allowlist_for_publicAPI.json

{
  "being_migrated": {
    "torch.nn.intrinsic": "torch.ao.nn.intrinsic",
    "torch.nn.intrinsic.modules": "torch.ao.nn.intrinsic.modules",
    "torch.nn.intrinsic.modules.fused": "torch.ao.nn.intrinsic.modules.fused",
    "torch.nn.intrinsic.qat": "torch.ao.nn.intrinsic.qat",
    "torch.nn.intrinsic.qat.modules": "torch.ao.nn.intrinsic.qat.modules",
    "torch.nn.intrinsic.qat.modules.conv_fused": "torch.ao.nn.intrinsic.qat.modules.conv_fused",
    "torch.nn.intrinsic.qat.modules.linear_fused": "torch.ao.nn.intrinsic.qat.modules.linear_fused",
    "torch.nn.intrinsic.qat.modules.linear_relu": "torch.ao.nn.intrinsic.qat.modules.linear_relu",
    "torch.nn.intrinsic.quantized": "torch.ao.nn.intrinsic.quantized",
    "torch.nn.intrinsic.quantized.modules": "torch.ao.nn.intrinsic.quantized.modules",
    "torch.nn.intrinsic.quantized.modules.bn_relu": "torch.ao.nn.intrinsic.quantized.modules.bn_relu",
    "torch.nn.intrinsic.quantized.modules.conv_relu": "torch.ao.nn.intrinsic.quantized.modules.conv_relu",
    "torch.nn.intrinsic.quantized.modules.linear_relu": "torch.ao.nn.intrinsic.quantized.modules.linear_relu",
    "torch.nn.intrinsic.quantized.dynamic": "torch.ao.nn.intrinsic.quantized.dynamic",
    "torch.nn.intrinsic.quantized.dynamic.modules": "torch.ao.nn.intrinsic.quantized.dynamic.modules",
    "torch.nn.intrinsic.quantized.dynamic.modules.linear_relu": "torch.ao.nn.intrinsic.quantized.dynamic.modules.linear_relu",
    "torch.nn.qat": "torch.ao.nn.qat",
    "torch.nn.qat.dynamic": "torch.ao.nn.qat.dynamic",
    "torch.nn.qat.dynamic.modules": "torch.ao.nn.qat.dynamic.modules",
    "torch.nn.qat.dynamic.modules.linear": "torch.ao.nn.qat.dynamic.modules.linear",
    "torch.nn.qat.modules": "torch.ao.nn.qat.modules",
    "torch.nn.qat.modules.conv": "torch.ao.nn.qat.modules.conv",
    "torch.nn.qat.modules.embedding_ops": "torch.ao.nn.qat.modules.embedding_ops",
    "torch.nn.qat.modules.linear": "torch.ao.nn.qat.modules.linear",
    "torch.nn.quantized.functional": "torch.ao.nn.quantized.functional",
    "torch.nn.quantized": "torch.ao.nn.quantized",
    "torch.nn.quantized.modules": "torch.ao.nn.quantized.modules",
    "torch.nn.quantized.dynamic": "torch.ao.nn.quantized.dynamic",
    "torch.nn.quantized.dynamic.modules": "torch.ao.nn.quantized.dynamic.modules",
    "torch.nn.quantized.dynamic.modules.rnn": "torch.ao.nn.quantized.dynamic.modules.rnn",
    "torch.nn.quantizable": "torch.ao.nn.quantizable",
    "torch.nn.quantizable.modules": "torch.ao.nn.quantizable.modules",
    "torch.nn.quantizable.modules.activation": "torch.ao.nn.quantizable.modules.activation",
    "torch.nn.quantizable.modules.rnn": "torch.ao.nn.quantizable.modules.rnn",
    "torch.distributed.tensor.device_mesh": "torch.distributed.device_mesh"
  },
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  ],
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    "ScubaRdzvLogHandler"
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  "torch.distributed.elastic.rendezvous.dynamic_rendezvous": [
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    "List",
    "Template"
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  "torch.distributed.nn.jit.instantiator": [
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  "torch.distributed.rpc": [],
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    "rfftn"
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    "pca_lowrank",
    "svd_lowrank"
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    "ProxyableClassMeta",
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    "Tracer",
    "symbolic_trace",
    "wrap"
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  "torch.fx.experimental.migrate_gradual_types.z3_types": [
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    "unify",
    "walk"
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  "torch.fx.experimental.unification.more": [
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    "hashable",
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    "tqdm",
    "urlopen",
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    "RecursiveScriptModule",
    "ScriptModule",
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    "TopLevelTracedModule",
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    "TracerWarning",
    "TracingCheckError",
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    "fuser",
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    "is_scripting",
    "is_tracing",
    "jit_module_from_flatbuffer",
    "last_executed_optimized_graph",
