Change onnx importer to use dynamic upsampling3d #3
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Add null checks to broadcast_to rel functions fail more isolated broadcast_to test
mbrookhart
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mbrookhart
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* Change onnx importer to use dynamic upsampling3d (#3) fix pylint * Refactor ONNX frontend to be dynamic Make OneHot dynamic Support BatchMatMul with dynamically shaped inputs fix dynamic broadcast Add null checks to broadcast_to rel functions fail more isolated broadcast_to test use StructuralEqual instead of pointer comparisions in dynamic_to_static pass add an optional weight freeze argument to onnx importer convert onnx resize to dynamic op add dynamic expand to onnx importer add a shape_func for power fix BERTSquad, lint handle onnx graph initializer parameters more intelligently * Dynamic ONNX importer: Upsampling and Pad (#2) fix lint fix Call reference fix a type issue with expand fix a bad test refactor respond to review comments, fix batch matmul tests * black format * fix batch matmul test * add dynamic strided slice to the onnx importer * fix clip importer * fix qnn tutorial * fix bad merge, respond to review comments * add a simple dynamic model test * Add dynamic-shaped autopadding to convolution and pooling ops * fix dynamic issues in a few ops * fix pylint * disable tests onnxrt doesn't support * fix pytorch test * respond to review comments * add documentation about partially supporting dynamic shapes Co-authored-by: Lily Orth-Smith <[email protected]>
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…-out (apache#8010) * [UnitTests] Explicitly list tests that were enabled by TVM_TEST_TARGETS but were skipped Previously, these were removed by a filter in tvm.testing._get_targets(), and weren't listed at all. With this change, they are instead removed by pytest.skipif, and show up as explicitly skipped tests in pytest's summary when using tvm.testing.parametrize_targets. * [UnitTests] Automatic parametrize_targets for tests that use (target,dev) Should make it easier to convert tests from using tvm.testing.enabled_targets to use pytest's parametrized tests instead. * [UnitTests] Added ability to explicitly exclude a target from a particular test Uses tvm_exclude_targets variable, which can be set (1) in the conftest.py to apply to a test directory, (2) in a test script to apply to that module, or (3) on an individual test function to apply to it. The @tvm.testing.exclude_targets decorator is provided for readability in case #3. * [UnitTests] Refactored test_topi_relu.py to use pytest.mark.parametrize * [UnitTests] Added tvm_known_failing_targets option for the unittests. Intended to mark tests that fail for a particular target, and are intended to be fixed in the future. Typically, these would result either from implementing a new test, or from an in-progress implementation of a new target. * [UnitTests] Known failing targets now marked with xfail instead of skipif * [UnitTests] Removed tvm_excluded_targets and tvm_known_failing_targets These were implemented to exclude or mark as failing an entire file or directory of tests. In https://discuss.tvm.apache.org/t/rfc-parametrized-unit-tests/9946/4, it was pointed out that the global variables would be vulnerable to typos in the names, resulting in the option being silently ignored. The decorators `@tvm.testing.exclude_targets` and `@tvm.testing.known_failing_targets` do not have this failure mode, and are the preferred version. * [UnitTests] Added helper functions to tvm.testing. - tvm.testing.parameter() defines a parameter that can be passed to tests. Tests that accept more than one parameter are run for all combinations of parameter values. - tvm.testing.parameters() defines multiple sets of parameter values. Tests that accept more than one parameter are run once for each set of parameter values. - tvm.testing.fixture() is a decorator that defines setup code. The `cache=True` argument can be passed to avoid repeating expensive setup across multiple tests. * [UnitTests] Bugfix for auto parametrizing of "target" Previously, if the @parametrize_targets were present, but had other @pytest.mark.parametrize after it, "target" would get parametrized a second time. Now, it checks more than just the closest "parametrize" marker. * [UnitTests] Renamed "cache" argument of tvm.testing.fixture to "cache_return_value" * [UnitTests] Minor updates to parametrized test implementation. As recommended by @tkonolige: - Avoid infinite loop if LLVM target isn't enabled - Update documentation for preferred use cases of tvm.testing.parametrize_targets, and recommended alternatives. * [UnitTests] Minor updates to parametrized test implementation - Documentation, removed previous example usage of tvm.testing.parametrize_targets * [UnitTests] Changed accidental use of pytest fixtures to a NameError. - Previously, a fixture function defined in a module was accessible through the global scope, and the function definition is accessible if a test function uses that name but fails to declare the fixture as a parameter. Now, it will result in a NameError instead. * [UnitTests] More careful removal of fixture functions from module global scope. - Initial implementation only checked hasattr(obj, "_pytestfixturefunction") before removing obj, which gave false positives for objects that implement __getattr__, such as caffe.layers. Now, also check that the value contained is a FixtureFunctionMarker. * [UnitTests] Copy cached values when using tvm.testing.fixture(cache_return_value=True) To avoid unit tests being able to influence each other through a shared cache, all cached fixtures are passed through copy.deepcopy prior to use. * [UnitTests] Added meta-tests for tvm.testing functionality Co-authored-by: Eric Lunderberg <[email protected]>
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