/backends/opt_einsum/__init__.py:67 in public function `set_flags`:
        D103: Missing docstring in public function
torch/backends/opt_einsum/__init__.py:77 in public function `flags`:
        D103: Missing docstring in public function
torch/backends/opt_einsum/__init__.py:93 in public class `OptEinsumModule`:
        D101: Missing docstring in public class
torch/backends/opt_einsum/__init__.py:94 in public method `__init__`:
        D107: Missing docstring in __init__
```

pydocstyle torch/utils/_device.py --count
before:  9
after: 6

**remaining errors**
```
torch/utils/_device.py:58 in public class `DeviceContext`:
        D101: Missing docstring in public class
torch/utils/_device.py:59 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/_device.py:62 in public method `__enter__`:
        D105: Missing docstring in magic method
torch/utils/_device.py:68 in public method `__exit__`:
        D105: Missing docstring in magic method
torch/utils/_device.py:73 in public method `__torch_function__`:
        D105: Missing docstring in magic method
torch/utils/_device.py:80 in public function `device_decorator`:
        D103: Missing docstring in public function

```

pydocstyle torch/utils/_freeze.py --count
before: 15
after: 7

**remaining errors**
```
torch/utils/_freeze.py:77 in public function `indent_msg`:
        D103: Missing docstring in public function
torch/utils/_freeze.py:89 in public class `FrozenModule`:
        D101: Missing docstring in public class
torch/utils/_freeze.py:100 in public class `Freezer`:
        D101: Missing docstring in public class
torch/utils/_freeze.py:101 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/_freeze.py:106 in public method `msg`:
        D102: Missing docstring in public method
torch/utils/_freeze.py:185 in public method `get_module_qualname`:
        D102: Missing docstring in public method
torch/utils/_freeze.py:206 in public method `compile_string`:
        D102: Missing docstring in public method

```

pydocstyle torch/utils/throughput_benchmark.py --count
before: 25
after: 8
**remaining errors**
```
torch/utils/throughput_benchmark.py:1 at module level:
        D100: Missing docstring in public module
torch/utils/throughput_benchmark.py:27 in public class `ExecutionStats`:
        D101: Missing docstring in public class
torch/utils/throughput_benchmark.py:28 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/throughput_benchmark.py:33 in public method `latency_avg_ms`:
        D102: Missing docstring in public method
torch/utils/throughput_benchmark.py:37 in public method `num_iters`:
        D102: Missing docstring in public method
torch/utils/throughput_benchmark.py:46 in public method `total_time_seconds`:
        D102: Missing docstring in public method
torch/utils/throughput_benchmark.py:50 in public method `__str__`:
        D105: Missing docstring in magic method
torch/utils/throughput_benchmark.py:94 in public method `__init__`:
        D107: Missing docstring in __init__

```

pydocstyle torch/utils/hooks.py --count

before: 14
after: 11

**remaining errors**
```
torch/utils/hooks.py:1 at module level:
        D100: Missing docstring in public module
torch/utils/hooks.py:23 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/hooks.py:34 in public method `remove`:
        D102: Missing docstring in public method
torch/utils/hooks.py:44 in public method `__getstate__`:
        D105: Missing docstring in magic method
torch/utils/hooks.py:50 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/hooks.py:64 in public method `__enter__`:
        D105: Missing docstring in magic method
torch/utils/hooks.py:67 in public method `__exit__`:
        D105: Missing docstring in magic method
torch/utils/hooks.py:82 in public function `warn_if_has_hooks`:
        D103: Missing docstring in public function
torch/utils/hooks.py:103 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/hooks.py:188 in public method `setup_input_hook`:
        D102: Missing docstring in public method
torch/utils/hooks.py:197 in public method `setup_output_hook`:
        D102: Missing docstring in public method
```

pydocstyle torch/utils/_traceback.py --count
before: 19
after: 14

**remaining errors**
```
torch/utils/_traceback.py:47 in public function `report_compile_source_on_error`:
        D103: Missing docstring in public function
torch/utils/_traceback.py:160 in public class `CapturedTraceback`:
        D101: Missing docstring in public class
torch/utils/_traceback.py:163 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/_traceback.py:167 in public method `cleanup`:
        D102: Missing docstring in public method
torch/utils/_traceback.py:170 in public method `summary`:
        D102: Missing docstring in public method
torch/utils/_traceback.py:182 in public method `__getstate__`:
        D105: Missing docstring in magic method
torch/utils/_traceback.py:190 in public method `extract`:
        D205: 1 blank line required between summary line and description (found 0)
torch/utils/_traceback.py:190 in public method `extract`:
        D400: First line should end with a period (not 't')
torch/utils/_traceback.py:213 in public method `format`:
        D205: 1 blank line required between summary line and description (found 0)
torch/utils/_traceback.py:213 in public method `format`:
        D400: First line should end with a period (not 'f')
torch/utils/_traceback.py:213 in public method `format`:
        D401: First line should be in imperative mood (perhaps 'Format', not 'Formats')
torch/utils/_traceback.py:224 in public method `format_all`:
