NXP backend: Add conversion and quantization support for dim_order_ops._clone_dim_order.default #14535
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14535
Note: Links to docs will display an error until the docs builds have been completed. ❌ 1 New FailureAs of commit 5647c3e with merge base 0b748bf ( NEW FAILURE - The following job has failed:
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@pytorchbot label "release notes: nxp" |
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MartinPavella
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backends/nxp/tests/executors.py
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| def graph_contains_any_of_ops(graph: Graph, ops: list) -> bool: | ||
| return any(node.target in ops for node in graph.nodes) | ||
| return graph_contains_any(graph, condition=lambda n: n in ops) |
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Shouldn't this be:
return graph_contains_any(graph, condition=lambda n: hasattr(n, "target") and n.target in ops)?
backends/nxp/tests/executors.py
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| def graph_contains_any(graph: Graph, condition: Callable[[Node], bool]) -> bool: | ||
| return any(condition(node.target) for node in graph.nodes) |
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This should be:
return any(condition(node) for node in graph.nodes)or if you prefer:
return any(map(condition, graph.nodes))| ] | ||
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| quantized_program = to_quantized_edge_program(model, input_shape).exported_program() | ||
| def target_can_be_clone(node): |
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| edge_program = to_edge_program(model, input_shape).exported_program() | ||
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| has_clone = graph_contains_any( |
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Nit:
You can use the graph_contains_any_of_ops() here (once it's fixed).
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Please take a look at the failing Neutron tests. |
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Both fails seems unrelated to this PR while one of them was already failing in our previous PRs. |
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backends/nxp/tests/ir/converter/node_converter/test_clone_converter.py
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That is done. ✅ |
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Summary
dim_order_ops._clone_dim_order.defaultoperator and fixes problems with some variations ofnn.Dropout.Test plan
All changes should be covered by unit tests.
cc @robert-kalmar @JakeStevens @digantdesai