import functools import importlib import sys import types import torch from .allowed_functions import _disallowed_function_ids, is_user_defined_allowed from .utils import hashable from .variables import ( SkipFilesVariable, TorchCtxManagerClassVariable, TorchInGraphFunctionVariable, ) """ Map of torch objects to their tracing rules (Dynamo variables). * TorchVariable: The functions should be put into the FX graph or can be constant folded. E.g., - torch.add: should be put into the FX graph. - torch.is_floating_point: constant folded. * TorchCtxManagerClassVariable: The context manager classes are supported by Dynamo. E.g., torch.no_grad * SkipFilesVariable: The objects should be skipped from tracing. * UserFunctionVariable: The functions should be inlined. We explicitly list torch objects which should be wrapped as TorchCtxManagerClassVariable. The initial list comes from the heuristic in test/dynamo/test_trace_rules.py:generate_allow_list. For developers: If you add/remove a torch level API, it may trigger failures from test/dynamo/test_trace_rules.py:test_torch_name_rule_map. To fix the failures: If you are adding a new torch level API or Dynamo implementation: * Add the name with TorchCtxManagerClassVariable to this map if you are adding Dynamo implementation for that context manager. * Remove the object name from test/dynamo/test_trace_rules.ignored_torch_name_rule_set if it's there. If you are removing an existing torch level API: * Remove the entry represented the API from this map or test/dynamo/test_trace_rules.ignored_torch_name_rule_set depends on where it is. TODO: Add torch object names mapping to TorchVariable for in graph and constant fold functions. TODO: We would consolidate the skipfiles.check rules into trace_rules.lookup later. TODO: We would support explictly list objects treated as skip/inline after the skipfiles.check and trace_rules.lookup consolidation is done. Then the explicit listing of skip/inline objects have a higher priority, which can be used to override the skipfiles.check rules in some cases. """ manual_torch_name_rule_map = { "torch.profiler.profiler.profile": TorchCtxManagerClassVariable, "torch.autograd.profiler.profile": TorchCtxManagerClassVariable, "torch.autograd.profiler.record_function": TorchCtxManagerClassVariable, "torch.onnx.is_in_onnx_export": TorchInGraphFunctionVariable, "torch.onnx.operators.shape_as_tensor": TorchInGraphFunctionVariable, "torch.overrides.is_tensor_like": TorchInGraphFunctionVariable, "torch.jit.is_scripting": TorchInGraphFunctionVariable, "torch.jit.is_tracing": TorchInGraphFunctionVariable, "torch.jit.annotate": TorchInGraphFunctionVariable, "torch.distributed.is_available": TorchInGraphFunctionVariable, "torch.distributed.is_initialized": TorchInGraphFunctionVariable, "torch.distributed.get_rank": TorchInGraphFunctionVariable, "torch.distributed.get_world_size": TorchInGraphFunctionVariable, "torch.distributed._tensor.DTensor#from_local": TorchInGraphFunctionVariable, "torch.distributed.distributed_c10d._get_group_tag": TorchInGraphFunctionVariable, "torch.distributed.distributed_c10d.get_process_group_ranks": TorchInGraphFunctionVariable, "torch._utils.is_compiling": TorchInGraphFunctionVariable, "torch.overrides.get_default_nowrap_functions": TorchInGraphFunctionVariable, "torch.fx._symbolic_trace.is_fx_tracing": TorchInGraphFunctionVariable, "torch._dynamo.external_utils.is_compiling": TorchInGraphFunctionVariable, "torch.autograd.graph.disable_saved_tensors_hooks": TorchInGraphFunctionVariable, "torch.autograd._profiler_enabled": SkipFilesVariable, # We graph break on RNG state setters or getters like # `torch.get_rng_state` or `torch.set_rng_state`. These functions # are not aten operations and therefore they are completely ignored # by the AOT dispatcher. As a result, the AOT graph does not have # these setter or getter functions, producing an incorrect graph # when it comes to rng states. "torch.default_generator#get_state": SkipFilesVariable, "torch._C.Generator#get_state": SkipFilesVariable, "torch.get_rng_state": SkipFilesVariable, "torch.cuda.get_rng_state": SkipFilesVariable, "torch.default_generator#set_state": SkipFilesVariable, "torch._C.Generator#set_state": SkipFilesVariable, "torch.set_rng_state": SkipFilesVariable, "torch.cuda.set_rng_state": SkipFilesVariable, # https://github.com/pytorch/pytorch/issues/107187 "torch.manual_seed": SkipFilesVariable, # https://github.com/pytorch/pytorch/issues/93501 "torch.nn.utils.rnn.pack_padded_sequence": SkipFilesVariable, # https://github.com/pytorch/pytorch/issues/99569 "torch.nn.Parameter": SkipFilesVariable, "torch._nested_tensor_from_mask": SkipFilesVariable, "torch._nested_from_padded": SkipFilesVariable, } # Dynamo implemented context managers torch_ctx_manager_classes = { k: TorchCtxManagerClassVariable for k in [ "torch._C.DisableTorchFunctionSubclass", "torch.amp.autocast_mode.autocast", "torch.autograd.grad_mode.enable_grad", "torch.autograd.grad_mode.inference_mode", "torch.autograd.grad_mode.no_grad", "torch.autograd.grad_mode.set_grad_enabled", "torch.cpu.amp.autocast_mode.autocast", "torch.cuda.amp.autocast_mode.autocast", ] } # In graph functions (including constant folding) that are C bindings torch_c_binding_in_graph_functions = { k: TorchInGraphFunctionVariable for k in [ "math.acos", "math.acosh", "math.asin", "math.asinh", "math.atan", "math.atan2", "math.atanh", "math.ceil", "math.comb", "math.copysign", "math.cos", "math.cosh", "math.degrees", "math.dist", "math.erf", "math.erfc", "math.exp", "math.expm1", "math.fabs", "math.factorial", "math.floor", "math.fmod", "math.frexp", "math.fsum", "math.gamma", "math.gcd", "math.hypot", "math.isclose", "math.isfinite", "math.isinf", "math.isnan", "math.isqrt", "math.ldexp", "math.lgamma", "math.log", "math.log10", "math.log1p", "math.log2", "math.modf", "math.nextafter", "math.perm", "math.pow", "math.prod", "math.radians", "math.remainder", "math.sin", "math.sinh", "math.tan", "math.tanh", "math.trunc", "math.ulp", "torch._adaptive_avg_pool2d", "torch._adaptive_avg_pool3d", "torch._add_batch_dim", "torch._add_relu_", "torch._add_relu", "torch._addmm_activation", "torch._aminmax", "torch._amp_foreach_non_finite_check_and_unscale_", "torch._amp_update_scale_", "torch._assert_async", "torch._assert_tensor_metadata", "torch._batch_norm_impl_index", "torch._C._activate_cuda_trace", "torch._C._add_cached_tensor", "torch._C._add_docstr", "torch._C._are_functorch_transforms_active", "torch._C._autograd_init", "torch._C._awaitable_nowait", "torch._C._awaitable_wait", "torch._C._awaitable", "torch._C._backport_for_mobile_from_buffer_to_buffer", "torch._C._backport_for_mobile_from_buffer", "torch._C._backport_for_mobile_to_buffer", "torch._C._backport_for_mobile", "torch._C._broadcast_coalesced", "torch._C._broadcast_out", "torch._C._broadcast", "torch._C._c10d_init", "torch._C._calculate_package_version_based_on_upgraders", "torch._C._can_use_flash_attention", "torch._C._can_use_mem_efficient_attention", "torch._C._check_onnx_proto", "torch._C._check_sparse_tensor_invariants", "torch._C._collect_all", "torch._C._commit_update", "torch._C._compile_graph_to_code_table", "torch._C._construct_CUDA_Tensor_From_Storage_And_Metadata", "torch._C._construct_storage_from_data_pointer", "torch._C._conv_determine_backend_memory_format", "torch._C._cpu._is_cpu_support_vnni", "torch._C._crash_if_aten_asan", "torch._C._crash_if_csrc_asan", "torch._C._crash_if_csrc_ubsan", "torch._C._crash_if_debug_asserts_fail", "torch._C._crash_if_vptr_ubsan", "torch._C._create_function_from_graph", "torch._C._create_function_from_trace_with_dict", "torch._C._create_function_from_trace", "torch._C._create_graph_by_tracing", "torch._C._create_module_with_type", "torch._C._create_object_with_type", "torch._C._cuda_attach_out_of_memory_observer", "torch._C._cuda_beginAllocateCurrentStreamToPool", "torch._C._cuda_canDeviceAccessPeer", "torch._C._cuda_changeCurrentAllocator", "torch._C._cuda_checkPoolLiveAllocations", "torch._C._cuda_clearCublasWorkspaces", "torch._C._cuda_cudaCachingAllocator_raw_alloc", "torch._C._cuda_cudaCachingAllocator_raw_delete", "torch._C._cuda_cudaCachingAllocator_set_allocator_settings", "torch._C._cuda_cudaHostAllocator", "torch._C._cuda_customAllocator", "torch._C._cuda_emptyCache", "torch._C._cuda_endAllocateCurrentStreamToPool", "torch._C._cuda_exchangeDevice", "torch._C._cuda_get_conv_benchmark_empty_cache", "torch._C._cuda_get_cudnn_benchmark_limit", "torch._C._cuda_get_sync_debug_mode", "torch._C._cuda_getAllocator", "torch._C._cuda_getAllocatorBackend", "torch._C._cuda_getArchFlags", "torch._C._cuda_getCheckpointState", "torch._C._cuda_getCompiledVersion", "torch._C._cuda_getCurrentBlasHandle", "torch._C._cuda_getCurrentRawStream", "torch._C._cuda_getCurrentStream", "torch._C._cuda_getDefaultStream", "torch._C._cuda_getDevice", "torch._C._cuda_getDeviceCount", "torch._C._cuda