        D200: One-line docstring should fit on one line with quotes (found 3)
torch/utils/_traceback.py:247 in private function `_extract_symbolized_tb`:
        D205: 1 blank line required between summary line and description (found 0)
torch/utils/_traceback.py:247 in private function `_extract_symbolized_tb`:
        D400: First line should end with a period (not 'f')
```

pydocstyle torch/utils/mkldnn.py --count
before: 28
after: 26

**remaining errors**
```
torch/utils/mkldnn.py:1 at module level:
        D100: Missing docstring in public module
torch/utils/mkldnn.py:4 in public class `MkldnnLinear`:
        D101: Missing docstring in public class
torch/utils/mkldnn.py:5 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/mkldnn.py:19 in public method `__getstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:23 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:29 in public method `forward`:
        D102: Missing docstring in public method
torch/utils/mkldnn.py:75 in public class `MkldnnConv1d`:
        D101: Missing docstring in public class
torch/utils/mkldnn.py:76 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/mkldnn.py:82 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:88 in public class `MkldnnConv2d`:
        D101: Missing docstring in public class
torch/utils/mkldnn.py:89 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/mkldnn.py:100 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:110 in public class `MkldnnConv3d`:
        D101: Missing docstring in public class
torch/utils/mkldnn.py:111 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/mkldnn.py:122 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:133 in public class `MkldnnBatchNorm`:
        D101: Missing docstring in public class
torch/utils/mkldnn.py:136 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/mkldnn.py:155 in public method `__getstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:163 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:171 in public method `forward`:
        D102: Missing docstring in public method
torch/utils/mkldnn.py:184 in public class `MkldnnPrelu`:
        D101: Missing docstring in public class
torch/utils/mkldnn.py:185 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/mkldnn.py:190 in public method `__getstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:194 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:199 in public method `forward`:
        D102: Missing docstring in public method
torch/utils/mkldnn.py:205 in public function `to_mkldnn`:
        D103: Missing docstring in public function
```

pydocstyle torch/utils/weak.py --count
before: 32
after: 30

**remaining errors**
```
torch/utils/weak.py:1 at module level:
        D100: Missing docstring in public module
torch/utils/weak.py:42 in public class `WeakIdRef`:
        D101: Missing docstring in public class
torch/utils/weak.py:45 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/weak.py:54 in public method `__call__`:
        D102: Missing docstring in public method
torch/utils/weak.py:61 in public method `__hash__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:64 in public method `__eq__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:84 in public class `WeakIdKeyDictionary`:
        D101: Missing docstring in public class
torch/utils/weak.py:87 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/weak.py:131 in public method `__delitem__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:135 in public method `__getitem__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:138 in public method `__len__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:145 in public method `__repr__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:148 in public method `__setitem__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:151 in public method `copy`:
        D102: Missing docstring in public method
torch/utils/weak.py:162 in public method `__deepcopy__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:172 in public method `get`:
        D102: Missing docstring in public method
torch/utils/weak.py:175 in public method `__contains__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:182 in public method `items`:
        D102: Missing docstring in public method
torch/utils/weak.py:189 in public method `keys`:
        D102: Missing docstring in public method
torch/utils/weak.py:198 in public method `values`:
        D102: Missing docstring in public method
torch/utils/weak.py:216 in public method `popitem`:
        D102: Missing docstring in public method
torch/utils/weak.py:224 in public method `pop`:
        D102: Missing docstring in public method
torch/utils/weak.py:228 in public method `setdefault`:
        D102: Missing docstring in public method
torch/utils/weak.py:231 in public method `update`:
        D102: Missing docstring in public method
torch/utils/weak.py:241 in public method `__ior__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:245 in public method `__or__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:252 in public method `__ror__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:262 in public method `__eq__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:276 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/weak.py:280 in public method `__call__`:
        D102: Missing docstring in public method

```

@mikaylagawarecki @jbschlosser @svekars
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113311
Approved by: https://github.com/ezyang
2023-11-15 17:40:04 +00:00

255 lines
10 KiB
Python

