SYMBOL INDEX (262 symbols across 17 files)

FILE: module/comfy_trace/model_base.py
  class BaseModelApplyModelModule (line 21) | class BaseModelApplyModelModule(torch.nn.Module):
    method __init__ (line 22) | def __init__(self, func, module):
    method forward (line 27) | def forward(
  class BaseModelApplyModelModuleFactory (line 54) | class BaseModelApplyModelModuleFactory(ModuleFactory):
    method __init__ (line 64) | def __init__(self, callable, kwargs) -> None:
    method gen_converted_kwargs (line 72) | def gen_converted_kwargs(self):
    method gen_cache_key (line 107) | def gen_cache_key(self):
    method converted_module_context (line 132) | def converted_module_context(self):
  class UNetModelModule (line 153) | class UNetModelModule(torch.nn.Module):
    method __init__ (line 154) | def __init__(self, module):
    method forward (line 158) | def forward(
  class UNetModelModuleFactory (line 183) | class UNetModelModuleFactory(ModuleFactory):
    method __init__ (line 192) | def __init__(self, diffusion_model, unet_config, **kwargs) -> None:
    method gen_converted_kwargs (line 200) | def gen_converted_kwargs(self):
    method gen_cache_key (line 235) | def gen_cache_key(self):
    method converted_module_context (line 260) | def converted_module_context(self):

FILE: module/comfy_trace/nodes_freelunch.py
  function Fourier_filter (line 8) | def Fourier_filter(x, threshold: int, scale: float):
  class FreeU (line 29) | class FreeU(torch.nn.Module):
    method __init__ (line 30) | def __init__(self, scale_map):
    method forward (line 34) | def forward(self, h, hsp, parameter, transformer_options):
    method from_closure (line 42) | def from_closure(closure, transformer_options):
    method gen_cache_key (line 50) | def gen_cache_key(self):
  class FreeU_V2 (line 54) | class FreeU_V2(torch.nn.Module):
    method __init__ (line 55) | def __init__(self, scale_map):
    method forward (line 59) | def forward(self, h, hsp, parameter, transformer_options):
    method from_closure (line 79) | def from_closure(closure, transformer_options):
    method gen_cache_key (line 89) | def gen_cache_key(self):

FILE: module/comfy_trace/nodes_model_downscale.py
  class PatchModelAddDownscale_input_block_patch (line 5) | class PatchModelAddDownscale_input_block_patch(torch.nn.Module):
    method __init__ (line 6) | def __init__(
    method forward (line 23) | def forward(self, h, parameter, transformer_options):
    method from_closure (line 36) | def from_closure(closure, transformer_options):
    method gen_cache_key (line 54) | def gen_cache_key(self):
  class PatchModelAddDownscale_output_block_patch (line 67) | class PatchModelAddDownscale_output_block_patch(torch.nn.Module):
    method __init__ (line 68) | def __init__(self, upscale_method):
    method forward (line 72) | def forward(self, h, hsp, parameter, transformer_options):
    method from_closure (line 84) | def from_closure(closure, transformer_options):
    method gen_cache_key (line 93) | def gen_cache_key(self):

FILE: module/comfy_trace/openaimodel.py
  class ForwardTimestepEmbedModule (line 15) | class ForwardTimestepEmbedModule(th.nn.Module):
    method __init__ (line 16) | def __init__(self, ts, transformer_options={}, num_video_frames=None):
    method forward (line 22) | def forward(
  class PatchUNetModel (line 46) | class PatchUNetModel(UNetModel):
    method cast_from (line 48) | def cast_from(other):
    method cast_to_base_model (line 56) | def cast_to_base_model(self):
    method patch_init (line 61) | def patch_init(self):
    method patch_deinit (line 72) | def patch_deinit(self):
    method set_patch_module (line 77) | def set_patch_module(self, patch_module):
    method forward (line 102) | def forward(

FILE: module/comfy_trace/sd.py
  class VAEDecodeModule (line 4) | class VAEDecodeModule(torch.nn.Module):
    method __init__ (line 5) | def __init__(self, module, decode):
    method forward (line 10) | def forward(self, samples):

