allowlist_for_publicAPI.json

{
  "being_migrated": {
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    "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"
  },
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  "torch.fx.experimental.unification.more": [
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    "optimize_for_inference",
    "optimized_execution",
    "run_frozen_optimizations",
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    "save_jit_module_to_flatbuffer",
    "script",
    "script_method",
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    "trace_module",
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    "ComplexType",
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    "is_tensor",
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    "make_source_context",
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    "parse_def",
    "should_drop",
    "monkeytype_trace"
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    "ldl_factor_ex",
    "ldl_solve",
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    "lu",
    "lu_factor",
    "lu_factor_ex",
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    "matmul",
    "matrix_exp",
    "matrix_norm",
    "matrix_power",
    "matrix_rank",
    "multi_dot",
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    "pinv",
    "qr",
    "slogdet",
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    "solve_triangular",
    "svd",
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    "tensorinv",
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    "vander",
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    "vector_norm"
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    "softmax",
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    "std",
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    "Manager",
    "Pipe",
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    "Process",
    "ProcessContext",
    "ProcessError",
    "ProcessExitedException",
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    "check_serializing_named_tensor",
    "register_after_fork"
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    "TensorProtoDataType",
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    "get_default_nowrap_functions",
    "has_torch_function"
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    "ProfilerActivity",
    "kineto_available",
    "record_function"
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    "DeQuantStub",
    "FakeQuantize",
    "FakeQuantizeBase",
    "FixedQParamsFakeQuantize",
    "FusedMovingAvgObsFakeQuantize",
    "HistogramObserver",
    "MinMaxObserver",
    "MovingAverageMinMaxObserver",
    "MovingAveragePerChannelMinMaxObserver",
    "NoopObserver",
    "ObserverBase",
    "PerChannelMinMaxObserver",
    "PlaceholderObserver",
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    "QConfigAny",
    "QConfigDynamic",
    "QuantStub",
    "QuantType",
    "QuantWrapper",
    "RecordingObserver",
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    "add_quant_dequant",
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    "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": [
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    "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",
    "qconfig_equals"
  ],
  "torch.quantization.quant_type": [
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    "_get_quant_type_to_str"
  ],
  "torch.quantization.quantization_mappings": [
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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",
    "get_default_static_quant_module_mappings",
    "get_dynamic_quant_module_class",
    "get_quantized_operator",
    "get_static_quant_module_class",
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    "prepare",
    "prepare_qat",
    "propagate_qconfig_",
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    "quantize_dynamic",
    "quantize_qat",
    "swap_module"
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    "convert_jit",
    "fuse_conv_bn_jit",
    "prepare_dynamic_jit",
    "prepare_jit",
    "quantize_dynamic_jit",
    "quantize_jit",
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    "script_qconfig_dict"
  ],
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    "QuantStub",
    "QuantWrapper"
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  ],
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    "Storage",
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    "closing",
    "contextmanager",
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    "get_default_mmap_options",
    "set_default_mmap_options"
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    "HalfTensor",
    "IntTensor",
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    "addmm",
    "log_softmax",
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    "softmax"
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    "bessel_y1",
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    "chebyshev_polynomial_u",
    "chebyshev_polynomial_v",
    "chebyshev_polynomial_w",
    "digamma",
    "entr",
    "erf",
    "erfc",
    "erfcx",
    "erfinv",
    "exp2",
    "expit",
    "expm1",
    "gammainc",
    "gammaincc",
    "gammaln",
    "hermite_polynomial_h",
    "hermite_polynomial_he",
    "i0",
    "i0e",
    "i1",
    "i1e",
    "laguerre_polynomial_l",
    "legendre_polynomial_p",
    "log1p",
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    "logsumexp",
    "modified_bessel_i0",
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    "modified_bessel_k0",
    "modified_bessel_k1",
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    "ndtri",
    "polygamma",
    "psi",
    "round",
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    "scaled_modified_bessel_k1",
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    "shifted_chebyshev_polynomial_v",
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    "xlog1py",
    "xlogy",
    "zeta"
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    "lru_cache"
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    "floating_types_and",
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    "Tuple",
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    "DisableTorchFunctionSubclass",
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    "HalfTensor",
    "QInt32Storage",
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    "_foreach_abs_",
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    "_foreach_acos_",
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    "_foreach_addcdiv_",
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    "_foreach_exp_",
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    "_foreach_expm1_",
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    "_foreach_floor_",
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    "_foreach_frac_",
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    "_foreach_lgamma_",
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    "_foreach_log10_",
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    "_foreach_log1p_",
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    "_foreach_log2_",
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    "_is_functional_tensor",
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    "_make_per_channel_quantized_tensor",
    "_make_per_tensor_quantized_tensor",
    "_masked_scale",
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    "_mkldnn_reshape",
    "_mkldnn_transpose",
    "_mkldnn_transpose_",
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    "_nested_from_padded",
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    "_reshape_alias_copy",
    "_reshape_from_tensor",
    "_rowwise_prune",
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    "_saturate_weight_to_fp16",
    "_shape_as_tensor",
    "_sobol_engine_draw",
    "_sobol_engine_ff_",
    "_sobol_engine_initialize_state_",
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    "_sparse_coo_tensor_unsafe",
    "_sparse_csr_prod",
    "_sparse_csr_sum",
    "_sparse_csr_tensor_unsafe",
    "_sparse_log_softmax_backward_data",
    "_sparse_softmax_backward_data",
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    "List",
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    "getattr_from_fqn"
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    "get_node_input_qparams",
    "get_node_type_to_io_type_map",
    "get_normalized_nth_input",
    "get_number_of_non_param_args",
    "get_target_type_str",
    "getattr_from_fqn",
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    "List",
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    "Set",
    "Tuple",
    "get_native_backend_config"
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    "NSResultsType",
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    "QConfigAny",
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    "Dict",
    "FakeQuantizeBase",
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    "List",
    "NSFusionElType",
    "NSFusionType",
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    "ObserverBase",
    "Set",
    "Tuple",
    "Union",
    "get_native_backend_config",
    "getattr_from_fqn"
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    "Set",
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    "getattr_from_fqn"
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    "NSSingleResultType",
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    "get_target_type_str",
    "getattr_from_fqn",
    "return_first_non_observer_node"
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    "BackendConfig",
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    "QConfig",
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    "Tuple",
    "convert_to_reference_fx",
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    "prepare_fx"
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    "EdgeOrNode",
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    "ObserverOrFakeQuantize",
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    "Union"
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    "fold_bn_weights_into_conv_node",
    "replace_pattern_with_filters"
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    "FuseCustomConfig",
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    "PrepareCustomConfig",
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    "QuantizationTracer",
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    "convert",
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    "prepare"
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    "Node",
    "QuantizationAnnotation"
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    "QuantizationConfig",
    "propagate_annotation"
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    "RawTextHelpFormatter",
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    "expanduser",
    "start_processes"
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    "RendezvousBackend",
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    "b64decode",
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    "RendezvousClosedError",
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    "cas_delay",
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    "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"
  ]
}