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    "optimize_for_inference",
    "optimized_execution",
    "run_frozen_optimizations",
    "save",
    "save_jit_module_to_flatbuffer",
    "script",
    "script_method",
    "set_fusion_strategy",
    "set_module",
    "trace",
    "trace_module",
    "unused",
    "wait"
  ],
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    "AnyType",
    "ComplexType",
    "Dict",
    "DictType",
    "EvalEnv",
    "FloatType",
    "IntType",
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    "ListType",
    "StringType",
    "TensorType",
    "Tuple",
    "TupleType",
    "get_enum_value_type",
    "is_dict",
    "is_function_or_method",
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    "is_optional",
    "is_tensor",
    "is_tuple",
    "is_union",
    "is_vararg"
  ],
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    "SliceExpr",
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    "TupleLiteral",
    "UnaryOp",
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    "WithItem",
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    "get_qualified_name",
    "get_source_lines_and_file",
    "is_static_fn",
    "make_source_context",
    "namedtuple",
    "parse_def",
    "should_drop",
    "monkeytype_trace"
  ],
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    "cholesky",
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    "det",
    "diagonal",
    "eig",
    "eigh",
    "eigvals",
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    "householder_product",
    "inv",
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    "ldl_factor",
    "ldl_factor_ex",
    "ldl_solve",
    "lstsq",
    "lu",
    "lu_factor",
    "lu_factor_ex",
    "lu_solve",
    "matmul",
    "matrix_exp",
    "matrix_norm",
    "matrix_power",
    "matrix_rank",
    "multi_dot",
    "norm",
    "pinv",
    "qr",
    "slogdet",
    "solve",
    "solve_ex",
    "solve_triangular",
    "svd",
    "svdvals",
    "tensorinv",
    "tensorsolve",
    "vander",
    "vecdot",
    "vector_norm"
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    "cumprod",
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    "logaddexp",
    "logsumexp",
    "masked_tensor",
    "MaskedTensor",
    "mean",
    "median",
    "norm",
    "normalize",
    "prod",
    "softmax",
    "softmin",
    "std",
    "sum",
    "var"
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    "AuthenticationError",
    "Barrier",
    "BoundedSemaphore",
    "BufferTooShort",
    "Condition",
    "Event",
    "JoinableQueue",
    "Lock",
    "Manager",
    "Pipe",
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    "Process",
    "ProcessContext",
    "ProcessError",
    "ProcessExitedException",
    "ProcessRaisedException",
    "Queue",
    "RLock",
    "RawArray",
    "RawValue",
    "Semaphore",
    "SimpleQueue",
    "SpawnContext",
    "TimeoutError",
    "Value",
    "active_children",
    "allow_connection_pickling",
    "cpu_count",
    "current_process",
    "freeze_support",
    "get_all_start_methods",
    "get_context",
    "get_logger",
    "get_start_method",
    "init_reductions",
    "log_to_stderr",
    "set_executable",
    "set_forkserver_preload",
    "set_start_method",
    "spawn",
    "start_processes",
    "parent_process"
  ],
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    "check_serializing_named_tensor",
    "register_after_fork"
  ],
  "torch.multiprocessing.spawn": [
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  ],
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    "to_padded_tensor"
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    "Tensor",
    "Tuple",
    "TypeVar",
    "Union"
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    "adaptive_avg_pool1d",
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    "logsigmoid",
    "native_channel_shuffle",
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    "rrelu_",
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    "selu_",
    "softplus",
    "softshrink",
    "threshold_"
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    "PackedSequence_"
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    "Optional",
    "TensorProtoDataType",
    "TrainingMode"
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    "TorchFunctionMode",
    "TorchFunctionModeMeta",
    "enable_torch_function_mode",
    "get_default_nowrap_functions",
    "has_torch_function"
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    "ModuleType",
    "is_mangled"
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    "Optional",
