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# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
"""
Global flags for aot autograd
"""
import os
import sys
from typing import TYPE_CHECKING
# Converts torch rng ops to their functional philox rng equivalents. Note that
# we functionalize only CUDA rng ops today.
functionalize_rng_ops = False
# can be useful for debugging if we are incorrectly creating meta fake tensors
fake_tensor_allow_meta = os.environ.get("FAKE_ALLOW_META", True)
# Enables optional asserts in hotpath code to check for errors. If
# you are seeing weird accuracy problems, try turning this on.
# This is currently off by default as it will harm tracing time,
# but it is on by default for aot_eager.
debug_assert = False
debug_partitioner = os.environ.get("AOT_PARTITIONER_DEBUG", False)
static_weight_shapes = True
# Applies CSE to the graph before partitioning
cse = True
# Restricts the amount of computation AOTAutograd can do.
max_dist_from_bw = 3
# Enable aggressive_recomputation in the min-cut algorithm in partitioners to reduce
# memory usage with some penalty of performance. It allows more ops to be considered
# as recomputable except random ops and compute-intensive ops.
aggressive_recomputation = False
if TYPE_CHECKING:
from torch.utils._config_typing import * # noqa: F401, F403
from torch.utils._config_module import install_config_module
# adds patch, save_config, invalid config checks, etc
install_config_module(sys.modules[__name__])
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