from types import TracebackType
from typing import List, Optional
import tempfile
import traceback
import contextlib
import inspect
import os.path
# This file contains utilities for ensuring dynamically compile()'d
# code fragments display their line numbers in backtraces.
#
# The constraints:
#
# - We don't have control over the user exception printer (in particular,
# we cannot assume the linecache trick will work, c.f.
# https://stackoverflow.com/q/50515651/23845 )
#
# - We don't want to create temporary files every time we compile()
# some code; file creation should happen lazily only at exception
# time. Arguably, you *should* be willing to write out your
# generated Python code to file system, but in some situations
# (esp. library code) it would violate user expectation to write
# to the file system, so we try to avoid it. In particular, we'd
# like to keep the files around, so users can open up the files
# mentioned in the trace; if the file is invisible, we want to
# avoid clogging up the filesystem.
#
# If this is not a constraint for you, there is a substantially simpler
# way to implement the functionality in this PR: instead of using
# eval/exec directly, just always write a Python file to filesystem
# and compile that.
#
# - You have control over a context where the compiled code will get
# executed, so that we can interpose while the stack is unwinding
# (otherwise, we have no way to interpose on the exception printing
# process.)
#
# There are two things you have to do to make use of the utilities here:
#
# - When you compile your source code, you must save its string source
# in its f_globals under the magic name "__compile_source__"
#
# - Before running the compiled code, enter the
# report_compile_source_on_error() context manager.
@contextlib.contextmanager
def report_compile_source_on_error():
try:
yield
except Exception as exc:
tb = exc.__traceback__
# Walk the traceback, looking for frames that have
# source attached
stack = []
while tb is not None:
filename = tb.tb_frame.f_code.co_filename
source = tb.tb_frame.f_globals.get("__compile_source__")
if filename == "<string>" and source is not None:
# What black magic are we doing here? Intuitively, what
# we would like to do is overwrite the co_filename on any
# frames that were generated from exec/eval so that they
# point to a temporary file that has the actual line
# information, so Python's default error printer can print
# useful line information on it.
#
# Writing out the temporary file is easy. But overwriting
# co_filename is not! You can't modify the code object
# associated with a frame. You can, however, reconstruct
# a traceback with entirely new frames from scratch, so that's
# what we do. But there's another problem, which is how to
# make the frame?
#
# The black magic is we make a frankenstein frame and code
# object which resembles the original frame/code enough so
# that it will print properly under traceback and the default
# error printer, but IT IS NOT THE ORIGINAL FRAME (you
# couldn't, e.g., execute its code with different variables
# and expect it to work.)
# Don't delete the temporary file so the user can inspect it
# TODO: This creates a temporary file for every frame, but we
# technically only need one per distinct __compile_source__
with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix=".py") as f:
f.write(source)
# Create a frame. Python doesn't let you construct
# FrameType directly, so just make one with compile
frame = tb.tb_frame
code = compile('__inspect_currentframe()', f.name, 'eval')
code = code.replace(co_name=frame.f_code.co_name)
# Python 3.11 only
if hasattr(frame.f_code, 'co_linetable'):
