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dryrun stats observable #4519
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dryrun stats observable #4519
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,48 @@ | ||
| # type: ignore | ||
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| import unittest | ||
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||
| import torch | ||
| import torch_tensorrt | ||
| from torch.testing._internal.common_utils import TestCase, run_tests | ||
| from torch_tensorrt.dynamo._DryRunTracker import DryRunTracker, dryrun_stats_display | ||
| from torch_tensorrt.dynamo.observer import ObserveContext | ||
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| @unittest.skipIf(not torch.cuda.is_available(), "CUDA required") | ||
| class TestDryRunStatsObservable(TestCase): | ||
| def test_observer_captures_tracker(self): | ||
| class Add(torch.nn.Module): | ||
| def forward(self, x): | ||
| return x + x | ||
|
|
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| model = Add().cuda().eval() | ||
| x = torch.randn(2, 3, device="cuda") | ||
| trackers = [] | ||
|
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| def capture(ctx: ObserveContext) -> None: | ||
| trackers.append(ctx.args[0]) | ||
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| with dryrun_stats_display.observers.pre.add(capture): | ||
| torch_tensorrt.dynamo.compile( | ||
| model, | ||
| [x], | ||
| dryrun=True, | ||
| min_block_size=1, | ||
| enabled_precisions={torch.float32}, | ||
| ) | ||
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| self.assertEqual(len(trackers), 1) | ||
| tracker = trackers[0] | ||
| self.assertIsInstance(tracker, DryRunTracker) | ||
| self.assertGreater(tracker.total_ops_in_graph, 0) | ||
| self.assertGreaterEqual(tracker.supported_ops_in_graph, 0) | ||
| self.assertLessEqual( | ||
| tracker.supported_ops_in_graph, tracker.total_ops_in_graph | ||
| ) | ||
| self.assertGreaterEqual(tracker.tensorrt_graph_count, 1) | ||
| self.assertEqual(len(tracker.per_subgraph_data), tracker.tensorrt_graph_count) | ||
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| if __name__ == "__main__": | ||
| run_tests() | ||
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dynamo.compile() needs an ExportedProgram, not an nn.Module. Export first with torch.export.export(model, (x,)), then pass that into compile.
Also drop enabled_precisions={torch.float32}, enabled_precisions is deprecated as of TRT 11. Dynamo uses dtypes on the model and input so this FP32 test needs no precision argument.