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from typing import List, Set, Callable, Any, Union, Optional
from enum import Enum
import torch
from ._profiler import _ProfilerEvent, ActiveProfilerType, ProfilerActivity, ProfilerConfig
# Defined in tools/autograd/init.cpp
class DeviceType(Enum):
CPU = ...
CUDA = ...
MKLDNN = ...
OPENGL = ...
OPENCL = ...
IDEEP = ...
HIP = ...
FPGA = ...
ORT = ...
XLA = ...
MPS = ...
HPU = ...
Meta = ...
Vulkan = ...
Metal = ...
...
class ProfilerEvent:
def cpu_elapsed_us(self, other: ProfilerEvent) -> float: ...
def cpu_memory_usage(self) -> int: ...
def cuda_elapsed_us(self, other: ProfilerEvent) -> float: ...
def cuda_memory_usage(self) -> int: ...
def device(self) -> int: ...
def handle(self) -> int: ...
def has_cuda(self) -> bool: ...
def is_remote(self) -> bool: ...
def kind(self) -> int: ...
def name(self) -> str: ...
def node_id(self) -> int: ...
def sequence_nr(self) -> int: ...
def shapes(self) -> List[List[int]]: ...
def thread_id(self) -> int: ...
def flops(self) -> float: ...
def is_async(self) -> bool: ...
...
class _KinetoEvent:
def name(self) -> str: ...
def device_index(self) -> int: ...
def start_us(self) -> int: ...
def duration_us(self) -> int: ...
def is_async(self) -> bool: ...
def linked_correlation_id(self) -> int: ...
...
class _ProfilerResult:
def events(self) -> List[_KinetoEvent]: ...
def legacy_events(self) -> List[List[ProfilerEvent]]: ...
def save(self, path: str) -> None: ...
def experimental_event_tree(self) -> List[_ProfilerEvent]: ...
class SavedTensor:
...
def _enable_profiler(config: ProfilerConfig, activities: Set[ProfilerActivity]) -> None: ...
def _prepare_profiler(config: ProfilerConfig, activities: Set[ProfilerActivity]) -> None: ...
def _disable_profiler() -> _ProfilerResult: ...
def _profiler_enabled() -> bool: ...
def _add_metadata_json(key: str, value: str) -> None: ...
def _kineto_step() -> None: ...
def kineto_available() -> bool: ...
def _add_execution_graph_observer(output_file_path: str) -> bool: ...
def _remove_execution_graph_observer() -> None: ...
def _enable_execution_graph_observer() -> None: ...
def _disable_execution_graph_observer() -> None: ...
def _record_function_with_args_enter(name: str, args: List[Any]) -> torch.Tensor: ...
def _record_function_with_args_exit(handle: torch.Tensor) -> None: ...
def _supported_activities() -> Set[ProfilerActivity]: ...
def _enable_record_function(enable: bool) -> None: ...
def _set_empty_test_observer(is_global: bool, sampling_prob: float) -> None: ...
def _push_saved_tensors_default_hooks(pack_hook: Callable, unpack_hook: Callable) -> None: ...
def _pop_saved_tensors_default_hooks() -> None: ...
def _enable_profiler_legacy(config: ProfilerConfig) -> None: ...
def _disable_profiler_legacy() -> List[List[ProfilerEvent]]: ...
def _profiler_type() -> ActiveProfilerType: ...
def _saved_tensors_hooks_enable() -> None: ...
def _saved_tensors_hooks_disable(message: str) -> None: ...
def _saved_tensors_hooks_get_disabled_error_message() -> Optional[str]: ...
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