# We can't copy ALL of the metadata over, because you
# can cause Python to segfault this way. What exactly
# do we need? We need enough information for
# traceback to be able to print the exception
# correctly. Code reading Lib/traceback.py reveals
# that traceback calls code.co_positions() in order to
# get the augmented line/col numbers. Objects/codeobject.c,
# specifically _PyCode_InitAddressRange, reveals that
# this iterator is initialized from co_linetable and
# co_firstfileno. So copy these we must!
code = code.replace( # type: ignore[call-arg]
co_linetable=frame.f_code.co_linetable, # type: ignore[attr-defined]
co_firstlineno=frame.f_code.co_firstlineno, # type: ignore[attr-defined]
)
fake_frame = eval(
code,
frame.f_globals,
{
**frame.f_locals,
'__inspect_currentframe': inspect.currentframe
}
)
fake_tb = TracebackType(
None, fake_frame, tb.tb_lasti, tb.tb_lineno
)
stack.append(fake_tb)
else:
stack.append(tb)
tb = tb.tb_next
# Reconstruct the linked list
tb_next = None
for tb in reversed(stack):
tb.tb_next = tb_next
tb_next = tb
raise exc.with_traceback(tb_next) # noqa: TRY200
def shorten_filename(fn, *, base=None):
"""Shorten a source filepath, with the assumption that torch/ subdirectories don't need to be shown to user."""
if base is None:
base = os.path.dirname(os.path.dirname(__file__))
# Truncate torch/foo.py to foo.py
try:
prefix = os.path.commonpath([fn, base])
except ValueError:
return fn
else:
return fn[len(prefix) + 1:]
def format_frame(frame, *, base=None, line=False):
"""
Format a FrameSummary in a short way, without printing full absolute path or code.
The idea is the result fits on a single line.
"""
extra_line = ""
if line:
extra_line = f"{frame.line} # "
return f"{extra_line}{shorten_filename(frame.filename, base=base)}:{frame.lineno} in {frame.name}"
def format_traceback_short(tb):
"""Format a TracebackType in a short way, printing only the inner-most frame."""
return format_frame(traceback.extract_tb(tb)[-1])
class CapturedTraceback:
__slots__ = ['tb', 'skip']
def __init__(self, tb, skip=0):
self.tb = tb
self.skip = skip
def cleanup(self):
self.tb = None
def summary(self):
import torch._C._profiler
if self.tb is None:
# TODO: Maybe indicate that the traceback was elided?
return traceback.StackSummary()
return _extract_symbolized_tb(
torch._C._profiler.symbolize_tracebacks([self.tb])[0],
self.skip
)
def __getstate__(self):
return (None, {
'tb': None, # TB is not pickleable
'skip': self.skip,
})
@staticmethod
def extract(*, script=False, cpp=False, skip=0):
"""
Like traceback.extract_stack(), but faster (approximately 20x faster); it
is fast enough that you can unconditionally log stacks this way as part of
normal execution. It returns a torch._C._profiler.CapturedTraceback
object that must be formatted specially with format_captured_tb.
By default, this only reports Python backtraces (like extract_stack). You
can set the script/cpp kwargs to also turn on TorchScript/C++ trace
reporting.
"""
import torch._C._profiler
if script or cpp:
assert skip == 0, "skip with script/cpp NYI"
return CapturedTraceback(
torch._C._profiler.gather_traceback(python=True, script=script, cpp=cpp),
# Elide extract() frame if we don't have script/cpp frames. If
# we do have those frames, it doesn't work so force zero.
0 if script or cpp else skip + 1
)
def format(self):
"""
Formats a single torch._C._profiler.CapturedTraceback into a list of
strings equivalent to the output of traceback.format_list. Note that if
pass it CapturedTraceback with C++ traces, it is better not to use this
function and use the batch formatting API format_captured_tbs to amortize
the cost of symbolization
"""
return traceback.format_list(self.summary())
@staticmethod
def format_all(tbs):
"""
Bulk version of CapturedTraceback.format. Returns a list of list of strings.
"""
import torch._C._profiler
# Directly populate tracebacks that already have cached summaries
rs: List[Optional[List[str]]] = []
delayed_idxs = []
for i, tb in enumerate(tbs):
if tb.tb is None:
rs.append([])
else:
rs.append(None)
delayed_idxs.append(i)
stbs = torch._C._profiler.symbolize_tracebacks([tbs[i].tb for i in delayed_idxs])
for i, stb in zip(delayed_idxs, stbs):
rs[i] = traceback.format_list(tbs[i].summary())
return rs
def _extract_symbolized_tb(tb, skip):
"""
Given a symbolized traceback from symbolize_tracebacks, return a StackSummary object of
pre-processed stack trace entries.
"""
stack = traceback.StackSummary()
for f in reversed(tb[skip:]):
stack.append(traceback.FrameSummary(f['filename'], f['line'], f['name']))
return stack