_hasPrimaryContext", "torch._C._cuda_init", "torch._C._cuda_ipc_collect", "torch._C._cuda_isCurrentStreamCapturing", "torch._C._cuda_isHistoryEnabled", "torch._C._cuda_isInBadFork", "torch._C._cuda_jiterator_compile_and_launch_kernel", "torch._C._cuda_lock_mutex", "torch._C._cuda_maybeExchangeDevice", "torch._C._cuda_memorySnapshot", "torch._C._cuda_memoryStats", "torch._C._cuda_record_memory_history_legacy", "torch._C._cuda_record_memory_history", "torch._C._cuda_releasePool", "torch._C._cuda_resetAccumulatedMemoryStats", "torch._C._cuda_resetPeakMemoryStats", "torch._C._cuda_set_cudnn_benchmark_limit", "torch._C._cuda_set_sync_debug_mode", "torch._C._cuda_setCheckpointPoolState", "torch._C._cuda_setDevice", "torch._C._cuda_setMemoryFraction", "torch._C._cuda_setStream", "torch._C._cuda_sleep", "torch._C._cuda_synchronize", "torch._C._cuda_unlock_mutex", "torch._C._cudnn_set_conv_benchmark_empty_cache", "torch._C._cudnn.getCompileVersion", "torch._C._cudnn.getRuntimeVersion", "torch._C._cudnn.getVersionInt", "torch._C._current_autograd_node", "torch._C._current_graph_task_execution_order", "torch._C._current_graph_task_id", "torch._C._cxx_flags", "torch._C._debug_get_fusion_group_inlining", "torch._C._debug_only_are_vmap_fallback_warnings_enabled", "torch._C._debug_only_display_vmap_fallback_warnings", "torch._C._debug_set_autodiff_subgraph_inlining", "torch._C._debug_set_fusion_group_inlining", "torch._C._demangle", "torch._C._disabled_torch_dispatch_impl", "torch._C._disabled_torch_function_impl", "torch._C._dispatch_call_boxed", "torch._C._dispatch_check_all_invariants", "torch._C._dispatch_check_invariants", "torch._C._dispatch_dump_table", "torch._C._dispatch_dump", "torch._C._dispatch_find_dangling_impls", "torch._C._dispatch_find_schema_or_throw", "torch._C._dispatch_get_all_op_names", "torch._C._dispatch_get_backend_keyset_from_autograd", "torch._C._dispatch_get_registrations_for_dispatch_key", "torch._C._dispatch_has_backend_fallback", "torch._C._dispatch_has_computed_kernel_for_dispatch_key", "torch._C._dispatch_has_kernel_for_any_dispatch_key", "torch._C._dispatch_has_kernel_for_dispatch_key", "torch._C._dispatch_has_kernel", "torch._C._dispatch_is_alias_key", "torch._C._dispatch_is_included_in_alias", "torch._C._dispatch_is_main_interpreter", "torch._C._dispatch_isTensorSubclassLike", "torch._C._dispatch_key_for_device", "torch._C._dispatch_key_name", "torch._C._dispatch_key_parse", "torch._C._dispatch_key_set", "torch._C._dispatch_keys", "torch._C._dispatch_keyset_full_after", "torch._C._dispatch_keyset_full", "torch._C._dispatch_keyset_to_string", "torch._C._dispatch_library", "torch._C._dispatch_num_backends", "torch._C._dispatch_print_registrations_for_dispatch_key", "torch._C._dispatch_pystub", "torch._C._dispatch_set_report_error_callback", "torch._C._dispatch_tls_is_dispatch_key_excluded", "torch._C._dispatch_tls_is_dispatch_key_included", "torch._C._dispatch_tls_local_exclude_set", "torch._C._dispatch_tls_local_include_set", "torch._C._dispatch_tls_set_dispatch_key_excluded", "torch._C._dispatch_tls_set_dispatch_key_included", "torch._C._dist_autograd_init", "torch._C._dump_local_tls_set", "torch._C._dump_upgraders_map", "torch._C._enable_mobile_interface_call_export", "torch._C._enter_dual_level", "torch._C._error_if_any_worker_fails", "torch._C._exit_dual_level", "torch._C._export_operator_list", "torch._C._export_opnames", "torch._C._faulty_agent_init", "torch._C._fft.fft_fft", "torch._C._fft.fft_fft2", "torch._C._fft.fft_fftfreq", "torch._C._fft.fft_fftn", "torch._C._fft.fft_fftshift", "torch._C._fft.fft_hfft", "torch._C._fft.fft_hfft2", "torch._C._fft.fft_hfftn", "torch._C._fft.fft_ifft", "torch._C._fft.fft_ifft2", "torch._C._fft.fft_ifftn", "torch._C._fft.fft_ifftshift", "torch._C._fft.fft_ihfft", "torch._C._fft.fft_ihfft2", "torch._C._fft.fft_ihfftn", "torch._C._fft.fft_irfft", "torch._C._fft.fft_irfft2", "torch._C._fft.fft_irfftn", "torch._C._fft.fft_rfft", "torch._C._fft.fft_rfft2", "torch._C._fft.fft_rfftfreq", "torch._C._fft.fft_rfftn", "torch._C._free_And_Remove_DeleterFn", "torch._C._freeze_module", "torch._C._from_dlpack", "torch._C._functionality_to_backend_keys", "torch._C._functionalization_reapply_views_tls", "torch._C._fuse_to_static_module", "torch._C._gather_out", "torch._C._gather", "torch._C._generate_upgraders_graph", "torch._C._get_autograd_fallback_mode", "torch._C._get_backcompat_broadcast_warn", "torch._C._get_backcompat_keepdim_warn", "torch._C._get_caught_jit_exception_class_name", "torch._C._get_caught_jit_exception_original_msg", "torch._C._get_constant_bool_symnode", "torch._C._get_cpp_backtrace", "torch._C._get_cpu_capability", "torch._C._get_cublas_allow_bf16_reduced_precision_reduction", "torch._C._get_cublas_allow_fp16_reduced_precision_reduction", "torch._C._get_cublas_allow_tf32", "torch._C._get_cudnn_allow_tf32", "torch._C._get_cudnn_benchmark", "torch._C._get_cudnn_deterministic", "torch._C._get_cudnn_enabled", "torch._C._get_custom_class_python_wrapper", "torch._C._get_default_device", "torch._C._get_deterministic_algorithms_warn_only", "torch._C._get_deterministic_algorithms", "torch._C._get_deterministic_fill_uninitialized_memory", "torch._C._get_dispatch_mode", "torch._C._get_dispatch_stack_at", "torch._C._get_file_format", "torch._C._get_flash_sdp_enabled", "torch._C._get_float32_matmul_precision", "torch._C._get_function_stack_at", "torch._C._get_graph_executor_optimize", "torch._C._get_linalg_preferred_backend", "torch._C._get_math_sdp_enabled", "torch._C._get_max_operator_version", "torch._C._get_mem_efficient_sdp_enabled", "torch._C._get_mkldnn_enabled", "torch._C._get_mobile_model_contained_types_from_buffer", "torch._C._get_mobile_model_contained_types", "torch._C._get_model_bytecode_version_from_buffer", "torch._C._get_model_bytecode_version", "torch._C._get_model_extra_files_from_buffer", "torch._C._get_model_extra_files", "torch._C._get_model_ops_and_info_from_buffer", "torch._C._get_model_ops_and_info", "torch._C._get_module_info_from_flatbuffer", "torch._C._get_obj_in_tls", "torch._C._get_operation_overload", "torch._C._get_operator_version_map", "torch._C._get_privateuse1_backend_name", "torch._C._get_qengine", "torch._C._get_schema", "torch._C._get_singleton_int", "torch._C._get_tensor_metadata", "torch._C._get_tracing_state", "torch._C._get_upgrader_ranges", "torch._C._get_upgraders_entry_map", "torch._C._get_upgraders_map_size", "torch._C._get_value_trace", "torch._C._get_version_calculator_flag", "torch._C._get_warnAlways", "torch._C._graph_pool_handle", "torch._C._group_tensors_by_device_and_dtype", "torch._C._hack_do_not_use_clone_module_with_class", "torch._C._has_distributed", "torch._C._has_Standard_Deleter", "torch._C._has_storage", "torch._C._has_tensorexpr_cpp_tests", "torch._C._run_tensorexpr_cpp_tests", "torch._C._has_torch_function_unary", "torch._C._has_torch_function_variadic", "torch._C._has_torch_function", "torch._C._import_ir_module_from_package", "torch._C._increment_version", "torch._C._infer_size", "torch._C._init_names", "torch._C._initExtension", "torch._C._is_alias_of", "torch._C._is_any_autocast_enabled", "torch._C._is_cached_tensor", "torch._C._is_fwd_grad_enabled", "torch._C._is_key_in_tls", "torch._C._is_multithreading_enabled", "torch._C._is_torch_function_enabled", "torch._C._is_torch_function_mode_enabled", "torch._C._is_tracing", "torch._C._is_view_replay_enabled", "torch._C._is_xnnpack_enabled", "torch._C._itt.is_available", "torch._C._itt.mark", "torch._C._itt.rangePop", "torch._C._itt.rangePush", "torch._C._ivalue_debug_python_object", "torch._C._ivalue_tags_match", "torch._C._jit_assert_is_instance", "torch._C._jit_can_fuse_on_cpu_legacy", "torch._C._jit_can_fuse_on_cpu", "torch._C._jit_can_fuse_on_gpu", "torch._C._jit_cat_wo_conditionals", "torch._C._jit_check_alias_annotation", "torch._C._jit_clear_class_registry", "torch._C._jit_debug_fuser_num_cached_kernel_specs", "torch._C._jit_debug_module_iterators", "torch._C._jit_decay_packed_param_input_types", "torch._C._jit_decomposition_graph_for_node", "torch._C._jit_differentiate", "torch._C._jit_erase_non_input_shape_information", "torch._C._jit_flatten", "torch._C._jit_fuser_get_fused_kernel_code", "torch._C._jit_get_all_schemas", "torch._C._jit_get_custom_class_schemas", "torch._C._jit_get_emit_hooks", "torch._C._jit_get_inline_everything_mode", "torch._C._jit_get_logging_option", "torch._C._jit_get_num_profiled_runs", "torch._C._jit_get_operation", "torch._C._jit_get_schemas_for_operator", "torch._C._jit_get_te_cuda_pointwise_block_count", "torch._C._jit_get_te_cuda_pointwise_block_size", "torch._C._jit_get_te_cuda_pointwise_loop_levels", "torch._C._jit_get_te_generate_block_code", "torch._C._jit_get_te_must_use_llvm_cpu", "torch._C._jit_get_tracer_state_warn", "torch._C._jit_has_cpp_tests", "torch._C._jit_init", "torch._C._jit_interpret_graph", "torch._C._jit_is_onnx_log_enabled", "torch