`IPEX_LOG` (Prototype)

Introduction

IPEX_LOG provides the capability to log verbose information from Intel® Extension for PyTorch* . Please use IPEX_LOG to get the log information or trace the execution from Intel® Extension for PyTorch*. Please continue using PyTorch* macros such as TORCH_CHECK, TORCH_ERROR, etc. to get the log information from PyTorch*.

`IPEX_LOG` Definition

Log Level

The supported log levels are defined as follows, default log level is DISABLED:

log level	number	usage
DISABLED	-1	Disable the logging
TRACE	0	Reserve for further usage
DEBUG	1	Provide the whole calling stack info
INFO	2	Record calling info to other library functions and environment variable settings
WARN	3	Warn the second attempt of an action, such as memory reallocation
ERR	4	Report error in try catch
FATAL	5	Reserve for further usage

Log Component

Log component is used to specify which part from Intel® Extension for PyTorch* does this log information belong to. The supported log components are defined as follows:

log component	description
OPS	Launch SYCL, oneDNN, oneMKL operators
SYNGRAPH	Syngraph related
MEMORY	Allocate/Free memory, Allocate/Free cache
RUNTIME	Device / Queue related
ALL	All output log

Usage in C++

All the usage are defined in utils/LogUtils.h. Currently Intel® Extension for PyTorch* supports:

Simple Log

You can use IPEX_XXX_LOG, XXX represents the log level as mentioned above. There are four parameters defined for simple log:

Log component, representing which part of Intel® Extension for PyTorch* does this log belong to.
Log sub component, input an empty string(””) for general usages. For SYNGRAPH you can add any log sub componment.
Log message template format string, same as fmt_string in lib fmt, {} is used as a place holder for format args .
Log args for template format string, args numbers should be aligned with size of {}s.

Below is an example for using simple log inside abs kernel:

IPEX_INFO_LOG("OPS", "", "Add a log for inside ops {}", "abs");

Event Log

Event log is used for recording a whole event, such as an operator calculation. The whole event is identified by an unique event_id. You can also mark each step by using step_id. Use IPEX_XXX_EVENT_END() to complete the logging of the whole event. XXX represents the log level mentioned above. It will be used as the log level for all logs within one single log event.

Below is an example for using event log:

IPEX_EVENT_LOG("OPS", "", "record_avg_pool", "start", "Here record the time start with arg:{}", arg);
prepare_data();
IPEX_EVENT_LOG("OPS", "", "record_avg_pool", "data_prepare_finish", "Here record the data_prepare_finish with arg:{}", arg);
avg_pool();
IPEX_INFO_EVENT_END("OPS", "", "record_avg_pool", "finish conv", "Here record the end");

Enviornment settings

Intel® Extension for PyTorch* provides five enviornment variables for configuring log output:

IPEX_LOG_LEVEL, accept integar or string, default is -1 for DISABLED.
IPEX_LOG_COMPONENT, accept string, used for specifying the log component and sub log component you would like to log, default is “ALL”. The log component and sub log component are separated by /. You could also specify several log components, such as “OPS;MEMORY”.
IPEX_LOG_OUTPUT, accept string. If you are using IPEX_LOG_OUTPUT, than all the logs will recorded inside a file rather than the console. Example: export IPEX_LOG_OUTPUT=”./ipex.log”.
IPEX_LOG_ROTATE_SIZE, accept integar, default is 10. Can be used only with IPEX_LOG_OUTPUT, for specifing how large file will be used when rotating this log, size is MB.
IPEX_LOG_SPLIT_SIZE, accept integar, default = null. Can be used only with IPEX_LOG_OUTPUT, for specifing how large file will be used when splitting the logs, size is MB.

Usage in python

torch.xpu.set_log_level(log_level) and torch.xpu.get_log_level(), these two functions are used for getting and setting the log level.
torch.xpu.set_log_output_file_path(log_path) and torch.xpu.get_log_output_file_path(), these two functions are used for getting and setting the log output file path, once log output file path is set, logs will be recorded in file only.
torch.xpu.set_log_rotate_file_size(file size) and torch.xpu.get_log_rotate_file_size(), these two functions are used for getting and setting the log rotate file size. Can be used when output file path is set.
torch.xpu.set_log_split_file_size(file size) and torch.xpu.get_log_split_file_size(), these two functions are used for getting and setting the log split file size. Can be used when output file path is set.
torch.xpu.set_log_component(log_component), and torch.xpu.get_log_component(), these two functions are used for getting and setting the log component. The log component string are the same as defined in enviornment settings.

Replace `IPEX_SIMPLE_TRACE`

Use torch.xpu.set_log_level(0) to get logs to replace the previous usage in IPEX_SIMPLE_TRACE.

Replace `IPEX_VERBOSE`

Use torch.xpu.set_log_level(1) to get logs to replace the previous usage in IPEX_VERBOSE.

IPEX_LOG (Prototype)