import os
from msprof_analyze.advisor.display.prompt.base_prompt import BasePrompt
from msprof_analyze.prof_common.additional_args_manager import AdditionalArgsManager
from msprof_analyze.prof_common.file_manager import FileManager
from msprof_analyze.advisor.result.result import OptimizeResult
from msprof_analyze.advisor.result.item import OptimizeItem
from msprof_analyze.advisor.result.item import OptimizeRecord
from msprof_analyze.advisor.common.analyzer_scopes import SupportedScopes
from msprof_analyze.advisor.display.html.render import HTMLRender
from msprof_analyze.advisor.utils.utils import convert_to_int_with_exception
from msprof_analyze.prof_common.additional_args_manager import AdditionalArgsManager
class EnvironmentVariableChecker:
ENV_SUGGEST_CONDITION = {
"ASCEND_GLOBAL_LOG_LEVEL": lambda x: x != "" and convert_to_int_with_exception(x) != 3,
"HCCL_RDMA_TC": lambda x: x != "",
"HCCL_RDMA_SL": lambda x: x != "",
"ACLNN_CACHE_LIMIT": lambda x: x == "" or convert_to_int_with_exception(x) < 10000,
"HOST_CACHE_CAPACITY": lambda x: x == "" or convert_to_int_with_exception(x) == 0,
"PYTORCH_NPU_ALLOC_CONF": lambda x: isinstance(x, str) and "expandable_segments:True" not in x,
"ASCEND_LAUNCH_BLOCKING": lambda x: x != "" and convert_to_int_with_exception(x) == 1,
"HCCL_ALGO": lambda x: x != "",
}
HEADERS = ["Environment", "Value", "Description", "Suggestion"]
def __init__(self):
self.environment_info = self.read_environment_info()
self.env_suggest_csv = []
self.env_suggest_html = []
@staticmethod
def read_environment_info():
language = AdditionalArgsManager().language
environment_variable_info_path = os.path.join(
os.path.dirname(os.path.dirname(os.path.dirname(os.path.realpath(__file__)))),
"rules",
language,
"environment_variable_info.yaml"
)
return FileManager.read_yaml_file(environment_variable_info_path)
def format_env_suggest(self, data):
data = data.env_data.get('ENV_VARIABLES', {})
for env, value in data.items():
if not self.ENV_SUGGEST_CONDITION.get(env, lambda x: False)(value):
continue
desc = self.environment_info.get(env, {}).get("desc", "")
suggest = self.environment_info.get(env, {}).get("suggest", "")
self.env_suggest_csv += [
[
env,
value,
desc,
suggest,
]
]
self.env_suggest_html += [
[
env,
value,
desc.replace('\n', '<br>'),
self.environment_info.get(env, {}).get("suggest_html", suggest),
]
]
def make_record(self, result: OptimizeResult):
if not self.env_suggest_csv:
return
prompt_class = BasePrompt.get_prompt_class(self.__class__.__name__)
optimization_item = OptimizeItem(
prompt_class.PROBLEM,
prompt_class.DESCRIPTION,
[prompt_class.SUGGESTION]
)
result.add(OptimizeRecord(optimization_item))
result.add_detail(prompt_class.PROBLEM, headers=self.HEADERS)
for env_suggest in self.env_suggest_csv:
result.add_detail(prompt_class.PROBLEM, detail=env_suggest)
def make_render(self, html_render: HTMLRender):
if not self.env_suggest_html:
return
html_render.render_template(key="overall",
template_dir="templates",
template_name="environment_variable.html",
result={
"headers": self.HEADERS,
"data": self.env_suggest_html,
})