    "Tuple"
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    "Iterable",
    "Union"
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  "torch.profiler": [
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    "ProfilerActivity",
    "kineto_available",
    "record_function"
  ],
  "torch.quantization": [
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    "DeQuantStub",
    "FakeQuantize",
    "FakeQuantizeBase",
    "FixedQParamsFakeQuantize",
    "FusedMovingAvgObsFakeQuantize",
    "HistogramObserver",
    "MinMaxObserver",
    "MovingAverageMinMaxObserver",
    "MovingAveragePerChannelMinMaxObserver",
    "NoopObserver",
    "ObserverBase",
    "PerChannelMinMaxObserver",
    "PlaceholderObserver",
    "QConfig",
    "QConfigAny",
    "QConfigDynamic",
    "QuantStub",
    "QuantType",
    "QuantWrapper",
    "RecordingObserver",
    "_add_module_to_qconfig_obs_ctr",
    "add_quant_dequant",
    "_assert_valid_qconfig",
    "convert",
    "convert_dynamic_jit",
    "convert_jit",
    "default_fixed_qparams_range_0to1_fake_quant",
    "default_affine_fixed_qparams_fake_quant",
    "default_debug_observer",
    "default_dynamic_quant_observer",
    "default_fake_quant",
    "default_float_qparams_observer",
    "default_fused_act_fake_quant",
    "default_fused_per_channel_wt_fake_quant",
    "default_fused_wt_fake_quant",
    "default_histogram_fake_quant",
    "default_histogram_observer",
    "default_observer",
    "default_per_channel_weight_fake_quant",
    "default_per_channel_weight_observer",
    "default_placeholder_observer",
    "default_fixed_qparams_range_neg1to1_fake_quant",
    "default_symmetric_fixed_qparams_fake_quant",
    "default_weight_fake_quant",
    "default_weight_observer",
    "disable_fake_quant",
    "disable_observer",
    "enable_fake_quant",
    "enable_observer",
    "fuse_conv_bn",
    "fuse_conv_bn_jit",
    "fuse_conv_bn_relu",
    "fuse_linear_bn",
    "fuse_modules",
    "get_default_compare_output_module_list",
    "get_default_dynamic_quant_module_mappings",
    "get_default_float_to_quantized_operator_mappings",
    "get_default_qat_module_mappings",
    "get_default_qat_qconfig",
    "get_default_qconfig",
    "get_default_qconfig_propagation_list",
    "get_default_static_quant_module_mappings",
    "get_dynamic_quant_module_class",
    "get_fuser_method",
    "get_observer_state_dict",
    "get_quantized_operator",
    "get_static_quant_module_class",
    "load_observer_state_dict",
    "no_observer_set",
    "prepare",
    "prepare_dynamic_jit",
    "prepare_jit",
    "prepare_qat",
    "propagate_qconfig_",
    "qconfig_equals",
    "_get_quant_type_to_str",
    "quantize",
    "quantize_dynamic",
    "quantize_dynamic_jit",
    "quantize_jit",
    "quantize_qat",
    "script_qconfig",
    "script_qconfig_dict",
    "swap_module"
  ],
  "torch.quantization.fake_quantize": [
    "FakeQuantize",
    "FakeQuantizeBase",
    "FixedQParamsFakeQuantize",
    "FusedMovingAvgObsFakeQuantize",
    "default_fixed_qparams_range_0to1_fake_quant",
    "default_affine_fixed_qparams_fake_quant",
    "default_fake_quant",
    "default_fused_act_fake_quant",
    "default_fused_per_channel_wt_fake_quant",
    "default_fused_wt_fake_quant",
    "default_histogram_fake_quant",
    "default_per_channel_weight_fake_quant",
    "default_fixed_qparams_range_neg1to1_fake_quant",
    "default_symmetric_fixed_qparams_fake_quant",
    "default_weight_fake_quant",
    "disable_fake_quant",
    "disable_observer",
    "enable_fake_quant",
    "enable_observer"
  ],
  "torch.quantization.fuse_modules": [
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    "fuse_conv_bn_relu",
    "fuse_known_modules",
    "fuse_modules",
    "get_fuser_method"
  ],
  "torch.quantization.fuser_method_mappings": [
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    "fuse_conv_bn_relu",
    "fuse_linear_bn",
    "get_fuser_method"
  ],
  "torch.quantization.observer": [
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    "HistogramObserver",
    "MinMaxObserver",
    "MovingAverageMinMaxObserver",
    "MovingAveragePerChannelMinMaxObserver",
    "NoopObserver",
    "ObserverBase",
    "PerChannelMinMaxObserver",
    "PlaceholderObserver",
    "RecordingObserver",
    "default_debug_observer",
    "default_dynamic_quant_observer",
    "default_float_qparams_observer",
    "default_histogram_observer",
    "default_observer",
    "default_per_channel_weight_observer",
    "default_placeholder_observer",
    "default_weight_observer",
    "get_observer_state_dict",
    "load_observer_state_dict"
