refine warnings (#2641)

* refine warnings

* fix

* further improve

* further improve

* refine warnings

* refine warnings

* workaround emb warning for jit.script

intel_extension_for_pytorch/__init__.py

@@ -2,7 +2,7 @@
 import re
 
 import torch
-import warnings
+
 
 try:
     import torchvision
@@ -128,12 +128,14 @@
 from . import _dynamo
 from . import _meta_registrations
 from ._init_on_device import OnDevice
+from .utils._logger import logger, WarningType
 
 try:
     from .cpu import tpp
 except BaseException:
-    warnings.warn(
-        "Please install transformers repo when you want to use fast_bert API."
+    logger.warn(
+        "Please install transformers repo when you want to use fast_bert API.",
+        _type=WarningType.MissingArgument,
     )
 
 from .frontend import optimize

intel_extension_for_pytorch/_inductor/compiler.py

@@ -2,9 +2,8 @@
 from torch._subclasses import FakeTensor
 from torch.utils._mode_utils import no_dispatch
 import builtins
-import warnings
 from typing import Callable, Dict, Optional, Union, List
-
+from ..utils._logger import logger, WarningType
 
 _compiler_backend = "inductor"
 
@@ -66,7 +65,10 @@ def defake(x):
                     traced_model = torch.jit.freeze(traced_model)
                 return traced_model
         except Exception:
-            warnings.warn("JIT trace failed during the IPEX compile process.")
+            logger.warning(
+                "JIT trace failed during the IPEX compile process.",
+                _type=WarningType.NotSupported,
+            )
             return model
     else:
         raise RuntimeError(

intel_extension_for_pytorch/_inductor/decomposition.py

@@ -1,14 +1,14 @@
-import logging
 import torch._decomp as decomp
 
-log = logging.getLogger(__name__)
+from ..utils._logger import logger
+
 decomposition_overrides = {}
 
 
 def register_decomposition(ops):
     for op in [ops] if callable(ops) else ops:
         if op in decomposition_overrides:
-            log.warning(f"duplicate decomp: {ops}")
+            logger.warning(f"duplicate decomp: {ops}")
     return decomp.register_decomposition(ops, decomposition_overrides)
 
 

intel_extension_for_pytorch/cpu/auto_ipex.py

@@ -1,17 +1,13 @@
 import os
 import platform
 import glob
-import logging
+from ..utils._logger import logger, WarningType
 import sys
 from argparse import ArgumentParser, REMAINDER
 from argparse import RawTextHelpFormatter
 from tempfile import mkstemp
 import uuid
 
-format_str = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
-logging.basicConfig(level=logging.INFO, format=format_str)
-logger = logging.getLogger(__name__)
-
 
 def apply_monkey_patch(program, dtype, auto_ipex_verbose, disable_ipex_graph_mode):
     # Auto apply the ipex features
@@ -213,7 +209,9 @@ def main():
                     lst_valid.append(item)
                 else:
                     logger.warning(
-                        "{} doesn't exist. Removing it from LD_PRELOAD.".format(item)
+                        f"You have set {item} into LD_PRELOAD but it doesn't exist. Removing it from LD_PRELOAD."
+                        + "please install it if you want it or remove it from LD_PRELOAD if you don't",
+                        _type=WarningType.MissingDependency,
                     )
         if len(lst_valid) > 0:
             os.environ["LD_PRELOAD"] = ":".join(lst_valid)

intel_extension_for_pytorch/cpu/graph_capture.py

@@ -7,9 +7,9 @@
 from typing import List
 
 import functools
-import logging
 import threading
 import warnings
+from ..utils._logger import logger, WarningType
 
 
 class RunMethods(IntEnum):
@@ -37,7 +37,10 @@ def compiler(gm: torch.fx.GraphModule, example_inputs: List[torch.Tensor]):
                     traced_model = torch.jit.freeze(traced_model)
                 return traced_model
             except Exception:
-                warnings.warn("JIT trace failed during the 'compiler' process.")
+                logger.warning(
+                    "JIT trace failed during the 'compiler' process.",
+                    _type=WarningType.NotSupported,
+                )
                 return gm
 
         @functools.wraps(func)
@@ -62,8 +65,9 @@ def forward(*input, **kwargs):
                             else:
                                 return self.model(*input, **kwargs)
                         if self.train:
-                            warnings.warn(
-                                "graph capture does not support training yet."
+                            logger.warning(
+                                "graph capture does not support training yet.",
+                                _type=WarningType.NotSupported,
                             )
                             self.method = RunMethods.EagerTrain
                             return func(*input, **kwargs)
@@ -89,7 +93,7 @@ def forward(*input, **kwargs):
                                     output = traced_model(*input, **kwargs)
                                     self.model = traced_model
                                     self.method = RunMethods.JIT
-                                    logging.debug("generate graph by JIT trace.")
+                                    logger.debug("generate graph by JIT trace.")
                                     return output
                             except BaseException:
                                 try:
@@ -101,11 +105,12 @@ def forward(*input, **kwargs):
                                     output = dynamo_model(*input, **kwargs)
                                     self.model = dynamo_model
                                     self.method = RunMethods.TorchDynamo
-                                    logging.debug("generate graph by TorchDynamo.")
+                                    logger.debug("generate graph by TorchDynamo.")
                                     return output
                                 except BaseException:
-                                    warnings.warn(
-                                        "Both JIT and TorchDynamo failed, fallback to original model."
+                                    logger.warning(
+                                        "Both JIT and TorchDynamo failed, fallback to original model.",
+                                        _type=WarningType.NotSupported,
                                     )
                                     self.method = RunMethods.EagerInfer
                                     torch._dynamo.reset()

