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1d6bd15790
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/52910 **Summary** PR #52158 tried to move all JIT bindings from `torch._C` to a new submodule `torch._C._jit`, but that...did not go well. This pull request adds the new `torch._C._jit` submodule, but does not migrate the existing bindings. Instead, it adds a unit test that fails if any new bindings are added to `torch._C`. A comment in the test instructs developers to add their new binding to the allowlist if it really should be in `torch._C`, or to add it to the appropriate submodule (e.g `torch._C._jit`, for example). The idea is to prevent the issue described in #51691 from getting *worse* if it cannot be fixed. **Test Plan** Continuous integration. **Fixes** This commit fixes #51691. Test Plan: Imported from OSS Reviewed By: albanD Differential Revision: D26698373 Pulled By: SplitInfinity fbshipit-source-id: ec9f5426051227a513d4fd09512b624420e0100b
196 lines
6.0 KiB
Python
196 lines
6.0 KiB
Python
from torch.testing._internal.common_utils import run_tests
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import torch
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import unittest
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class TestPublicBindings(unittest.TestCase):
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def test_no_new_bindings(self):
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"""
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This test aims to stop the introduction of new JIT bindings into torch._C
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whose names do not start with _. Such bindings are made available as
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torch.XXX, which may not be desirable.
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If your change causes this test to fail, add your new binding to a relevant
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submodule of torch._C, such as torch._C._jit (or other relevant submodule of
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torch._C). If your binding really needs to be available as torch.XXX, add it
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to torch._C and add it to the allowlist below.
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If you have removed a binding, remove it from the allowlist as well.
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"""
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# This allowlist contains every binding in torch._C that is copied into torch at
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# the time of writing. It was generated with
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#
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# {elem for elem in dir(torch._C) if not elem.startswith("_")}
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#
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torch_C_allowlist = {
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"AVG",
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"AggregationType",
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"AnyType",
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"Argument",
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"ArgumentSpec",
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"BFloat16StorageBase",
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"BenchmarkConfig",
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"BenchmarkExecutionStats",
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"Block",
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"BoolStorageBase",
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"BoolType",
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"BufferDict",
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"ByteStorageBase",
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"CONV_BN_FUSION",
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"CallStack",
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"Capsule",
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"CharStorageBase",
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"ClassType",
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"Code",
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"CompilationUnit",
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"CompleteArgumentSpec",
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"ComplexDoubleStorageBase",
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"ComplexFloatStorageBase",
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"ComplexType",
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"ConcreteModuleType",
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"ConcreteModuleTypeBuilder",
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"CudaBFloat16StorageBase",
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"CudaBFloat16TensorBase",
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"CudaBoolStorageBase",
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"CudaBoolTensorBase",
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"CudaByteStorageBase",
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"CudaByteTensorBase",
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"CudaCharStorageBase",
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"CudaCharTensorBase",
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"CudaComplexDoubleStorageBase",
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"CudaComplexDoubleTensorBase",
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"CudaComplexFloatStorageBase",
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"CudaComplexFloatTensorBase",
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"CudaDoubleStorageBase",
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"CudaDoubleTensorBase",
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"CudaFloatStorageBase",
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"CudaFloatTensorBase",
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"CudaHalfStorageBase",
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"CudaHalfTensorBase",
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"CudaIntStorageBase",
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"CudaIntTensorBase",
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"CudaLongStorageBase",
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"CudaLongTensorBase",
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"CudaShortStorageBase",
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"CudaShortTensorBase",
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"DeepCopyMemoTable",
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"DeviceObjType",
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"DictType",
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"DisableTorchFunction",
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"DoubleStorageBase",
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"EnumType",
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"ErrorReport",
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"ExecutionPlan",
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"FUSE_ADD_RELU",
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"FatalError",
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"FileCheck",
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"FloatStorageBase",
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"FloatType",
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"FunctionSchema",
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"Future",
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"FutureType",
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"Generator",
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"Gradient",
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"Graph",
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"GraphExecutorState",
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"HOIST_CONV_PACKED_PARAMS",
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"HalfStorageBase",
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"INSERT_FOLD_PREPACK_OPS",
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"IODescriptor",
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"InferredType",
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"IntStorageBase",
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"IntType",
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"InterfaceType",
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"JITException",
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"ListType",
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"LiteScriptModule",
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"LockingLogger",
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"LoggerBase",
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"LongStorageBase",
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"MobileOptimizerType",
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"ModuleDict",
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"Node",
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"NoneType",
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"NoopLogger",
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"NumberType",
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"OptionalType",
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"ParameterDict",
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"PyObjectType",
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"PyTorchFileReader",
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"PyTorchFileWriter",
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"QInt32StorageBase",
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"QInt8StorageBase",
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"QUInt4x2StorageBase",
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"QUInt8StorageBase",
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"REMOVE_DROPOUT",
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"RRefType",
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"SUM",
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"ScriptClass",
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"ScriptClassFunction",
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"ScriptFunction",
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"ScriptMethod",
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"ScriptModule",
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"ScriptObject",
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"ShortStorageBase",
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"Size",
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"StaticRuntime",
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"Stream",
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"StreamObjType",
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"StringType",
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"TensorType",
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"ThroughputBenchmark",
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"TracingState",
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"TupleType",
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"Type",
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"Use",
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"Value",
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"autocast_decrement_nesting",
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"autocast_increment_nesting",
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"clear_autocast_cache",
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"cpp",
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"default_generator",
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"device",
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"dtype",
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"finfo",
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"fork",
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"get_default_dtype",
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"get_num_interop_threads",
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"get_num_threads",
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"has_cuda",
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"has_cudnn",
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"has_lapack",
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"has_mkl",
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"has_mkldnn",
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"has_mlc",
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"has_openmp",
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"iinfo",
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"import_ir_module",
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"import_ir_module_from_buffer",
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"init_num_threads",
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"is_anomaly_enabled",
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"is_autocast_enabled",
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"is_grad_enabled",
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"layout",
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"memory_format",
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"merge_type_from_type_comment",
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"parse_ir",
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"parse_schema",
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"parse_type_comment",
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"qscheme",
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"set_anomaly_enabled",
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"set_autocast_enabled",
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"set_flush_denormal",
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"set_num_interop_threads",
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"set_num_threads",
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"unify_type_list",
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"wait",
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}
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torch_C_bindings = {elem for elem in dir(torch._C) if not elem.startswith("_")}
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# Check that both sets above have the same elements as each other.
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self.assertSetEqual(torch_C_bindings.symmetric_difference(torch_C_bindings), set())
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if __name__ == '__main__':
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run_tests()
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