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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/74353 Repatched `d00de0d43598522b8f6ab2de553b6aaf6768faa5` by Nora Belrose (norabelrose). With following changes: * Register fake source of generated methods in linecache so that inspect.get_source will succeed. * this patching is only triggered if the given dataclass passed to torch.jit.script previously. Effectively we make this feature opt-in. ## Original Summary: Fixes https://github.com/pytorch/pytorch/issues/72901. Since we can't get access to the source code for synthesized magic methods on dataclasses, we have to synthesize our own versions. torch/jit/_dataclass_impls.py has the code that does this. What's supported Synthesized __init__, __eq__, and the comparison magic methods when order=True is set on the dataclass decorator Default values for fields __post_init__, including using InitVar fields inside of __post_init__, on Python 3.8+ Overriding __eq__ or any of the comparison magic methods to provide your own implementation What's not supported Default factory initializers for fields Frozen dataclasses InitVar on Python 3.7 __repr__ and __hash__ (these are actually implemented, but the TorchScript interpreter won't call them) Using the != operator on dataclasses inside TorchScript; this is because TorchScript requires that you implement __ne__ to use this operator, whereas in regular Python the != operator will resolve to the negation of whatever is returned by __eq__ if there's no __ne__. Dataclasses don't actually synthesize an __ne__ method for this reason. I've been toying with different ways to fix this but != is not working in this PR at the moment. Pull Request resolved: https://github.com/pytorch/pytorch/pull/74889 Test Plan: unittest Also run previously failed test: ``` buck test mode/dev-nosan //fblearner/flow/projects/fluent2/definition/transformers/contrib/faim/test:tests -- --exact 'fblearner/flow/projects/fluent2/definition/transformers/contrib/faim/test:tests - test_mixmatch_multiclass (fblearner.flow.projects.fluent2.definition.transformers.contrib.faim.test.faim_mixmatch_test.TestFaimTransformerMixMatch)' ``` passes Reviewed By: zhxchen17 Differential Revision: D35206262 Pulled By: qihqi Pull Request resolved: https://github.com/pytorch/pytorch/pull/76771 Approved by: https://github.com/seemethere
113 lines
4.2 KiB
Python
113 lines
4.2 KiB
Python
import ast
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import functools
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import inspect
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from textwrap import dedent
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from typing import Any, Optional, Tuple, List, NamedTuple
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from torch._C import ErrorReport
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from torch._C._jit_tree_views import SourceRangeFactory
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def get_source_lines_and_file(
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obj: Any,
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error_msg: Optional[str] = None,
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) -> Tuple[List[str], int, Optional[str]]:
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"""
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Wrapper around inspect.getsourcelines and inspect.getsourcefile.
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Returns: (sourcelines, file_lino, filename)
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"""
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filename = None # in case getsourcefile throws
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try:
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filename = inspect.getsourcefile(obj)
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sourcelines, file_lineno = inspect.getsourcelines(obj)
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except OSError as e:
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msg = (f"Can't get source for {obj}. TorchScript requires source access in "
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"order to carry out compilation, make sure original .py files are "
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"available.")
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if error_msg:
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msg += '\n' + error_msg
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raise OSError(msg) from e
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return sourcelines, file_lineno, filename
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def normalize_source_lines(sourcelines: List[str]) -> List[str]:
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"""
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This helper function accepts a list of source lines. It finds the
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indentation level of the function definition (`def`), then it indents
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all lines in the function body to a point at or greater than that
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level. This allows for comments and continued string literals that
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are at a lower indentation than the rest of the code.
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Args:
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sourcelines: function source code, separated into lines by
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the '\n' character
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Returns:
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A list of source lines that have been correctly aligned
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"""
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def remove_prefix(text, prefix):
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return text[text.startswith(prefix) and len(prefix):]
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# Find the line and line number containing the function definition
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idx = None
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for i, l in enumerate(sourcelines):
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if l.lstrip().startswith("def"):
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idx = i
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break
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# This will happen when the function is a lambda- we won't find "def" anywhere in the source
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# lines in that case. Currently trying to JIT compile a lambda will throw an error up in
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# `parse_def()`, but we might want to handle this case in the future.
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if idx is None:
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return sourcelines
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# Get a string representing the amount of leading whitespace
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fn_def = sourcelines[idx]
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whitespace = fn_def.split("def")[0]
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# Add this leading whitespace to all lines before and after the `def`
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aligned_prefix = [whitespace + remove_prefix(s, whitespace) for s in sourcelines[:idx]]
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aligned_suffix = [whitespace + remove_prefix(s, whitespace) for s in sourcelines[idx + 1:]]
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# Put it together again
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aligned_prefix.append(fn_def)
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return aligned_prefix + aligned_suffix
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# Thin wrapper around SourceRangeFactory to store extra metadata
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# about the function-to-be-compiled.
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class SourceContext(SourceRangeFactory):
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def __init__(self, source, filename, file_lineno, leading_whitespace_len, uses_true_division=True, funcname=None):
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super(SourceContext, self).__init__(source, filename, file_lineno, leading_whitespace_len)
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self.uses_true_division = uses_true_division
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self.filename = filename
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self.funcname = funcname
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@functools.lru_cache(maxsize=None)
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def make_source_context(*args):
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return SourceContext(*args)
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def fake_range():
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return SourceContext('', None, 0, 0).make_raw_range(0, 1)
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class ParsedDef(NamedTuple):
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ast: ast.Module
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ctx: SourceContext
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source: str
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filename: Optional[str]
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file_lineno: int
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def parse_def(fn):
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sourcelines, file_lineno, filename = get_source_lines_and_file(fn, ErrorReport.call_stack())
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sourcelines = normalize_source_lines(sourcelines)
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source = ''.join(sourcelines)
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dedent_src = dedent(source)
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py_ast = ast.parse(dedent_src)
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if len(py_ast.body) != 1 or not isinstance(py_ast.body[0], ast.FunctionDef):
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raise RuntimeError(f"Expected a single top-level function: {filename}:{file_lineno}")
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leading_whitespace_len = len(source.split('\n', 1)[0]) - len(dedent_src.split('\n', 1)[0])
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ctx = make_source_context(source, filename, file_lineno, leading_whitespace_len, True, fn.__name__)
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return ParsedDef(py_ast, ctx, source, filename, file_lineno)
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