FILE: module/comfy_trace_utilities.py
  function hash_arg (line 7) | def hash_arg(arg):
  class ModuleWrapper (line 25) | class ModuleWrapper(torch.nn.Module):
    method __init__ (line 26) | def __init__(self, module):
    method forward (line 30) | def forward(self, *args, **kwargs):
  class ModuleFactory (line 34) | class ModuleFactory:
    method __init__ (line 35) | def __init__(self, callable, kwargs) -> None:
    method gen_converted_kwargs (line 40) | def gen_converted_kwargs(self):
    method get_converted_kwargs (line 43) | def get_converted_kwargs(self):
    method gen_cache_key (line 46) | def gen_cache_key(self):
    method converted_module_context (line 53) | def converted_module_context(self):
    method load_state_dict_to_module (line 56) | def load_state_dict_to_module(self, script_module):
  class TracerWithCache (line 64) | class TracerWithCache:
    method get_traced_module (line 68) | def get_traced_module(module_factory: ModuleFactory, device=None):

FILE: module/controlnet_tensorrt.py
  class CallableTensorRTEngineWrapperDynamicShapeControlNet (line 4) | class CallableTensorRTEngineWrapperDynamicShapeControlNet(
    method gen_onnx_args (line 9) | def gen_onnx_args(self, kwargs, module=None):
    method gen_tensorrt_args (line 27) | def gen_tensorrt_args(self, kwargs):
    method gen_tensorrt_args_profile (line 38) | def gen_tensorrt_args_profile(self, input_shape_info):
    method gen_onnx_outputs (line 60) | def gen_onnx_outputs(self, module):
    method gen_tensorrt_outputs (line 67) | def gen_tensorrt_outputs(self, output_map):

FILE: module/model_base_tensorrt.py
  class CallableTensorRTEngineWrapperDynamicShapeBaseModelApplyModel (line 6) | class CallableTensorRTEngineWrapperDynamicShapeBaseModelApplyModel(
    method gen_onnx_args (line 18) | def gen_onnx_args(self, kwargs, module=None):
    method gen_tensorrt_args (line 54) | def gen_tensorrt_args(self, kwargs):
    method gen_tensorrt_args_profile (line 73) | def gen_tensorrt_args_profile(self, input_shape_info):

FILE: module/onnx_module_refit.py
  class ParamsDictGenMapValue (line 13) | class ParamsDictGenMapValue:
  function make_module_onnx_tensor_gen_map_by_params_dict (line 18) | def make_module_onnx_tensor_gen_map_by_params_dict(
  function make_module_onnx_tensor_gen_map_by_onnx_model (line 64) | def make_module_onnx_tensor_gen_map_by_onnx_model(
  function make_params_dict_by_module (line 73) | def make_params_dict_by_module(
  function make_constant_params_dict_by_onnx_model (line 95) | def make_constant_params_dict_by_onnx_model(

FILE: module/openaimodel_tensorrt.py
  class TensorRTEngineBlockContext (line 21) | class TensorRTEngineBlockContext:
    method dump_input_profile_info (line 29) | def dump_input_profile_info(self):
  class CallableTensorRTEngineWrapperDynamicShapeForwardTimestep (line 36) | class CallableTensorRTEngineWrapperDynamicShapeForwardTimestep(
    method gen_onnx_args (line 48) | def gen_onnx_args(self, kwargs, module=None):
    method gen_tensorrt_args (line 66) | def gen_tensorrt_args(self, kwargs):
    method gen_tensorrt_args_profile (line 77) | def gen_tensorrt_args_profile(self, input_shape_info):
  function hook_forward_timestep_embed (line 100) | def hook_forward_timestep_embed(
  function do_hook_forward_timestep_embed (line 138) | def do_hook_forward_timestep_embed():
  function undo_hook_forward_timestep_embed (line 144) | def undo_hook_forward_timestep_embed():
  class CallableTensorRTEngineWrapperDynamicShapeUNetModelForward (line 150) | class CallableTensorRTEngineWrapperDynamicShapeUNetModelForward(
    method gen_onnx_args (line 161) | def gen_onnx_args(self, kwargs, module=None):
    method gen_tensorrt_args (line 197) | def gen_tensorrt_args(self, kwargs):
    method gen_tensorrt_args_profile (line 216) | def gen_tensorrt_args_profile(self, input_shape_info):