._C._jit_is_script_object", "torch._C._jit_llga_enabled", "torch._C._jit_nvfuser_can_be_enabled", "torch._C._jit_nvfuser_clear_comparison_callback", "torch._C._jit_nvfuser_enabled", "torch._C._jit_nvfuser_horizontal_mode", "torch._C._jit_nvfuser_set_comparison_callback", "torch._C._jit_nvfuser_single_node_mode", "torch._C._jit_object_is_non_holding", "torch._C._jit_onnx_convert_pattern_from_subblock", "torch._C._jit_onnx_create_full_scope_name", "torch._C._jit_onnx_list_model_parameters", "torch._C._jit_onnx_log", "torch._C._jit_opt_conditionals", "torch._C._jit_override_can_fuse_on_cpu_legacy", "torch._C._jit_override_can_fuse_on_cpu", "torch._C._jit_override_can_fuse_on_gpu", "torch._C._jit_pass_autocast", "torch._C._jit_pass_batch_mm", "torch._C._jit_pass_canonicalize_graph_fuser_ops", "torch._C._jit_pass_canonicalize", "torch._C._jit_pass_complete_shape_analysis", "torch._C._jit_pass_concat_frozen_linear", "torch._C._jit_pass_constant_loop_unrolling", "torch._C._jit_pass_constant_pooling", "torch._C._jit_pass_constant_propagation_immutable_types", "torch._C._jit_pass_constant_propagation", "torch._C._jit_pass_convert_frozen_ops_to_mkldnn", "torch._C._jit_pass_create_autodiff_subgraphs", "torch._C._jit_pass_create_functional_graphs", "torch._C._jit_pass_cse", "torch._C._jit_pass_custom_pattern_based_rewrite_graph", "torch._C._jit_pass_custom_pattern_based_rewrite", "torch._C._jit_pass_dbr_quant_remove_redundant_aliases", "torch._C._jit_pass_dce_allow_deleting_nodes_with_side_effects", "torch._C._jit_pass_dce", "torch._C._jit_pass_decompose_ops", "torch._C._jit_pass_dedup_module_uses", "torch._C._jit_pass_erase_number_types", "torch._C._jit_pass_erase_shape_information", "torch._C._jit_pass_filter_non_tensor_arguments", "torch._C._jit_pass_fixup_onnx_controlflow_node", "torch._C._jit_pass_fold_convbn", "torch._C._jit_pass_fold_frozen_conv_add_or_sub", "torch._C._jit_pass_fold_frozen_conv_bn", "torch._C._jit_pass_fold_frozen_conv_mul_or_div", "torch._C._jit_pass_fold_frozen_linear_bn", "torch._C._jit_pass_fold_prepacking_ops", "torch._C._jit_pass_functional_to_inplace_activation", "torch._C._jit_pass_fuse_add_relu", "torch._C._jit_pass_fuse_addmm", "torch._C._jit_pass_fuse_clamp_w_prepacked_linear_conv", "torch._C._jit_pass_fuse_frozen_conv_add_relu", "torch._C._jit_pass_fuse_linear", "torch._C._jit_pass_fuse_quantized_add_relu", "torch._C._jit_pass_fuse_tensorexprs", "torch._C._jit_pass_fuse", "torch._C._jit_pass_inline_fork_wait", "torch._C._jit_pass_inline_functional_graphs", "torch._C._jit_pass_inline", "torch._C._jit_pass_inplace_to_functional_activation", "torch._C._jit_pass_insert_observer_method_for_ondevice_ptq", "torch._C._jit_pass_insert_observers", 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"torch._C._special.special_modified_bessel_i0", "torch._C._special.special_modified_bessel_i1", "torch._C._special.special_modified_bessel_k0", "torch._C._special.special_modified_bessel_k1", "torch._C._special.special_multigammaln", "torch._C._special.special_ndtr", "torch._C._special.special_ndtri", "torch._C._special.special_polygamma", "torch._C._special.special_psi", "torch._C._special.special_round", "torch._C._special.special_scaled_modified_bessel_k0", "torch._C._special.special_scaled_modified_bessel_k1", "torch._C._special.special_shifted_chebyshev_polynomial_t", "torch._C._special.special_shifted_chebyshev_polynomial_u", "torch._C._special.special_shifted_chebyshev_polynomial_v", "torch._C._special.special_shifted_chebyshev_polynomial_w", "torch._C._special.special_sinc", "torch._C._special.special_softmax", "torch._C._special.special_spherical_bessel_j0", "torch._C._special.special_xlog1py", "torch._C._special.special_xlogy", "torch._C._special.special_zeta", "torch._C._stash_obj_in_tls", "torch._C._storage_id", "torch._C._storage_Use_Count", "torch._C._supported_qengines", "torch._C._te.abs", "torch._C._te.acos", "torch._C._te.annotate_input_shapes", "torch._C._te.asin", "torch._C._te.atan", "torch._C._te.atan2", "torch._C._te.ceil", "torch._C._te.Compute", "torch._C._te.Compute2", "torch._C._te.construct_codegen", "torch._C._te.cos", "torch._C._te.cosh", "torch._C._te.erf", "torch._C._te.erfc", "torch._C._te.exp", "torch._C._te.expm1", "torch._C._te.fixup_missing_shape_info", "torch._C._te.floor", "torch._C._te.fmod", "torch._C._te.frac", "torch._C._te.ifThenElse", "torch._C._te.is_graph_compilable", "torch._C._te.isnan", "torch._C._te.lgamma", "torch._C._te.log", "torch._C._te.log10", "torch._C._te.log1p", "torch._C._te.log2", "torch._C._te.lower", "torch._C._te.make_shapes_symbolic", "torch._C._te.pow", "torch._C._te.Reduce", "torch._C._te.remainder", "torch._C._te.remove_graph_output", "torch._C._te.remove_unused_self_argument", "torch._C._te.replace_list_output_with_tuple", "torch._C._te.round", "torch._C._te.rsqrt", "torch._C._te.sigmoid", "torch._C._te.simplify", "torch._C._te.sin", "torch._C._te.sinh", "torch._C._te.sqrt", "torch._C._te.tan", "torch._C._te.tanh", "torch._C._te.trim_graph", "torch._C._te.trunc", "torch._C._tensor_impl_raw_handle", "torch._C._test_only_add_entry_to_op_version_map", "torch._C._test_only_populate_upgraders", "torch._C._test_only_remove_entry_to_op_version_map", "torch._C._test_only_remove_upgraders", "torch._C._to_dlpack", "torch._C._to_functionality_key", "torch._C._tracer_set_force_outplace", "torch._C._tracer_set_get_unique_name_fn", "torch._C._tracer_warn_use_python", "torch._C._unset_default_mobile_cpu_allocator", "torch._C._unset_dispatch_mode", "torch._C._valgrind_supported_platform", "torch._C._valgrind_toggle_and_dump_stats", "torch._C._valgrind_toggle", "torch._C._verbose.mkl_set_verbose", "torch._C._verbose.mkldnn_set_verbose", "torch._C._vmapmode_decrement_nesting", "torch._C._vmapmode_increment_nesting", "torch._C._warn_deprecation", "torch._C._warn", "torch._C._will_engine_execute_node", "torch._C._wrap_tensor_impl", "torch._C.autocast_decrement_nesting", "torch._C.autocast_increment_nesting", "torch._C.clear_autocast_cache", "torch._C.fork", "torch._C.get_autocast_cpu_dtype", "torch._C.get_autocast_gpu_dtype", "torch._C.get_autocast_ipu_dtype", "torch._C.get_autocast_xla_dtype", "torch._C.get_default_dtype", "torch._C.get_num_interop_threads", "torch._C.get_num_threads", "torch._C.import_ir_module_from_buffer", "torch._C.import_ir_module", "torch._C.init_num_threads", "torch._C.is_anomaly_check_nan_enabled", "torch._C.is_anomaly_enabled", "torch._C.is_autocast_cache_enabled", "torch._C.is_autocast_cpu_enabled", "torch._C.is_autocast_enabled", "torch._C.is_autocast_ipu_enabled", "torch._C.is_autocast_xla_enabled", "torch._C.is_grad_enabled", "torch._C.is_inference_mode_enabled", "torch._C.merge_type_from_type_comment", "torch._C.parse_ir", "torch._C.parse_schema", "torch._C.parse_type_comment", "torch._C.read_vitals", "torch._C.set_anomaly_enabled", "torch._C.set_autocast_cache_enabled", "torch._C.set_autocast_cpu_dtype", "torch._C.set_autocast_cpu_enabled", "torch._C.set_autocast_enabled", "torch._C.set_autocast_gpu_dtype", "torch._C.set_autocast_ipu_dtype", "torch._C.set_autocast_ipu_enabled", "torch._C.set_autocast_xla_dtype", "torch._C.set_autocast_xla_enabled", "torch._C.set_flush_denormal", "torch._C.set_num_interop_threads", "torch._C.set_num_threads", "torch._C.set_vital", "torch._C.unify_type_list", "torch._C.vitals_enabled", "torch._C.wait", "torch._cast_Byte", "torch._cast_Char", "torch._cast_Double", "torch._cast_Float", "torch._cast_Half", "torch._cast_Int", "torch._cast_Long", "torch._cast_Short", "torch._choose_qparams_per_tensor", "torch._coalesce", "torch._compute_linear_combination", "torch._conj_copy", "torch._conj_physical", "torch._conj", "torch._convert_indices_from_coo_to_csr", "torch._convert_indices_from_csr_to_coo", "torch._convert_weight_to_int4pack", "torch._convolution_mode", "torch._convolution", "torch._copy_from_and_resize", "torch._copy_from", "torch._cslt_compress", "torch._cslt_sparse_mm", "torch._ctc_loss", "torch._cudnn_ctc_loss", "torch._cudnn_init_dropout_state", "torch._cudnn_rnn_flatten_weight", "torch._cudnn_rnn", "torch._cufft_clear_plan_cache", "torch._cufft_get_plan_cache_max_size", "torch._cufft_get_plan_cache_size", "torch._cufft_set_plan_cache_max_size", "torch._cummax_helper", "torch._cummin_helper", "torch._debug_has_internal_overlap", "torch._dim_arange", "torch._dirichlet_grad", "torch._disable_functionalization", "torch._efficientzerotensor", "torch._embedding_bag_forward_only", "torch._embedding_bag", "torch._empty_affine_quantized", "torch._empty_per_channel_affine_quantized", "torch._enable_functionalization", "torch._euclidean_dist", "torch._fake_quantize_learnable_per_channel_affine", "torch._fake_quantize_learnable_per_tensor_affine", "torch._fake_quantize_per_tensor_affine_cachemask_tensor_qparams", "torch._fft_c2c", "torch._fft_c2r", "torch._fft_r2c", "torch._fill_mem_eff_dropout_mask_", "torch._foobar", "torch._foreach_abs_", "torch._foreach_abs", "torch._foreach_acos_", "torch._foreach_acos", "torch._foreach_add_", "torch._foreach_add", "torch._foreach_addcdiv_", "torch._foreach_addcdiv", "torch._foreach_addcmul_", "torch._foreach_addcmul", "torch._foreach_asin_", "torch._foreach_asin", "torch._foreach_atan_", "torch._foreach_atan", "torch._foreach_ceil_", "torch._foreach_ceil", "torch._foreach_clamp_max_", "torch._foreach_clamp_max", "torch._foreach_clamp_min_", "torch._foreach_clamp_min", "torch._foreach_copy_", "torch._foreach_cos_", "torch._foreach_cos", "torch._foreach_cosh_", "torch._foreach_cosh", "torch._foreach_div_", "torch._foreach_div", "torch._foreach_erf_", "torch._foreach_erf", 