  ],
  "torch.quantization.qconfig": [
    "QConfig",
    "QConfigAny",
    "QConfigDynamic",
    "_add_module_to_qconfig_obs_ctr",
    "_assert_valid_qconfig",
    "get_default_qat_qconfig",
    "get_default_qconfig",
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    "get_default_dynamic_quant_module_mappings",
    "get_default_float_to_quantized_operator_mappings",
    "get_default_qat_module_mappings",
    "get_default_qconfig_propagation_list",
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    "quantize_dynamic",
    "quantize_qat",
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    "prepare_jit",
    "quantize_dynamic_jit",
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    "QuantStub",
    "QuantWrapper"
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    "set_default_mmap_options"
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    "chebyshev_polynomial_v",
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    "erfcx",
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    "gammainc",
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    "i0e",
    "i1",
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    "_foreach_floor_",
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    "_sparse_csr_sum",
    "_sparse_csr_tensor_unsafe",
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    "get_normalized_nth_input",
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    "get_native_backend_config"
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    "NSFusionElType",
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    "get_native_backend_config",
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    "Set",
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    "getattr_from_fqn"
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    "convert_to_reference_fx",
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    "prepare_fx"
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    "QuantizationAnnotation"
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    "b64decode",
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    "RendezvousClosedError",
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  "torch.distributed.logging_handlers": [
    "C10D_CATEGORY",
    "Dict",
    "LogCategory",
    "Optional",
    "Sample",
    "ScubaData",
    "signpost",
    "SignpostType"
  ],
  "torch.utils.benchmark.examples.sparse.op_benchmark": [
    "BinaryOpSparseFuzzer",
    "Timer",
    "UnaryOpSparseFuzzer"
  ],
  "torch.version": [
    "get_file_path"
  ],
  "torch.ao.nn.intrinsic.modules": [
    "_FusedModule"
  ],
  "torch.distributed.benchmarks.benchmark_ddp_rpc": [
    "BackendType",
    "DDP",
    "DistributedOptimizer",
    "RRef",
    "TensorPipeRpcBackendOptions"
  ],
  "torch.distributed.pipelining": [
    "Pipe",
    "PipelineStage",
    "SplitPoint",
    "pipe_split",
    "pipeline"
  ],
  "torch.distributed.pipelining.microbatch": [
    "Any",
    "Dict",
    "List",
    "Optional",
    "Tuple",
    "tree_flatten",
    "tree_unflatten"
  ],
  "torch.export": [
    "Constraint",
    "ShapesCollection"
  ],
  "torch.export.dynamic_shapes": [
    "Constraint",
    "ShapesCollection"
  ],
  "torch.export.graph_signature": [
    "TokenArgument"
  ],
  "torch.fx.experimental.shape_inference.infer_shape": [
    "DimDynamic",
    "FakeTensorMode",
    "LocalSource",
    "ShapeEnv",
    "defaultdict",
    "infer_symbol_values",
    "make_fx"
  ],
  "torch.fx.experimental.shape_inference.infer_symbol_values": [
    "Any",
    "DefaultDict",
    "Dict",
    "List",
    "Tuple",
    "Union"
  ],
  "torch.fx.passes.runtime_assert": [
    "Any",
    "Dict",
    "GraphModule",
    "Optional",
    "Set",
    "ShapeEnv",
    "SymNode",
    "compatibility",
    "lazy_format_graph_code"
  ],
  "torch.library": [
    "opcheck",
    "register_autograd",
    "register_kernel"
  ],
  "torch.mtia": [
    "DeferredMtiaCallError",
    "StreamContext"
  ],
  "torch.onnx.symbolic_helper": [
    "Any",
    "Callable",
    "List",
    "Literal",
    "NoReturn",
    "Number",
    "Optional",
    "Sequence",
    "Set",
    "Tuple",
    "Union"
  ],
  "torch.onnx.symbolic_opset18": [
    "amax",
    "amin",
    "aminmax",
    "embedding_bag",
    "linalg_vector_norm",
    "max",
    "maximum",
    "min",
    "minimum"
  ],
  "torch.onnx.symbolic_opset20": [
    "_affine_grid_generator",
    "_grid_sampler",
    "convert_grid_sample_mode"
  ],
  "torch.utils.data.datapipes.dataframe.dataframe_wrapper": [
    "Any",
    "Optional"
  ],
  "torch.utils.hipify.hipify_python": [
    "TrieNode"
  ]
}