Fix import exceptions in tracing.py for older (<1.12) versions of pyt…

…orch

Summary:
X-link: facebookresearch/d2go#362

Pull Request resolved: #4491

Recently landed D35518556 (36a65a0) / Github: 36a65a0 throws an exception with older versions of PyTorch, due to a missing library for import. This has been reported by multiple members of the PyTorch community at 36a65a0

This change uses `try/except` to check for libraries and set flags on presence/absence to later guard code that would use them.

Reviewed By: wat3rBro

Differential Revision: D38879134

fbshipit-source-id: 72f5a7a8d350eb82be87567f006368bf207f5a74

detectron2/modeling/poolers.py

@@ -7,7 +7,7 @@
 
 from detectron2.layers import ROIAlign, ROIAlignRotated, cat, nonzero_tuple, shapes_to_tensor
 from detectron2.structures import Boxes
-from detectron2.utils.tracing import assert_fx_safe
+from detectron2.utils.tracing import assert_fx_safe, is_fx_tracing
 
 """
 To export ROIPooler to torchscript, in this file, variables that should be annotated with
@@ -220,9 +220,11 @@ def forward(self, x: List[torch.Tensor], box_lists: List[Boxes]):
         """
         num_level_assignments = len(self.level_poolers)
 
-        assert_fx_safe(
-            isinstance(x, list) and isinstance(box_lists, list), "Arguments to pooler must be lists"
-        )
+        if not is_fx_tracing():
+            torch._assert(
+                isinstance(x, list) and isinstance(box_lists, list),
+                "Arguments to pooler must be lists",
+            )
         assert_fx_safe(
             len(x) == num_level_assignments,
             "unequal value, num_level_assignments={}, but x is list of {} Tensors".format(

detectron2/utils/tracing.py

@@ -1,11 +1,22 @@
 import inspect
-from typing import Union
 import torch
-from torch.fx._symbolic_trace import _orig_module_call
-from torch.fx._symbolic_trace import is_fx_tracing as is_fx_tracing_current
 
 from 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:
@@ -20,32 +31,41 @@ def is_fx_tracing_legacy() -> bool:
 def is_fx_tracing() -> bool:
     """Returns whether execution is currently in
     Torch FX tracing mode"""
-    if TORCH_VERSION >= (1, 10):
+    if TORCH_VERSION >= (1, 10) and tracing_current_exists:
         return is_fx_tracing_current()
-    else:
+    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: Union[bool, str], message: str):
+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)