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"torch._foreach_sin_", "torch._foreach_sin", "torch._foreach_sinh_", "torch._foreach_sinh", "torch._foreach_sqrt_", "torch._foreach_sqrt", "torch._foreach_sub_", "torch._foreach_sub", "torch._foreach_tan_", "torch._foreach_tan", "torch._foreach_tanh_", "torch._foreach_tanh", "torch._foreach_trunc_", "torch._foreach_trunc", "torch._foreach_zero_", "torch._freeze_functional_tensor", "torch._from_functional_tensor", "torch._functional_assert_async", "torch._functional_sym_constrain_range_for_size", "torch._functional_sym_constrain_range", "torch._functionalize_are_all_mutations_hidden_from_autograd", "torch._functionalize_commit_update", "torch._functionalize_enable_reapply_views", "torch._functionalize_has_data_mutation", "torch._functionalize_has_metadata_mutation", "torch._functionalize_is_multi_output_view", "torch._functionalize_mark_mutation_hidden_from_autograd", "torch._functionalize_replace", "torch._functionalize_sync", "torch._functionalize_was_storage_changed", 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"torch._mirror_autograd_meta_to", "torch._mixed_dtypes_linear", "torch._mkldnn_reshape", "torch._mkldnn_transpose_", "torch._mkldnn_transpose", "torch._mps_convolution_transpose", "torch._mps_convolution", "torch._native_batch_norm_legit_no_training", "torch._native_batch_norm_legit", "torch._native_multi_head_attention", "torch._neg_view_copy", "torch._neg_view", "torch._nested_from_padded_and_nested_example", "torch._nested_tensor_from_mask_left_aligned", "torch._nested_tensor_from_tensor_list", "torch._nested_tensor_softmax_with_shape", "torch._nested_view_from_buffer_copy", "torch._nested_view_from_buffer", "torch._nnpack_available", "torch._nnpack_spatial_convolution", "torch._pack_padded_sequence", "torch._pad_packed_sequence", "torch._pin_memory", "torch._prelu_kernel", "torch._propagate_xla_data", "torch._remove_batch_dim", "torch._reshape_alias_copy", "torch._reshape_from_tensor", "torch._resize_output_", "torch._rowwise_prune", "torch._sample_dirichlet", 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"torch._to_cpu", "torch._to_functional_tensor", "torch._to_sparse_semi_structured", "torch._transform_bias_rescale_qkv", "torch._transformer_encoder_layer_fwd", "torch._trilinear", "torch._triton_multi_head_attention", "torch._triton_scaled_dot_attention", "torch._unique", "torch._unique2", "torch._unpack_dual", "torch._unsafe_index_put", "torch._unsafe_index", "torch._use_cudnn_ctc_loss", "torch._use_cudnn_rnn_flatten_weight", "torch._validate_compressed_sparse_indices", "torch._validate_sparse_bsc_tensor_args", "torch._validate_sparse_bsr_tensor_args", "torch._validate_sparse_compressed_tensor_args", "torch._validate_sparse_coo_tensor_args", "torch._validate_sparse_csc_tensor_args", "torch._validate_sparse_csr_tensor_args", "torch._values_copy", "torch._weight_int4pack_mm", "torch._weight_norm_interface", "torch._weight_norm", "torch.abs_", "torch.abs", "torch.absolute", "torch.acos_", "torch.acos", "torch.acosh_", "torch.acosh", "torch.adaptive_avg_pool1d", 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"torch.bartlett_window", "torch.batch_norm_backward_elemt", "torch.batch_norm_backward_reduce", "torch.batch_norm_elemt", "torch.batch_norm_gather_stats_with_counts", "torch.batch_norm_gather_stats", "torch.batch_norm_stats", "torch.batch_norm_update_stats", "torch.batch_norm", "torch.bernoulli", "torch.bilinear", "torch.binary_cross_entropy_with_logits", "torch.bincount", "torch.binomial", "torch.bitwise_and", "torch.bitwise_left_shift", "torch.bitwise_not", "torch.bitwise_or", "torch.bitwise_right_shift", "torch.bitwise_xor", "torch.blackman_window", "torch.bmm", "torch.broadcast_to", "torch.bucketize", "torch.can_cast", "torch.cat", "torch.ccol_indices_copy", "torch.ceil_", "torch.ceil", "torch.celu_", "torch.celu", "torch.channel_shuffle", "torch.cholesky_inverse", "torch.cholesky_solve", "torch.cholesky", "torch.choose_qparams_optimized", "torch.chunk", "torch.clamp_", "torch.clamp_max_", "torch.clamp_max", "torch.clamp_min_", "torch.clamp_min", "torch.clamp", "torch.clip_", "torch.clip", "torch.clone", "torch.col_indices_copy", "torch.column_stack", "torch.combinations", "torch.complex", "torch.concat", "torch.concatenate", "torch.conj_physical_", "torch.conj_physical", "torch.conj", "torch.constant_pad_nd", "torch.conv_tbc", "torch.conv_transpose1d", "torch.conv_transpose2d", "torch.conv_transpose3d", "torch.conv1d", "torch.conv2d", "torch.conv3d", "torch.convolution", "torch.copysign", "torch.corrcoef", "torch.cos_", "torch.cos", "torch.cosh_", "torch.cosh", "torch.cosine_embedding_loss", "torch.cosine_similarity", "torch.count_nonzero", "torch.cov", "torch.cross", "torch.crow_indices_copy", "torch.ctc_loss", "torch.cuda._get_device_properties", "torch.cudnn_affine_grid_generator", "torch.cudnn_batch_norm", "torch.cudnn_convolution_add_relu", "torch.cudnn_convolution_relu", "torch.cudnn_convolution_transpose", "torch.cudnn_convolution", "torch.cudnn_grid_sampler", "torch.cudnn_is_acceptable", "torch.cummax", "torch.cummin", "torch.cumprod", "torch.cumsum", "torch.cumulative_trapezoid", "torch.deg2rad_", "torch.deg2rad", "torch.dequantize", "torch.det", "torch.detach_", "torch.detach_copy", "torch.detach", "torch.diag_embed", "torch.diag", "torch.diagflat", "torch.diagonal_copy", "torch.diagonal_scatter", "torch.diagonal", "torch.diff", "torch.digamma", "torch.dist", "torch.div", "torch.divide", "torch.dot", "torch.dropout_", "torch.dropout", "torch.dsmm", "torch.dsplit", "torch.dstack", "torch.embedding_bag", "torch.embedding_renorm_", "torch.embedding", "torch.empty_like", "torch.empty_permuted", "torch.empty_quantized", "torch.empty_strided", "torch.empty", "torch.eq", "torch.equal", "torch.erf_", "torch.erf", "torch.erfc_", "torch.erfc", "torch.erfinv", "torch.exp_", "torch.exp", "torch.exp2_", "torch.exp2", "torch.expand_copy", "torch.expm1_", "torch.expm1", "torch.eye", "torch.fake_quantize_per_channel_affine", "torch.fake_quantize_per_tensor_affine", "torch.fbgemm_linear_fp16_weight_fp32_activation", "torch.fbgemm_linear_fp16_weight", "torch.fbgemm_linear_int8_weight_fp32_activation", "torch.fbgemm_linear_int8_weight", "torch.fbgemm_linear_quantize_weight", "torch.fbgemm_pack_gemm_matrix_fp16", "torch.fbgemm_pack_quantized_matrix", "torch.feature_alpha_dropout_", "torch.feature_alpha_dropout", "torch.feature_dropout_", "torch.feature_dropout", "torch.fill_", "torch.fill", "torch.fix_", "torch.fix", "torch.flatten", "torch.flip", "torch.fliplr", "torch.flipud", "torch.float_power", "torch.floor_", "torch.floor_divide", "torch.floor", "torch.fmax", "torch.fmin", "torch.fmod", "torch.frac_", "torch.frac", "torch.frexp", "torch.frobenius_norm", "torch.from_file", "torch.from_numpy", "torch.frombuffer", "torch.full_like", "torch.full", "torch.fused_moving_avg_obs_fake_quant", "torch.gather", "torch.gcd_", "torch.gcd", "torch.ge", "torch.geqrf", "torch.ger", "torch.get_device", "torch.gradient", "torch.greater_equal", "torch.greater", "torch.grid_sampler_2d", "torch.grid_sampler_3d", "torch.grid_sampler", "torch.group_norm", "torch.gru_cell", "torch.gru", "torch.gt", "torch.hamming_window", "torch.hann_window", "torch.hardshrink", "torch.heaviside", "torch.hinge_embedding_loss", "torch.histc", "torch.histogram", "torch.histogramdd", "torch.hsmm", "torch.hsplit", "torch.hspmm", "torch.hstack", "torch.hypot", "torch.i0_", "torch.i0", "torch.igamma", "torch.igammac", "torch.imag", "torch.index_add", "torch.index_copy", "torch.index_fill", "torch.index_put_", "torch.index_put", "torch.index_reduce", "torch.index_select", "torch.indices_copy", "torch.inner", "torch.instance_norm", "torch.int_repr", "torch.inverse", "torch.is_complex", "torch.is_conj", "torch.is_distributed", "torch.is_floating_point", "torch.is_inference", "torch.is_neg", "torch.is_nonzero", "torch.is_same_size", "torch.is_signed", "torch.is_vulkan_available", "torch.isclose", "torch.isfinite", "torch.isin", "torch.isinf", "torch.isnan", "torch.isneginf", "torch.isposinf", "torch.isreal", "torch.istft", "torch.kaiser_window", "torch.kl_div", "torch.kron", "torch.kthvalue", "torch.layer_norm", "torch.lcm_", "torch.lcm", "torch.ldexp_", "torch.ldexp", "torch.le", "torch.lerp", "torch.less_equal", "torch.less", "torch.lgamma", "torch.linspace", "torch.log_", "torch.log_softmax", "torch.log", "torch.log10_", "torch.log10", "torch.log1p_", "torch.log1p", "torch.log2_", "torch.log2", "torch.logaddexp", "torch.logaddexp2", "torch.logcumsumexp", "torch.logdet", "torch.logical_and", "torch.logical_not", "torch.logical_or", "torch.logical_xor", "torch.logit_", "torch.logit", "torch.logspace", "torch.logsumexp", "torch.lstm_cell", "torch.lstm", "torch.lt", "torch.lu_solve", "torch.lu_unpack", "torch.margin_ranking_loss", "torch.masked_fill", "torch.masked_scatter", "torch.masked_select", "torch.matmul", "torch.matrix_exp", "torch.matrix_power", "torch.max_pool1d_with_indices", "torch.max_pool1d", "torch.max_pool2d", "torch.max_pool3d", "torch.max", "torch.maximum", "torch.mean", "torch.median", "torch.min", "torch.minimum", "torch.miopen_batch_norm", "torch.miopen_convolution_add_relu", "torch.miopen_convolution_relu", "torch.miopen_convolution_transpose", "torch.miopen_convolution", "torch.miopen_depthwise_convolution", "torch.miopen_rnn", "torch.mkldnn_adaptive_avg_pool2d", "torch.mkldnn_convolution", "torch.mkldnn_linear_backward_weights", "torch.mkldnn_max_pool2d", "torch.mkldnn_max_pool3d", "torch.mkldnn_rnn_layer", "torch.mm", "torch.mode", "torch.moveaxis", "torch.movedim", "torch.msort", "torch.mul", "torch.multinomial", "torch.multiply", "torch.mv", "torch.mvlgamma", "torch.nan_to_num_", "torch.nan_to_num", "torch.nanmean", "torch.nanmedian", "torch.nanquantile", "torch.nansum", "torch.narrow_copy", "torch.narrow", "torch.native_batch_norm", "torch.native_channel_shuffle", "torch.native_dropout", "torch.native_group_norm", "torch.native_layer_norm", "torch.native_norm", "torch.ne", "torch.neg_", "torch.neg", "torch.negative_", "torch.negative", "torch.nextafter", "torch.nonzero_static", "torch.nonzero", "torch.norm_except_dim", "torch.normal", "torch.not_equal", "torch.nuclear_norm", "torch.numel", "torch.obj", "torch.ones_like", "torch.ones", "torch.orgqr", "torch.ormqr", "torch.outer", "torch.pairwise_distance", "torch.pdist", "torch.permute_copy", "torch.permute", "torch.pinverse", "torch.pixel_shuffle", "torch.pixel_unshuffle", "torch.poisson_nll_loss", "torch.poisson", "torch.polar", "torch.polygamma", "torch.positive", "torch.pow", "torch.prelu", "torch.prod", "torch.promote_types", "torch.put", "torch.q_per_channel_axis", "torch.q_per_channel_scales", "torch.q_per_channel_zero_points", "torch.q_scale", "torch.q_zero_point", "torch.qr", "torch.quantile", "torch.quantize_per_channel", "torch.quantize_per_tensor_dynamic", "torch.quantize_per_tensor", "torch.quantized_batch_norm", "torch.quantized_gru_cell", "torch.quantized_lstm_cell", "torch.quantized_max_pool1d", "torch.quantized_max_pool2d", "torch.quantized_max_pool3d", "torch.quantized_rnn_relu_cell", "torch.quantized_rnn_tanh_cell", "torch.rad2deg_", "torch.rad2deg", "torch.rand_like", "torch.rand", "torch.randint_like", "torch.randint", "torch.randn_like", "torch.randn", "torch.randperm", "torch.range", "torch.ravel", "torch.real", "torch.reciprocal_", "torch.reciprocal", "torch.relu_", "torch.relu", "torch.remainder", "torch.renorm", "torch.repeat_interleave", "torch.reshape", "torch.resize_as_", "torch.resize_as_sparse_", "torch.resolve_conj", "torch.resolve_neg", "torch.result_type", "torch.rnn_relu_cell", "torch.rnn_relu", "torch.rnn_tanh_cell", "torch.rnn_tanh", "torch.roll", "torch.rot90", "torch.round_", "torch.round", "torch.row_indices_copy", "torch.row_stack", "torch.rrelu_", "torch.rrelu", "torch.rsqrt_", "torch.rsqrt", "torch.rsub", "torch.saddmm", "torch.scalar_tensor", "torch.scatter_add", "torch.scatter_reduce", "torch.scatter", "torch.searchsorted", "torch.segment_reduce", "torch.select_copy", "torch.select_scatter", "torch.select", "torch.selu_", "torch.selu", "torch.sgn", "torch.sigmoid_", "torch.sigmoid", "torch.sign", "torch.signal.windows.windows.sqrt", "torch.signbit", "torch.sin_", "torch.sin", "torch.sinc_", "torch.sinc", "torch.sinh_", "torch.sinh", "torch.slice_copy", "torch.slice_scatter", "torch.slogdet", "torch.smm", "torch.softmax", "torch.sort", "torch.sparse_bsc_tensor", "torch.sparse_bsr_tensor", "torch.sparse_compressed_tensor", "torch.sparse_coo_tensor", "torch.sparse_csc_tensor", "torch.sparse_csr_tensor", "torch.split_copy", "torch.split_with_sizes_copy", "torch.split_with_sizes", "torch.spmm", "torch.sqrt_", "torch.sqrt", "torch.square_", "torch.square", "torch.squeeze_copy", "torch.squeeze", "torch.sspaddmm", "torch.stack", "torch.std_mean", "torch.std", "torch.sub", "torch.subtract", "torch.sum", "torch.svd", "torch.swapaxes", "torch.swapdims", "torch.sym_constrain_range_for_size", "torch.sym_constrain_range", "torch.t_copy", "torch.t", "torch.take_along_dim", "torch.take", "torch.tan_", "torch.tan", "torch.tanh_", "torch.tanh", "torch.tensor_split", "torch.tensor", "torch.threshold_", "torch.threshold", "torch.tile", "torch.topk", "torch.trace", "torch.transpose_copy", "torch.transpose", "torch.trapezoid", "torch.trapz", "torch.triangular_solve", "torch.tril_indices", "torch.tril", "torch.triplet_margin_loss", "torch.triu_indices", "torch.triu", "torch.true_divide", "torch.trunc_", "torch.trunc", "torch.unbind_copy", "torch.unbind", "torch.unflatten", "torch.unfold_copy", "torch.unsafe_chunk", "torch.unsafe_split_with_sizes", "torch.unsafe_split", "torch.unsqueeze_copy", "torch.unsqueeze", "torch.values_copy", "torch.vander", "torch.var_mean", "torch.var", "torch.vdot", "torch.view_as_complex_copy", "torch.view_as_complex", "torch.view_as_real_copy", "torch.view_as_real", "torch.view_copy", "torch.vsplit", "torch.vstack", "torch.where", "torch.xlogy_", "torch.xlogy", "torch.zero_", "torch.zeros", ] } if sys.version_info >= (3, 9): torch_c_binding_in_graph_functions["math.lcm"] = TorchInGraphFunctionVariable if sys.version_info >= (3, 11): torch_c_binding_in_graph_functions["math.exp2"] = TorchInGraphFunctionVariable torch_c_binding_in_graph_functions["math.cbrt"] = TorchInGraphFunctionVariable # In graph functions (including constant folding) that are not C bindings torch_non_c_binding_in_graph_functions = { k: TorchInGraphFunctionVariable for k in [ "torch.__future__.get_overwrite_module_params_on_conversion", "torch.__future__.set_overwrite_module_params_on_conversion", "torch.__getattr__", "torch._assert", "torch._check_index", "torch._check_is_size", "torch._check_not_implemented", "torch._check_tensor_all_with", "torch._check_tensor_all", "torch._check_type", "torch._check_value", "torch._check_with", "torch._check", "torch._compile._disable_dynamo", "torch._constrain_as_size", "torch._constrain_as_value", "torch._functorch.apis.chunk_vmap", "torch._functorch.autograd_function.custom_function_call_functionalize", "torch._functorch.autograd_function.custom_function_call_grad", "torch._functorch.autograd_function.custom_function_call_vmap_generate_rule", "torch._functorch.autograd_function.custom_function_call_vmap", "torch._functorch.autograd_function.generate_single_level_function", "torch._functorch.autograd_function.get_tangents_in_dims", "torch._functorch.autograd_function.has_overriden_vmap_rule", "torch._functorch.autograd_function.reductify_leaf", "torch._functorch.autograd_function.reductify", "torch._functorch.autograd_function.validate_vmap_returns_tuple_of_two_elements", "torch._functorch.autograd_function.vmapify_autograd_function", "torch._functorch.autograd_function.wrap_outputs_maintaining_identity", "torch._functorch.batch_norm_replacement.batch_norm_without_running_stats", "torch._functorch.batch_norm_replacement.replace_all_batch_norm_modules_", "torch._functorch.deprecated.combine_state_for_ensemble", "torch._functorch.deprecated.functionalize", "torch._functorch.deprecated.get_warning", "torch._functorch.deprecated.grad_and_value", "torch._functorch.deprecated.hessian", "torch._functorch.deprecated.jacfwd", "torch._functorch.deprecated.jacrev", "torch._functorch.deprecated.jvp", "torch._functorch.deprecated.make_functional_with_buffers", "torch._functorch.deprecated.make_functional", "torch._functorch.deprecated.setup_docs", "torch._functorch.deprecated.vjp", "torch._functorch.deprecated.warn_deprecated", "torch._functorch.eager_transforms._any_differentiable", "torch._functorch.eager_transforms._as_tuple", "torch._functorch.eager_transforms._autograd_grad", "torch._functorch.eager_transforms._check_unique_non_empty", "torch._functorch.eager_transforms._chunked_standard_basis_for_", "torch._functorch.eager_transforms._construct_standard_basis_for", "torch._functorch.eager_transforms._create_differentiable", "torch._functorch.eager_transforms._is_differentiable", "torch._functorch.eager_transforms._jvp_with_argnums", "torch._functorch.eager_transforms._maybe_unwrap_functional_tensor", "torch._functorch.eager_transforms._maybe_wrap_functional_tensor", "torch._