FILE: module/patched_onnx_export/utils_2_4_0.py
  function is_in_onnx_export (line 72) | def is_in_onnx_export() -> bool:
  function select_model_mode_for_export (line 84) | def select_model_mode_for_export(model, mode: _C_onnx.TrainingMode):
  function disable_apex_o2_state_dict_hook (line 133) | def disable_apex_o2_state_dict_hook(
  function setup_onnx_logging (line 167) | def setup_onnx_logging(verbose: bool):
  function exporter_context (line 180) | def exporter_context(model, mode: _C_onnx.TrainingMode, verbose: bool):
  function export (line 191) | def export(
  function _is_constant_tensor_list (line 573) | def _is_constant_tensor_list(node):
  function _split_tensor_list_constants (line 588) | def _split_tensor_list_constants(g, block):
  function _optimize_graph (line 611) | def _optimize_graph(
  function warn_on_static_input_change (line 754) | def warn_on_static_input_change(input_states):
  function _resolve_args_by_export_type (line 784) | def _resolve_args_by_export_type(arg_name, arg_value, operator_export_ty...
  function _decide_keep_init_as_input (line 801) | def _decide_keep_init_as_input(
  function _decide_add_node_names (line 845) | def _decide_add_node_names(add_node_names, operator_export_type):
  function _decide_constant_folding (line 852) | def _decide_constant_folding(do_constant_folding, operator_export_type, ...
  function _signature (line 871) | def _signature(model) -> inspect.Signature:
  function _decide_input_format (line 879) | def _decide_input_format(model, args):
  function _trace (line 918) | def _trace(func, args, operator_export_type, return_outs=False):
  function _trace_and_get_graph_from_model (line 939) | def _trace_and_get_graph_from_model(model, args):
  function _get_param_count_list (line 970) | def _get_param_count_list(method_graph, args_params):
  function _check_flatten_did_not_remove (line 983) | def _check_flatten_did_not_remove(original, jit_flattened):
  function _create_jit_graph (line 1008) | def _create_jit_graph(
  function _get_named_param_dict (line 1060) | def _get_named_param_dict(graph, params):
  function _get_example_outputs (line 1068) | def _get_example_outputs(model, args):
  function unpack_quantized_tensor (line 1093) | def unpack_quantized_tensor(value, cast_onnx_accepted=True):
  function _pre_trace_quant_model (line 1114) | def _pre_trace_quant_model(model, args):
  function _model_to_graph (line 1128) | def _model_to_graph(
  function export_to_pretty_string (line 1274) | def export_to_pretty_string(
  function unconvertible_ops (line 1351) | def unconvertible_ops(
  function _setup_trace_module_map (line 1420) | def _setup_trace_module_map(
  function _reset_trace_module_map (line 1498) | def _reset_trace_module_map():
  function _get_module_attributes (line 1504) | def _get_module_attributes(module):
  function _export (line 1529) | def _export(
  function _apply_friendly_debug_names (line 1752) | def _apply_friendly_debug_names(graph, params):
  function _set_input_and_output_names (line 1765) | def _set_input_and_output_names(graph, input_names, output_names):
  function _run_symbolic_method (line 1798) | def _run_symbolic_method(g, op_name, symbolic_fn, args):
  function _add_block (line 1824) | def _add_block(node: _C.Node) -> _C.Block:
  function _add_input_to_block (line 1829) | def _add_input_to_block(block: _C.Block):
  function _add_output_to_block (line 1834) | def _add_output_to_block(block: _C.Block, value: _C.Value) -> int:
  function _should_aten_fallback (line 1839) | def _should_aten_fallback(
  function _need_symbolic_context (line 1870) | def _need_symbolic_context(symbolic_fn: Callable) -> bool:
  function _symbolic_context_handler (line 1886) | def _symbolic_context_handler(symbolic_fn: Callable) -> Callable:
  function _get_aten_op_overload_name (line 1911) | def _get_aten_op_overload_name(n: _C.Node) -> str:
  function _run_symbolic_function (line 1920) | def _run_symbolic_function(
  function _verify_custom_op_name (line 2045) | def _verify_custom_op_name(symbolic_name: str):
  function register_custom_op_symbolic (line 2062) | def register_custom_op_symbolic(
  function unregister_custom_op_symbolic (line 2099) | def unregister_custom_op_symbolic(symbolic_name: str, opset_version: int):
  function _validate_dynamic_axes (line 2118) | def _validate_dynamic_axes(dynamic_axes, model, input_names, output_names):
  function model_signature (line 2162) | def model_signature(model: Union[torch.nn.Module, Callable]) -> inspect....

FILE: module/sd_tensorrt.py
  class CallableTensorRTEngineWrapperDynamicShapeVAEDecode (line 4) | class CallableTensorRTEngineWrapperDynamicShapeVAEDecode(CallableTensorR...
    method gen_onnx_args (line 9) | def gen_onnx_args(self, kwargs, module=None):
    method gen_tensorrt_args (line 24) | def gen_tensorrt_args(self, kwargs):
    method gen_tensorrt_args_profile (line 35) | def gen_tensorrt_args_profile(self, input_shape_info):

