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import inspect
import torch
from annotator.oneformer.detectron2.utils.env import TORCH_VERSION
try:
from torch.fx._symbolic_trace import is_fx_tracing as is_fx_tracing_current
tracing_current_exists = True
except ImportError:
tracing_current_exists = False
try:
from torch.fx._symbolic_trace import _orig_module_call
tracing_legacy_exists = True
except ImportError:
tracing_legacy_exists = False
@torch.jit.ignore
def is_fx_tracing_legacy() -> bool:
"""
Returns a bool indicating whether torch.fx is currently symbolically tracing a module.
Can be useful for gating module logic that is incompatible with symbolic tracing.
"""
return torch.nn.Module.__call__ is not _orig_module_call
@torch.jit.ignore
def is_fx_tracing() -> bool:
"""Returns whether execution is currently in
Torch FX tracing mode"""
if TORCH_VERSION >= (1, 10) and tracing_current_exists:
return is_fx_tracing_current()
elif tracing_legacy_exists:
return is_fx_tracing_legacy()
else:
# Can't find either current or legacy tracing indication code.
# Enabling this assert_fx_safe() call regardless of tracing status.
return False
@torch.jit.ignore
def assert_fx_safe(condition: bool, message: str) -> torch.Tensor:
"""An FX-tracing safe version of assert.
Avoids erroneous type assertion triggering when types are masked inside
an fx.proxy.Proxy object during tracing.
Args: condition - either a boolean expression or a string representing
the condition to test. If this assert triggers an exception when tracing
due to dynamic control flow, try encasing the expression in quotation
marks and supplying it as a string."""
# Must return a concrete tensor for compatibility with PyTorch <=1.8.
# If <=1.8 compatibility is not needed, return type can be converted to None
if not is_fx_tracing():
try:
if isinstance(condition, str):
caller_frame = inspect.currentframe().f_back
torch._assert(
eval(condition, caller_frame.f_globals, caller_frame.f_locals), message
)
return torch.ones(1)
else:
torch._assert(condition, message)
return torch.ones(1)
except torch.fx.proxy.TraceError as e:
print(
"Found a non-FX compatible assertion. Skipping the check. Failure is shown below"
+ str(e)
)
return torch.zeros(1)
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