functorch.eager_transforms._replace_args", "torch._functorch.eager_transforms._safe_zero_index", "torch._functorch.eager_transforms._slice_argnums", "torch._functorch.eager_transforms._undo_create_differentiable", "torch._functorch.eager_transforms._unwrap_all_tensors_from_functional", "torch._functorch.eager_transforms._validate_and_wrap_argnum", "torch._functorch.eager_transforms._validate_and_wrap_argnums", "torch._functorch.eager_transforms._vjp_with_argnums", "torch._functorch.eager_transforms._wrap_all_tensors_to_functional", "torch._functorch.eager_transforms._wrap_all_tensors", "torch._functorch.eager_transforms._wrap_tensor_for_grad", "torch._functorch.eager_transforms.assert_flat_tuple_of_tensors", "torch._functorch.eager_transforms.assert_non_empty_list_of_tensors", "torch._functorch.eager_transforms.assert_non_empty_tensor_output", "torch._functorch.eager_transforms.assert_output_is_tensor_or_tensors", "torch._functorch.eager_transforms.enable_inplace_requires_grad", "torch._functorch.eager_transforms.error_if_complex", "torch._functorch.eager_transforms.functionalize", "torch._functorch.eager_transforms.grad_and_value", "torch._functorch.eager_transforms.grad_impl", "torch._functorch.eager_transforms.hessian", "torch._functorch.eager_transforms.jacfwd", "torch._functorch.eager_transforms.jacrev", "torch._functorch.eager_transforms.jvp", "torch._functorch.eager_transforms.lazy_dynamo_disable", "torch._functorch.eager_transforms.linearize", "torch._functorch.eager_transforms.noop", "torch._functorch.eager_transforms.safe_unflatten", "torch._functorch.eager_transforms.safe_unpack_dual", "torch._functorch.eager_transforms.vjp", "torch._functorch.functional_call.construct_stacked_leaf", "torch._functorch.functional_call.functional_call", "torch._functorch.functional_call.stack_module_state", "torch._functorch.pyfunctorch.coerce_cinterpreter", "torch._functorch.pyfunctorch.dispatch_functorch", "torch._functorch.pyfunctorch.nested", "torch._functorch.pyfunctorch.retrieve_current_functorch_interpreter", "torch._functorch.pyfunctorch.temporarily_pop_interpreter_stack", "torch._functorch.utils.enable_single_level_autograd_function", "torch._functorch.utils.exposed_in", "torch._functorch.utils.unwrap_dead_wrappers", "torch._functorch.vmap._as_tuple", "torch._functorch.vmap._check_int_or_none", "torch._functorch.vmap._check_out_dims_is_int_or_int_pytree", "torch._functorch.vmap._check_randomness_arg", "torch._functorch.vmap._chunked_vmap", "torch._functorch.vmap._concat_chunked_outputs", "torch._functorch.vmap._create_batched_inputs", "torch._functorch.vmap._flat_vmap", "torch._functorch.vmap._flatten_chunks_output", "torch._functorch.vmap._get_chunked_inputs", "torch._functorch.vmap._get_name", "torch._functorch.vmap._maybe_remove_batch_dim", "torch._functorch.vmap._num_outputs", "torch._functorch.vmap._process_batched_inputs", "torch._functorch.vmap._unwrap_batched", "torch._functorch.vmap._validate_and_get_batch_size", "torch._functorch.vmap.doesnt_support_saved_tensors_hooks", "torch._functorch.vmap.get_chunk_sizes", "torch._functorch.vmap.lazy_load_decompositions", "torch._functorch.vmap.restore_vmap", "torch._functorch.vmap.unwrap_batched", "torch._functorch.vmap.vmap_impl", "torch._functorch.vmap.wrap_batched", "torch._guards.compile_context", "torch._guards.detect_fake_mode", "torch._guards.tracing", "torch._higher_order_ops.map._has_potential_branch_input_alias", "torch._higher_order_ops.map._has_potential_branch_input_mutation", "torch._higher_order_ops.map._stack_pytree", "torch._higher_order_ops.map._unstack_pytree", "torch._higher_order_ops.map.create_fw_bw_graph", "torch._higher_order_ops.map.map_autograd", "torch._higher_order_ops.map.map_dense", "torch._higher_order_ops.map.map_fake_tensor_mode", "torch._higher_order_ops.map.map_functionalize", "torch._higher_order_ops.map.map_proxy_torch_dispatch_mode", "torch._higher_order_ops.map.map_wrapper", "torch._higher_order_ops.map.trace_map", "torch._higher_order_ops.out_dtype.elementwise_dtypes", "torch._higher_order_ops.out_dtype.is_int_mm", "torch._higher_order_ops.out_dtype.out_dtype_dense", "torch._higher_order_ops.out_dtype.out_dtype_fake_tensor_mode", "torch._higher_order_ops.out_dtype.out_dtype_fallback", "torch._higher_order_ops.out_dtype.out_dtype_func", "torch._higher_order_ops.out_dtype.out_dtype_predispatch", "torch._higher_order_ops.out_dtype.out_dtype_proxy", "torch._higher_order_ops.out_dtype.trace_out_dtype", "torch._higher_order_ops.utils.autograd_not_implemented_inner", "torch._higher_order_ops.utils.autograd_not_implemented", "torch._linalg_utils._symeig", "torch._linalg_utils.basis", "torch._linalg_utils.bform", "torch._linalg_utils.conjugate", "torch._linalg_utils.eig", "torch._linalg_utils.get_floating_dtype", "torch._linalg_utils.is_sparse", "torch._linalg_utils.lstsq", "torch._linalg_utils.matmul", "torch._linalg_utils.matrix_rank", "torch._linalg_utils.qform", "torch._linalg_utils.solve", "torch._linalg_utils.symeig", "torch._linalg_utils.transjugate", "torch._linalg_utils.transpose", "torch._load_global_deps", "torch._lowrank._svd_lowrank", "torch._lowrank.get_approximate_basis", "torch._lowrank.pca_lowrank", "torch._lowrank.svd_lowrank", "torch._ops._compute_keyset", "torch._ops._get_tensors", "torch._ops._to_flat_tuple", "torch._ops.add_cached_op", "torch._ops.dl_open_guard", "torch._ops.get_cached_ops", "torch._ops.key_extractor", "torch._ops.mode_stack_per_key", "torch._ops.pop_mode_for_key", "torch._ops.push_mode_for_key", "torch._ops.reset_cached_ops", "torch._ops.resolve_key", "torch._ops.temporarily_pop_mode", "torch._preload_cuda_deps", "torch._register_device_module", "torch._running_with_deploy", "torch._sparse_coo_tensor_unsafe", "torch._weights_only_unpickler._get_allowed_globals", "torch._weights_only_unpickler.load", "torch.align_tensors", "torch.amp.autocast_mode._enter_autocast", "torch.amp.autocast_mode._exit_autocast", "torch.amp.autocast_mode.autocast_decorator", "torch.are_deterministic_algorithms_enabled", "torch.atleast_1d", "torch.atleast_2d", "torch.atleast_3d", "torch.autograd._calculate_shape", "torch.autograd._is_checkpoint_valid", "torch.autograd._make_grads", "torch.autograd._register_py_tensor_class_for_device", "torch.autograd._tensor_or_tensors_to_tuple", "torch.autograd.backward", "torch.autograd.forward_ad.enter_dual_level", "torch.autograd.forward_ad.exit_dual_level", "torch.autograd.forward_ad.make_dual", "torch.autograd.forward_ad.unpack_dual", "torch.autograd.function._iter_filter", "torch.autograd.function._iter_jit_values", "torch.autograd.function._iter_None_tensors", "torch.autograd.function._iter_tensors_permissive", "torch.autograd.function._iter_tensors", "torch.autograd.function._jit_unwrap_structured", "torch.autograd.function._map_tensor_data", "torch.autograd.function._nested_map", "torch.autograd.function._unflatten", "torch.autograd.function.once_differentiable", "torch.autograd.function.traceable", "torch.autograd.functional._as_tuple_nocheck", "torch.autograd.functional._as_tuple", "torch.autograd.functional._autograd_grad", "torch.autograd.functional._check_requires_grad", "torch.autograd.functional._construct_standard_basis_for", "torch.autograd.functional._fill_in_zeros", "torch.autograd.functional._grad_postprocess", "torch.autograd.functional._grad_preprocess", "torch.autograd.functional._jacfwd", "torch.autograd.functional._tuple_postprocess", "torch.autograd.functional._validate_v", "torch.autograd.functional.hessian", "torch.autograd.functional.hvp", "torch.autograd.functional.jacobian", "torch.autograd.functional.jvp", "torch.autograd.functional.vhp", "torch.autograd.functional.vjp", "torch.autograd.grad_mode._enter_inference_mode", "torch.autograd.grad_mode._exit_inference_mode", "torch.autograd.grad", "torch.autograd.gradcheck", "torch.autograd.gradgradcheck", "torch.autograd.graph._get_sid", "torch.autograd.graph._get_tid", "torch.autograd.graph.allow_mutation_on_saved_tensors", "torch.autograd.graph.get_gradient_edge", "torch.autograd.graph.increment_version", "torch.autograd.graph.register_multi_grad_hook", "torch.autograd.variable", "torch.backends.