FILE: module/sfast_pipeline_compiler.py
  class TracedModuleCacheItem (line 20) | class TracedModuleCacheItem:
  class LazyTraceModule (line 26) | class LazyTraceModule:
    method __init__ (line 29) | def __init__(self, config=None, patch_id=None, **kwargs_) -> None:
    method ts_compiler (line 43) | def ts_compiler(
    method __call__ (line 60) | def __call__(self, model_function, /, **kwargs):
    method to_empty (line 109) | def to_empty(self):
  function build_lazy_trace_module (line 115) | def build_lazy_trace_module(config, device, patch_id):

FILE: module/tensorrt_utilities.py
  class TQDMProgressMonitor (line 67) | class TQDMProgressMonitor(trt.IProgressMonitor):
    method __init__ (line 68) | def __init__(self):
    method phase_start (line 74) | def phase_start(self, phase_name, parent_phase, num_steps):
    method phase_finish (line 100) | def phase_finish(self, phase_name):
    method step_complete (line 126) | def step_complete(self, phase_name, step):
  class Engine (line 138) | class Engine:
    method __init__ (line 139) | def __init__(self, engine_path, enable_cuda_graph=False):
    method __del__ (line 156) | def __del__(self):
    method refit_simple (line 162) | def refit_simple(self, onnx_model):
    method refit_from_dict (line 175) | def refit_from_dict(
    method build (line 232) | def build(
    method save_engine (line 340) | def save_engine(self):
    method load (line 345) | def load(self):
    method update_binding_set (line 356) | def update_binding_set(self):
    method offload (line 361) | def offload(self, offload_context_only=False):
    method is_weight_streaming_engine (line 386) | def is_weight_streaming_engine(self):
    method activate (line 389) | def activate(
    method get_device_memory_size (line 416) | def get_device_memory_size(self):
    method allocate_buffers (line 427) | def allocate_buffers(
    method release_buffers (line 462) | def release_buffers(self):
    method infer (line 465) | def infer(
    method set_static_dict_input (line 516) | def set_static_dict_input(self, feed_dict):
    method __str__ (line 524) | def __str__(self):

FILE: module/tensorrt_wrapper.py
  class TensorRTEngineConfig (line 36) | class TensorRTEngineConfig:
  class CallableTensorRTEngineWrapper (line 45) | class CallableTensorRTEngineWrapper:
    method __init__ (line 46) | def __init__(self, tensorrt_context, identification) -> None:
    method gen_onnx_args (line 63) | def gen_onnx_args(self, kwargs, module=None):
    method gen_onnx_outputs (line 73) | def gen_onnx_outputs(self, module):
    method gen_tensorrt_args (line 76) | def gen_tensorrt_args(self, kwargs):
    method gen_tensorrt_args_profile (line 86) | def gen_tensorrt_args_profile(self, input_shape_info):
    method gen_tensorrt_outputs (line 89) | def gen_tensorrt_outputs(self, output):
    method is_profile_compatible (line 92) | def is_profile_compatible(self, input_profile_info, input_shape_info):
    method __call__ (line 108) | def __call__(self, module: torch.nn.Module, /, **kwargs: Any) -> Any:
  class TensorRTEngineComfyModelPatcherWrapper (line 337) | class TensorRTEngineComfyModelPatcherWrapper(comfy.model_patcher.ModelPa...
    method patch_model_lowvram (line 338) | def patch_model_lowvram(self, device_to=None, *arg, **kwargs):
    method patch_model (line 341) | def patch_model(self, device_to=None, *arg, **kwargs):
    method unpatch_model (line 351) | def unpatch_model(self, device_to=None, *arg, **kwargs):
  function get_additional_keep_models (line 357) | def get_additional_keep_models():
  class TensorRTEngineContext (line 368) | class TensorRTEngineContext:
  function get_key_hash (line 395) | def get_key_hash(key):
  function get_cache_path (line 399) | def get_cache_path(key, dir_name):
  function get_engine_path (line 407) | def get_engine_path(key):
  function get_engine_with_cache (line 411) | def get_engine_with_cache(key):
  function gen_engine (line 418) | def gen_engine(key, onnx_model, input_profile, dtype, enable_weight_stre...
  function get_refit_info_cache (line 434) | def get_refit_info_cache(key):
  function gen_refit_info (line 441) | def gen_refit_info(key):
  class TorchTensorRTRefitInfo (line 446) | class TorchTensorRTRefitInfo:
    method __init__ (line 447) | def __init__(self, info_path) -> None:
    method save (line 452) | def save(self):
    method load (line 459) | def load(self):
  function sha256sum_state_dict (line 467) | def sha256sum_state_dict(state_dict: dict[str, torch.Tensor]):

