_utils_internal.py

import functools
import logging
import os
import sys
import tempfile
from typing import Any, Dict

import torch

log = logging.getLogger(__name__)


# this arbitrary-looking assortment of functionality is provided here
# to have a central place for overrideable behavior. The motivating
# use is the FB build environment, where this source file is replaced
# by an equivalent.

if torch._running_with_deploy():
    # __file__ is meaningless in the context of frozen torch used in torch deploy.
    # setting empty torch_parent should allow below functions to operate without crashing,
    # but it's unclear if there is a valid use case for them in the context of deploy.
    torch_parent = ""
else:
    if os.path.basename(os.path.dirname(__file__)) == "shared":
        torch_parent = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
    else:
        torch_parent = os.path.dirname(os.path.dirname(__file__))


def get_file_path(*path_components: str) -> str:
    return os.path.join(torch_parent, *path_components)


def get_file_path_2(*path_components: str) -> str:
    return os.path.join(*path_components)


def get_writable_path(path: str) -> str:
    if os.access(path, os.W_OK):
        return path
    return tempfile.mkdtemp(suffix=os.path.basename(path))


def prepare_multiprocessing_environment(path: str) -> None:
    pass


def resolve_library_path(path: str) -> str:
    return os.path.realpath(path)


def throw_abstract_impl_not_imported_error(opname, module, context):
    if module in sys.modules:
        raise NotImplementedError(
            f"{opname}: We could not find the abstract impl for this operator. "
        )
    else:
        raise NotImplementedError(
            f"{opname}: We could not find the abstract impl for this operator. "
            f"The operator specified that you may need to import the '{module}' "
            f"Python module to load the abstract impl. {context}"
        )


# Meta only, see
# https://www.internalfb.com/intern/wiki/ML_Workflow_Observability/User_Guides/Adding_instrumentation_to_your_code/
#
# This will cause an event to get logged to Scuba via the signposts API.  You
# can view samples on the API at https://fburl.com/scuba/workflow_signpost/zh9wmpqs
# we log to subsystem "torch", and the category and name you provide here.
# Each of the arguments translate into a Scuba column.  We're still figuring
# out local conventions in PyTorch, but category should be something like
# "dynamo" or "inductor", and name should be a specific string describing what
# kind of event happened.
#
# Killswitch is at
# https://www.internalfb.com/intern/justknobs/?name=pytorch%2Fsignpost#event
def signpost_event(category: str, name: str, parameters: Dict[str, Any]):
    log.info("%s %s: %r", category, name, parameters)


def log_compilation_event(metrics):
    log.info("%s", metrics)


def upload_graph(graph):
    pass


def set_pytorch_distributed_envs_from_justknobs():
    pass


def log_export_usage(**kwargs):
    pass


@functools.lru_cache(None)
def max_clock_rate():
    from triton.testing import nvsmi

    return nvsmi(["clocks.max.sm"])[0]


TEST_MASTER_ADDR = "127.0.0.1"
TEST_MASTER_PORT = 29500
# USE_GLOBAL_DEPS controls whether __init__.py tries to load
# libtorch_global_deps, see Note [Global dependencies]
USE_GLOBAL_DEPS = True
# USE_RTLD_GLOBAL_WITH_LIBTORCH controls whether __init__.py tries to load
# _C.so with RTLD_GLOBAL during the call to dlopen.
USE_RTLD_GLOBAL_WITH_LIBTORCH = False