__allow_nonbracketed_mutation", "torch.backends.cpu.get_cpu_capability", "torch.backends.cuda.can_use_efficient_attention", "torch.backends.cuda.can_use_flash_attention", "torch.backends.cuda.enable_flash_sdp", "torch.backends.cuda.enable_math_sdp", "torch.backends.cuda.enable_mem_efficient_sdp", "torch.backends.cuda.flash_sdp_enabled", "torch.backends.cuda.is_built", "torch.backends.cuda.math_sdp_enabled", "torch.backends.cuda.mem_efficient_sdp_enabled", "torch.backends.cuda.preferred_linalg_library", "torch.backends.cuda.sdp_kernel", "torch.backends.cudnn._init", "torch.backends.cudnn.flags", "torch.backends.cudnn.is_acceptable", "torch.backends.cudnn.is_available", "torch.backends.cudnn.set_flags", "torch.backends.cudnn.version", "torch.backends.disable_global_flags", "torch.backends.flags_frozen", "torch.backends.mkl.is_available", "torch.backends.mkldnn.flags", "torch.backends.mkldnn.is_available", "torch.backends.mkldnn.set_flags", "torch.backends.mps._init", "torch.backends.mps.is_available", "torch.backends.mps.is_built", "torch.backends.mps.is_macos13_or_newer", "torch.backends.openmp.is_available", "torch.backends.quantized._get_qengine_id", "torch.backends.quantized._get_qengine_str", "torch.block_diag", "torch.broadcast_tensors", "torch.cartesian_prod", "torch.cdist", "torch.chain_matmul", "torch.compile", "torch.compiled_with_cxx11_abi", "torch.cpu._is_cpu_support_vnni", "torch.cpu.current_device", "torch.cpu.current_stream", "torch.cpu.device_count", "torch.cpu.is_available", "torch.cpu.set_device", "torch.cpu.stream", "torch.cpu.synchronize", "torch.cuda._check_capability", "torch.cuda._check_cubins", "torch.cuda._device_count_nvml", "torch.cuda._get_device", "torch.cuda._get_generator", "torch.cuda._get_nvml_device_index", "torch.cuda._get_pynvml_handler", "torch.cuda._get_rng_state_offset", "torch.cuda._is_compiled", "torch.cuda._lazy_call", "torch.cuda._lazy_init", "torch.cuda._memory_viz._block_extra_legacy", "torch.cuda._memory_viz._block_extra", "torch.cuda._memory_viz._format_size", "torch.cuda._memory_viz._format_viz", "torch.cuda._memory_viz._frame_filter", "torch.cuda._memory_viz._frame_fmt", "torch.cuda._memory_viz._frames_fmt", "torch.cuda._memory_viz._profile_to_snapshot", "torch.cuda._memory_viz._report_free", "torch.cuda._memory_viz._write_blocks", "torch.cuda._memory_viz.calc_active", "torch.cuda._memory_viz.compare", "torch.cuda._memory_viz.format_flamegraph", "torch.cuda._memory_viz.memory", "torch.cuda._memory_viz.profile_plot", "torch.cuda._memory_viz.segment_plot", "torch.cuda._memory_viz.segments", "torch.cuda._memory_viz.segsum", "torch.cuda._memory_viz.trace_plot", "torch.cuda._memory_viz.trace", "torch.cuda._nvml_based_avail", "torch.cuda._parse_visible_devices", "torch.cuda._raw_device_count_nvml", "torch.cuda._raw_device_uuid_nvml", "torch.cuda._register_triton_kernels", "torch.cuda._set_rng_state_offset", "torch.cuda._set_stream_by_id", "torch.cuda._sleep", "torch.cuda._transform_uuid_to_ordinals", "torch.cuda._utils._dummy_type", "torch.cuda._utils._get_device_index", "torch.cuda.amp.autocast_mode._cast", "torch.cuda.amp.autocast_mode.custom_bwd", "torch.cuda.amp.autocast_mode.custom_fwd", "torch.cuda.amp.common.amp_definitely_not_available", "torch.cuda.amp.grad_scaler._refresh_per_optimizer_state", "torch.cuda.can_device_access_peer", "torch.cuda.check_error", "torch.cuda.clock_rate", "torch.cuda.cudart", "torch.cuda.current_blas_handle", "torch.cuda.current_device", "torch.cuda.current_stream", "torch.cuda.default_stream", "torch.cuda.device_count", "torch.cuda.get_arch_list", "torch.cuda.get_device_capability", "torch.cuda.get_device_name", "torch.cuda.get_device_properties", "torch.cuda.get_gencode_flags", "torch.cuda.get_sync_debug_mode", "torch.cuda.graphs.graph_pool_handle", "torch.cuda.graphs.is_current_stream_capturing", "torch.cuda.graphs.make_graphed_callables", "torch.cuda.init", "torch.cuda.ipc_collect", "torch.cuda.is_available", "torch.cuda.is_bf16_supported", "torch.cuda.is_initialized", "torch.cuda.jiterator._create_jit_fn", "torch.cuda.jiterator._create_multi_output_jit_fn", "torch.cuda.memory_usage", "torch.cuda.memory._dump_snapshot", "torch.cuda.memory._free_mutex", "torch.cuda.memory._get_current_allocator", "torch.cuda.memory._host_allocator", "torch.cuda.memory._record_memory_history_impl", "torch.cuda.memory._record_memory_history_legacy", "torch.cuda.memory._record_memory_history", "torch.cuda.memory._save_memory_usage", "torch.cuda.memory._save_segment_usage", "torch.cuda.memory._set_allocator_settings", "torch.cuda.memory._snapshot", "torch.cuda.memory.caching_allocator_alloc", "torch.cuda.memory.caching_allocator_delete", "torch.cuda.memory.change_current_allocator", "torch.cuda.memory.empty_cache", "torch.cuda.memory.get_allocator_backend", "torch.cuda.memory.list_gpu_processes", "torch.cuda.memory.max_memory_allocated", "torch.cuda.memory.max_memory_cached", "torch.cuda.memory.max_memory_reserved", "torch.cuda.memory.mem_get_info", "torch.cuda.memory.memory_allocated", "torch.cuda.memory.memory_cached", "torch.cuda.memory.memory_reserved", "torch.cuda.memory.memory_snapshot", "torch.cuda.memory.memory_stats_as_nested_dict", "torch.cuda.memory.memory_stats", "torch.cuda.memory.memory_summary", "torch.cuda.memory.reset_accumulated_memory_stats", "torch.cuda.memory.reset_max_memory_allocated", "torch.cuda.memory.reset_max_memory_cached", "torch.cuda.memory.reset_peak_memory_stats", "torch.cuda.memory.set_per_process_memory_fraction", "torch.cuda.nccl._check_sequence_type", "torch.cuda.nccl.all_gather", "torch.cuda.nccl.all_reduce", "torch.cuda.nccl.broadcast", "torch.cuda.nccl.init_rank", "torch.cuda.nccl.is_available", "torch.cuda.nccl.reduce_scatter", "torch.cuda.nccl.reduce", "torch.cuda.nccl.unique_id", "torch.cuda.nccl.version", "torch.cuda.nvtx.mark", "torch.cuda.nvtx.range_end", "torch.cuda.nvtx.range_pop", "torch.cuda.nvtx.range_push", "torch.cuda.nvtx.range_start", "torch.cuda.nvtx.range", "torch.cuda.power_draw", "torch.cuda.profiler.init", "torch.cuda.profiler.profile", "torch.cuda.profiler.start", "torch.cuda.profiler.stop", "torch.cuda.random.get_rng_state_all", "torch.cuda.random.initial_seed", "torch.cuda.random.manual_seed_all", "torch.cuda.random.manual_seed", "torch.cuda.random.seed_all", "torch.cuda.random.seed", "torch.cuda.random.set_rng_state_all", "torch.cuda.set_device", "torch.cuda.set_stream", "torch.cuda.set_sync_debug_mode", "torch.cuda.stream", "torch.cuda.synchronize", "torch.cuda.temperature", "torch.cuda.utilization", "torch.einsum", "torch.functional._check_list_size", "torch.functional._consecutive_return_counts", "torch.functional._consecutive_return_inverse_false", "torch.functional._consecutive_return_inverse_true", "torch.functional._consecutive_return_inverse", "torch.functional._consecutive_return_output", "torch.functional._lu_impl", "torch.functional._lu_no_infos", "torch.functional._lu_with_infos", "torch.functional._meshgrid", "torch.functional._return_counts", "torch.functional._return_inverse_false", "torch.functional._return_inverse_true", "torch.functional._return_inverse", "torch.functional._return_output", "torch.functional._unique_consecutive_impl", "torch.functional._unique_impl", "torch.functional._unravel_index", "torch.functional.broadcast_shapes", "torch.functional.lu", "torch.functional.unique", "torch.functional.unravel_index", "torch.futures.collect_all", "torch.futures.wait_all", "torch.get_deterministic_debug_mode", "torch.get_float32_matmul_precision", "torch.is_deterministic_algorithms_warn_only_enabled", "torch.is_storage", "torch.is_tensor", "torch.is_warn_always_enabled", "torch.masked._ops._any", "torch.masked._ops._apply_docstring_templates", "torch.masked._ops._canonical_dim", "torch.masked._ops._combine_input_and_mask", "torch.masked._ops._generate_docstring", "torch.masked._ops._input_mask", "torch.masked._ops._output_mask", "torch.masked._ops._reduction_identity", "torch.masked._ops._sparse_coo_flatten_indices", "torch.masked._ops._sparse_coo_scatter_reduction_helper", "torch.masked._ops._sparse_coo_where", "torch.masked._ops._sparse_csr_segment_reduction_helper", "torch.masked._ops._sparse_csr_where", "torch.masked._ops._std_var", "torch.masked._ops._where", "torch.masked._ops.amax", "torch.masked._ops.amin", "torch.masked._ops.argmax", "torch.masked._ops.argmin", "torch.masked._ops.corresponding_real_dtype", "torch.masked._ops.cumprod", "torch.masked._ops.cumsum", "torch.masked._ops.log_softmax", "torch.masked._ops.logaddexp", "torch.masked._ops.logsumexp", "torch.masked._ops.mean", "torch.masked._ops.median", "torch.masked._ops.norm", "torch.masked._ops.normalize", "torch.masked._ops.prod", "torch.masked._ops.softmax", "torch.masked._ops.softmin", "torch.masked._ops.std", "torch.masked._ops.sum", "torch.masked._ops.var", "torch.meshgrid", "torch.mps._get_default_mps_generator", "torch.mps.current_allocated_memory", "torch.mps.driver_allocated_memory", "torch.mps.empty_cache", "torch.mps.get_rng_state", "torch.mps.manual_seed", "torch.mps.profiler.profile", "torch.mps.profiler.start", "torch.mps.profiler.stop", "torch.mps.seed", "torch.mps.set_per_process_memory_fraction", "torch.mps.set_rng_state", "torch.mps.synchronize", "torch.nested._internal.nested_tensor.buffer_from_jagged", "torch.nested._internal.nested_tensor.get_tensor_symint", "torch.nested._internal.nested_tensor.is_expandable_to", "torch.nested._internal.nested_tensor.jagged_from_list", "torch.nested._internal.nested_tensor.jagged_from_tensor_and_lengths", "torch.nested.as_nested_tensor", "torch.nested.narrow", "torch.nested.nested_tensor", "torch.nn._reduction.get_enum", "torch.nn._reduction.legacy_get