FILE: node.py
  function is_cuda_malloc_async (line 7) | def is_cuda_malloc_async():
  function gen_stable_fast_config (line 11) | def gen_stable_fast_config():
  class StableFastPatch (line 40) | class StableFastPatch:
    method __init__ (line 41) | def __init__(self, model, config):
    method __deepcopy__ (line 46) | def __deepcopy__(self, memo=None):
    method __call__ (line 49) | def __call__(self, model_function, params):
    method to (line 69) | def to(self, device):
  class ApplyStableFastUnet (line 85) | class ApplyStableFastUnet:
    method INPUT_TYPES (line 87) | def INPUT_TYPES(s):
    method apply_stable_fast (line 100) | def apply_stable_fast(self, model, enable_cuda_graph):

FILE: tensorrt_node.py
  class BlockTensorRTPatch (line 27) | class BlockTensorRTPatch(torch.nn.Module):
    method __init__ (line 28) | def __init__(self, config, model_config, model_sampling_type):
    method __deepcopy__ (line 38) | def __deepcopy__(self, memo=None):
    method dtype (line 42) | def dtype(self):
    method warmup (line 45) | def warmup(
    method __call__ (line 103) | def __call__(
    method to (line 160) | def to(self, device):
  class UnetTensorRTPatch (line 166) | class UnetTensorRTPatch(BlockTensorRTPatch):
    method __init__ (line 167) | def __init__(self, *args):
    method __call__ (line 171) | def __call__(
  class ModelUnetFunctionWrapper (line 237) | class ModelUnetFunctionWrapper:
    method __init__ (line 238) | def __init__(self, patch):
    method __deepcopy__ (line 241) | def __deepcopy__(self, memo=None):
    method __call__ (line 244) | def __call__(self, model_function, params):
  function hook_memory_required (line 260) | def hook_memory_required(input_shape):
  class TensorRTEngineOriginModelPatcherWrapper_BlockPatch (line 264) | class TensorRTEngineOriginModelPatcherWrapper_BlockPatch(
    method cast_from (line 268) | def cast_from(other):
    method patch_init (line 275) | def patch_init(self, tensorrt_module_patch):
    method patch_deinit (line 278) | def patch_deinit(self):
    method cast_to_base_model (line 282) | def cast_to_base_model(self):
    method patch_model (line 287) | def patch_model(self, device_to=None, *arg, **kwargs):
    method __del__ (line 306) | def __del__(self):
  class TensorRTEngineOriginModelPatcherWrapper_UnetPatch (line 310) | class TensorRTEngineOriginModelPatcherWrapper_UnetPatch(
    method cast_from (line 314) | def cast_from(other):
    method patch_init (line 321) | def patch_init(self, tensorrt_module_patch):
    method patch_deinit (line 324) | def patch_deinit(self):
    method cast_to_base_model (line 328) | def cast_to_base_model(self):
    method model_size (line 333) | def model_size(self):
    method patch_model_lowvram (line 341) | def patch_model_lowvram(
    method patch_model (line 366) | def patch_model(self, device_to=None, *arg, **kwargs):
    method __del__ (line 374) | def __del__(self):
  class PatchType (line 378) | class PatchType(enum.Enum):
  class ApplyTensorRTUnet (line 383) | class ApplyTensorRTUnet:
    method INPUT_TYPES (line 385) | def INPUT_TYPES(s):
    method apply_tensorrt (line 410) | def apply_tensorrt(
  class VAEDecodeTensorRTPatch (line 442) | class VAEDecodeTensorRTPatch:
    method __init__ (line 443) | def __init__(self, model, config):
    method warmup (line 450) | def warmup(self, samples_in):
    method __call__ (line 464) | def __call__(self, samples_in):
  class ApplyTensorRTVaeDecoder (line 494) | class ApplyTensorRTVaeDecoder:
    method INPUT_TYPES (line 496) | def INPUT_TYPES(s):
    method apply_tensorrt (line 517) | def apply_tensorrt(
  class ControlNetTensorRTPatch (line 537) | class ControlNetTensorRTPatch:
    method __init__ (line 538) | def __init__(self, control_model, config):
    method state_dict (line 545) | def state_dict(self):
    method to (line 548) | def to(self, device):
    method warmup (line 551) | def warmup(self, x, hint, timesteps, context, y=None):
    method __call__ (line 589) | def __call__(self, x, hint, timesteps, context, y=None):
  class ApplyTensorRTControlNet (line 610) | class ApplyTensorRTControlNet:
    method INPUT_TYPES (line 612) | def INPUT_TYPES(s):
    method apply_tensorrt (line 634) | def apply_tensorrt(