commit to add validator in nonzero for thor runs (currently fallback to torch) and make ATenAnyDimNegIndexConvertsCorrectly input deterministic on ORIN

Author: apbose

py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py

@@ -24,6 +24,7 @@
     get_positive_dim,
     is_only_operator_on_placeholder,
 )
+from torch_tensorrt.dynamo.utils import is_thor
 
 _LOGGER: logging.Logger = logging.getLogger(__name__)
 
@@ -3601,10 +3602,18 @@ def aten_ops_full(
     )
 
 
+def nonzero_validator(
+    node: Node, settings: Optional[CompilationSettings] = None
+) -> bool:
+    return not is_thor()
+
+
 # currently nonzero is not supported for tensorrt_rtx
 # TODO: lan to add the nonzero support once tensorrt_rtx team has added the support
+# TODO: apbose to remove the capability validator once thor bug resolve in NGC
 @dynamo_tensorrt_converter(
     torch.ops.aten.nonzero.default,
+    capability_validator=nonzero_validator,
     supports_dynamic_shapes=True,
     requires_output_allocator=True,
 )

tests/core/conversion/converters/test_reduce.cpp

@@ -345,7 +345,14 @@ TEST(Converters, ATenAnyDimNegIndexConvertsCorrectly) {
       %3 : bool = prim::Constant[value=1]()
       %5 : Tensor = aten::any(%0, %1, %3)
       return (%5))IR";
-  auto in = at::randint(-2, 2, {2, 32}, at::kCUDA);
+  std::vector<int> data(64, 0);
+  for (int i = 0; i < 64; ++i) {
+    if (i % 7 == 0)
+      data[i] = 1; // some positives
+    if (i % 13 == 0)
+      data[i] = -1; // some negatives
+  }
+  auto in = at::tensor(data, at::TensorOptions().dtype(at::kInt).device(at::kCUDA)).reshape({2, 32}); // shape [2, 32]
   test_body(graph, in);
 }