_enum", "torch.nn._reduction.legacy_get_string", "torch.nn.factory_kwargs", "torch.nn.functional._adaptive_max_pool1d", "torch.nn.functional._adaptive_max_pool2d", "torch.nn.functional._adaptive_max_pool3d", "torch.nn.functional._canonical_mask", "torch.nn.functional._fractional_max_pool2d", "torch.nn.functional._fractional_max_pool3d", "torch.nn.functional._get_softmax_dim", "torch.nn.functional._in_projection_packed", "torch.nn.functional._in_projection", "torch.nn.functional._is_integer", "torch.nn.functional._max_pool1d", "torch.nn.functional._max_pool2d", "torch.nn.functional._max_pool3d", "torch.nn.functional._mha_shape_check", "torch.nn.functional._no_grad_embedding_renorm_", "torch.nn.functional._none_or_dtype", "torch.nn.functional._threshold", "torch.nn.functional._unpool_output_size", "torch.nn.functional._verify_batch_size", "torch.nn.functional._verify_spatial_size", "torch.nn.functional.adaptive_avg_pool2d", "torch.nn.functional.adaptive_avg_pool3d", "torch.nn.functional.adaptive_max_pool1d_with_indices", "torch.nn.functional.adaptive_max_pool1d", "torch.nn.functional.adaptive_max_pool2d_with_indices", "torch.nn.functional.adaptive_max_pool2d", "torch.nn.functional.adaptive_max_pool3d_with_indices", "torch.nn.functional.adaptive_max_pool3d", "torch.nn.functional.affine_grid", "torch.nn.functional.alpha_dropout", "torch.nn.functional.assert_int_or_pair", "torch.nn.functional.batch_norm", "torch.nn.functional.binary_cross_entropy_with_logits", "torch.nn.functional.binary_cross_entropy", "torch.nn.functional.celu", "torch.nn.functional.cosine_embedding_loss", "torch.nn.functional.cross_entropy", "torch.nn.functional.ctc_loss", "torch.nn.functional.dropout", "torch.nn.functional.dropout1d", "torch.nn.functional.dropout2d", "torch.nn.functional.dropout3d", "torch.nn.functional.elu", "torch.nn.functional.embedding_bag", "torch.nn.functional.embedding", "torch.nn.functional.feature_alpha_dropout", "torch.nn.functional.fold", "torch.nn.functional.fractional_max_pool2d_with_indices", "torch.nn.functional.fractional_max_pool2d", "torch.nn.functional.fractional_max_pool3d_with_indices", "torch.nn.functional.fractional_max_pool3d", "torch.nn.functional.gaussian_nll_loss", "torch.nn.functional.glu", "torch.nn.functional.grid_sample", "torch.nn.functional.group_norm", "torch.nn.functional.gumbel_softmax", "torch.nn.functional.hardsigmoid", "torch.nn.functional.hardswish", "torch.nn.functional.hardtanh", "torch.nn.functional.hinge_embedding_loss", "torch.nn.functional.huber_loss", "torch.nn.functional.instance_norm", "torch.nn.functional.interpolate", "torch.nn.functional.kl_div", "torch.nn.functional.l1_loss", "torch.nn.functional.layer_norm", "torch.nn.functional.leaky_relu", "torch.nn.functional.local_response_norm", "torch.nn.functional.log_softmax", "torch.nn.functional.lp_pool1d", "torch.nn.functional.lp_pool2d", "torch.nn.functional.margin_ranking_loss", "torch.nn.functional.max_pool1d_with_indices", "torch.nn.functional.max_pool1d", "torch.nn.functional.max_pool2d_with_indices", "torch.nn.functional.max_pool2d", "torch.nn.functional.max_pool3d_with_indices", "torch.nn.functional.max_pool3d", "torch.nn.functional.max_unpool1d", "torch.nn.functional.max_unpool2d", "torch.nn.functional.max_unpool3d", "torch.nn.functional.mish", "torch.nn.functional.mse_loss", "torch.nn.functional.multi_head_attention_forward", "torch.nn.functional.multi_margin_loss", "torch.nn.functional.multilabel_margin_loss", "torch.nn.functional.multilabel_soft_margin_loss", "torch.nn.functional.nll_loss", "torch.nn.functional.normalize", "torch.nn.functional.poisson_nll_loss", "torch.nn.functional.relu", "torch.nn.functional.relu6", "torch.nn.functional.rrelu", "torch.nn.functional.selu", "torch.nn.functional.sigmoid", "torch.nn.functional.silu", "torch.nn.functional.smooth_l1_loss", "torch.nn.functional.soft_margin_loss", "torch.nn.functional.softmax", "torch.nn.functional.softmin", "torch.nn.functional.softsign", "torch.nn.functional.tanh", "torch.nn.functional.tanhshrink", "torch.nn.functional.triplet_margin_loss", "torch.nn.functional.unfold", "torch.nn.functional.upsample_bilinear", "torch.nn.functional.upsample_nearest", "torch.nn.functional.upsample", "torch.nn.grad._pair", "torch.nn.grad._single", "torch.nn.grad._triple", "torch.nn.grad.conv1d_input", "torch.nn.grad.conv1d_weight", "torch.nn.grad.conv2d_input", "torch.nn.grad.conv2d_weight", "torch.nn.grad.conv3d_input", "torch.nn.grad.conv3d_weight", "torch.nn.modules.activation._arg_requires_grad", "torch.nn.modules.activation._check_arg_device", "torch.nn.modules.activation._is_make_fx_tracing", "torch.nn.modules.container._addindent", "torch.nn.modules.transformer._detect_is_causal_mask", "torch.nn.modules.transformer._generate_square_subsequent_mask", "torch.nn.modules.transformer._get_activation_fn", "torch.nn.modules.transformer._get_clones", "torch.nn.modules.transformer._get_seq_len", "torch.nn.modules.utils._list_with_default", "torch.nn.modules.utils._ntuple", "torch.nn.modules.utils._quadruple", "torch.nn.modules.utils._reverse_repeat_tuple", "torch.nn.modules.utils.consume_prefix_in_state_dict_if_present", "torch.nn.parameter.is_lazy", "torch.norm", "torch.quantization.default_eval_fn", "torch.random._seed_custom_device", "torch.random.fork_rng", "torch.random.initial_seed", "torch.random.seed", "torch.return_types.pytree_register_structseq", "torch.set_default_device", "torch.set_default_dtype", "torch.set_default_tensor_type", "torch.set_deterministic_debug_mode", "torch.set_float32_matmul_precision", "torch.set_warn_always", "torch.signal.windows.windows._add_docstr", "torch.signal.windows.windows._window_function_checks", "torch.signal.windows.windows.bartlett", "torch.signal.windows.windows.blackman", "torch.signal.windows.windows.cosine", "torch.signal.windows.windows.exponential", "torch.signal.windows.windows.gaussian", "torch.signal.windows.windows.general_cosine", "torch.signal.windows.windows.general_hamming", "torch.signal.windows.windows.hamming", "torch.signal.windows.windows.hann", "torch.signal.windows.windows.kaiser", "torch.signal.windows.windows.merge_dicts", "torch.signal.windows.windows.nuttall", "torch.signal.windows.windows.parse_kwargs", "torch.sparse.as_sparse_gradcheck", "torch.sparse.semi_structured.to_sparse_semi_structured", "torch.sparse.sum", "torch.split", "torch.stft", "torch.sym_float", "torch.sym_int", "torch.sym_ite", "torch.sym_max", "torch.sym_min", "torch.sym_not", "torch.tensordot", "torch.typename", "torch.unique_consecutive", "torch.use_deterministic_algorithms", ] } torch_name_rule_map = { **manual_torch_name_rule_map, **torch_ctx_manager_classes, **torch_c_binding_in_graph_functions, **torch_non_c_binding_in_graph_functions, } """ Generate the torch object - Dynamo tracing rule (the wrapping variable) map. """ @functools.lru_cache(None) def get_torch_obj_rule_map(): d = dict() for k, v in torch_name_rule_map.items(): obj = load_object(k) if obj is not None: d[obj] = v return d def _load_obj_from_str(fully_qualified_name): module, obj_name = fully_qualified_name.rsplit(".", maxsplit=1) return getattr(importlib.import_module(module), obj_name) """ Load string represented torch objects. """ def load_object(name): try: x = name.split("#") if len(x) == 2: obj = _load_obj_from_str(x[0]) val = getattr(obj, x[1]) else: assert len(x) == 1, f"Invalid obj name {name}" val = _load_obj_from_str(x[0]) if hasattr(val, "__wrapped__"): val = val.__wrapped__ except (AttributeError, ModuleNotFoundError): val = None return val """ Get all torch.Tensor methods which are allowed to be in graph functions. """ @functools.lru_cache(None) def get_tensor_method(): s = set() for name in dir(torch.Tensor): method = getattr(torch.Tensor, name) if isinstance( method, (types.MethodDescriptorType, types.WrapperDescriptorType) ): s.add(method) return frozenset(s) """ Return if a torch object is ATen op or torch.Tensor method. """ def is_aten_op_or_tensor_method(obj): return obj in get_tensor_method() or isinstance( obj, (torch._ops.OpOverloadPacket, torch._ops.OpOverload), ) """ Main entry point for looking up the trace rule (the Dynamo variable) for a given object. E.g, the lookup result of `torch.amp.autocast_mode.autocast` is `TorchCtxManagerClassVariable`. """ def lookup(obj): if not hashable(obj): return None # Custom allow/disallow in graph takes precedence over the `torch_name_rule_map`. if id(obj) in _disallowed_function_ids: return None if is_user_defined_allowed(obj): return TorchInGraphFunctionVariable if hasattr(obj, "__wrapped__"): # TODO: Weird case, should not unwrap if it's wrapped as _VariableFunctionsClass. if not ( hasattr(obj, "__qualname__") and str(obj.__qualname__).startswith("_VariableFunctionsClass") ): obj = obj.__wrapped__ rule = get_torch_obj_rule_map().get(obj, None) if rule is None and is_aten_op_or_tensor_method(obj): return TorchInGraphFunctionVariable else: return rule