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| import os | |
| import sys | |
| from typing import Optional | |
| # [@compile_ignored: debug] Uses z3 for validating the guard optimizations transformations. | |
| translation_validation = ( | |
| os.environ.get("TORCHDYNAMO_TRANSLATION_VALIDATION", "0") == "1" | |
| ) | |
| # Timeout (in milliseconds) for z3 finding a solution. | |
| # [@compile_ignored: debug] | |
| translation_validation_timeout = int( | |
| os.environ.get("TORCHDYNAMO_TRANSLATION_VALIDATION_TIMEOUT", "600000") | |
| ) | |
| # Disables bisection for translation validation. | |
| # | |
| # Translation validation bisection is enabled by default, if translation validation | |
| # is also enabled. This should help finding guard simplification issues. However, | |
| # since validation uses Z3 for bisecting, it might take a lot of time. | |
| # | |
| # Set this configuration option so as to avoid bisecting. | |
| # [@compile_ignored: debug] | |
| translation_validation_no_bisect = ( | |
| os.environ.get("TORCHDYNAMO_TRANSLATION_NO_BISECT", "0") == "1" | |
| ) | |
| # Checks whether replaying ShapeEnv events on a freshly constructed one yields | |
| # the a ShapeEnv with the same state. This should be used only in testing. | |
| check_shape_env_recorded_events = False | |
| # TODO: Perhaps consider allowing unions for the configs below (so you can hit | |
| # multiple reps at the same time) | |
| # Give extended debug information if the string representation of a guard | |
| # matches this. For example, set this to "Ne(s0, 10)" and whenever we issue | |
| # this guard, we will generate full Python and C++ backtrace | |
| # [@compile_ignored: debug] | |
| extended_debug_guard_added = os.environ.get( | |
| "TORCHDYNAMO_EXTENDED_DEBUG_GUARD_ADDED", None | |
| ) | |
| # Give extended debug information when a particular symbol is allocated. For | |
| # example, set this to "u2" and whenever we create this symbol, we will | |
| # generate full Python and C++ backtrace | |
| # [@compile_ignored: debug] | |
| extended_debug_create_symbol = os.environ.get( | |
| "TORCHDYNAMO_EXTENDED_DEBUG_CREATE_SYMBOL", None | |
| ) | |
| # Give extended debug information (C++ backtrace) for all extended debug | |
| # settings as well as errors. The C++ backtrace is slow and very spammy so we | |
| # don't include it by default even when you're requesting extended debug. | |
| # [@compile_ignored: debug] | |
| extended_debug_cpp = os.environ.get("TORCHDYNAMO_EXTENDED_DEBUG_CPP", "") != "" | |
| # [@compile_ignored: debug] Show a warning for every specialization | |
| print_specializations = False | |
| # wraps (un)equalities with 'Not' class after recording the correct expression | |
| # in the FX graph. This should incorrectly construct the divisible and replacement | |
| # lists, and incorrectly issue guards. | |
| inject_EVALUATE_EXPR_flip_equality_TESTING_ONLY = False | |
| # [@compile_ignored: debug] Validate that ShapeEnv's version key is updated correctly | |
| validate_shape_env_version_key = False | |
| # If we produce more than this many guards on a symbol, force the symbol to | |
| # get specialized and bail out if this many guards mention this particular | |
| # symbol. This may be slightly more aggressive than the true number of guards | |
| # issued (as we test if we've hit the limit on-the-fly, whereas we may | |
| # do further simplifications at final guard issuance time that make guards | |
| # irrelevant.) | |
| symbol_guard_limit_before_specialize: Optional[int] = None | |
| from torch.utils._config_module import install_config_module | |
| install_config_module(sys.modules[__name__]) | |