intel_extension_for_pytorch/cpu/hypertune/objective.py

@@ -1,6 +1,7 @@
 # reference: https://github.com/intel/neural-compressor/blob/\
 #            15477100cef756e430c8ef8ef79729f0c80c8ce6/neural_compressor/objective.py
 import subprocess
+from ...utils._logger import logger, WarningType
 
 
 class MultiObjective(object):
@@ -39,7 +40,10 @@ def deprecate_config(self, cfg, deprecated, new, default):
         ), f"Configurations {deprecated} and {new} cannot be set at the same time."
         ret = default
         if v_deprecated != default:
-            print(f"[**Warning**] Configuration {deprecated} is deprecated by {new}.")
+            logger.warn(
+                f"[**Warning**] Configuration {deprecated} is deprecated by {new}.",
+                _type=WarningType.DeprecatedArgument,
+            )
             ret = v_deprecated
         if v_new != default:
             ret = v_new

intel_extension_for_pytorch/cpu/launch/cpu_info.py

@@ -3,6 +3,7 @@
 import platform
 import re
 import subprocess
+from ...utils._logger import WarningType
 
 # lscpu Examples
 # # The following is the parsable format, which can be fed to other
@@ -206,7 +207,7 @@ def __init__(self, logger=None, lscpu_txt=""):
                     if c.maxmhz in e_core_mhzs:
                         c.is_p_core = False
 
-    def verbose(self, level, msg):
+    def verbose(self, level, msg, warning_type=None):
         if self.logger:
             logging_fn = {
                 "warning": self.logger.warning,
@@ -215,7 +216,7 @@ def verbose(self, level, msg):
             assert (
                 level in logging_fn.keys()
             ), f"Unrecognized logging level {level} is detected. Available levels are {logging_fn.keys()}."
-            logging_fn[level](msg)
+            logging_fn[level](msg, _type=warning_type)
         else:
             print(msg)
 
@@ -264,12 +265,18 @@ def gen_pools_ondemand(
             if use_logical_cores:
                 self.verbose(
                     "warning",
-                    "Argument --use-logical-cores won't take effect when --cores-list is set.",
+                    "Argument --use-logical-cores won't take effect when --cores-list is set."
+                    + "please see https://intel.github.io/intel-extension-for-pytorch/cpu/latest/tutorials/performance_tuning/launch_script.html#launch-script-usage-guide"  # noqa: B950
+                    + "for usage guide",
+                    warning_type=WarningType.AmbiguousArgument,
                 )
             if use_e_cores:
                 self.verbose(
                     "warning",
                     "Argument --use-e-cores won't take effect when --cores-list is set.",
+                    +"please see https://intel.github.io/intel-extension-for-pytorch/cpu/latest/tutorials/performance_tuning/launch_script.html#launch-script-usage-guide"  # noqa: B950
+                    + "for usage guide",
+                    warning_type=WarningType.AmbiguousArgument,
                 )
             pool = [c for c in self.pool_all if c.cpu in cores_list]
             nodes = list(set([c.node for c in pool]))
@@ -284,6 +291,9 @@ def gen_pools_ondemand(
                         self.verbose(
                             "warning",
                             "Argument --skip-cross-node-cores cannot take effect on the designated cores. Disabled.",
+                            +"please see https://intel.github.io/intel-extension-for-pytorch/cpu/latest/tutorials/performance_tuning/launch_script.html#launch-script-usage-guide"  # noqa: B950
+                            + "for usage guide",
+                            warning_type=WarningType.WrongArgument,
                         )
                         break
         else:
@@ -302,7 +312,7 @@ def gen_pools_ondemand(
                 e_cores = [c.cpu for c in pool if not c.is_p_core]
                 if len(e_cores) > 0:
                     self.verbose(
-                        "warning",
+                        "info",
                         f"Efficient-Cores are detected ({e_cores}). Disabled for performance consideration. \
                             You can enable them with argument --use-e-cores.",
                     )
@@ -348,8 +358,11 @@ def gen_pools_ondemand(
             if skip_cross_node_cores:
                 self.verbose(
                     "warning",
-                    "Argument --skip-cross-node-cores won't take effect when both --ninstances and \
-                        --ncores-per-instance are explicitly set.",
+                    "Argument --skip-cross-node-cores won't take effect when both --ninstances and"
+                    + " --ncores-per-instance are explicitly set."
+                    + "please see https://intel.github.io/intel-extension-for-pytorch/cpu/latest/tutorials/performance_tuning/launch_script.html#launch-script-usage-guide"  # noqa: B950
+                    + "for usage guide",
+                    warning_type=WarningType.AmbiguousArgument,
                 )
         assert (
             ninstances * ncores_per_instance > 0

intel_extension_for_pytorch/cpu/launch/launch.py

@@ -8,6 +8,7 @@
 import intel_extension_for_pytorch.cpu.auto_ipex as auto_ipex
 from .launcher_distributed import DistributedTrainingLauncher
 from .launcher_multi_instances import MultiInstancesLauncher
+from ...utils._logger import logger, WarningType
 
 """
 This is a script for launching PyTorch training and inference on Intel Xeon CPU with optimal configurations.
@@ -220,53 +221,72 @@ def add_deprecated_params(parser):
 
 def process_deprecated_params(args, logger):
     if args.nproc_per_node != -1:
-        logger.warning("Argument --nproc_per_node is deprecated by --nprocs-per-node.")
+        logger.warning(
+            "Argument --nproc_per_node is deprecated by --nprocs-per-node.",
+            _type=WarningType.DeprecatedArgument,
+        )
         args.nprocs_per_node = args.nproc_per_node
     if args.more_mpi_params != "":
         logger.warning(
-            "Argument --more_mpi_params is deprecated by --extra-mpi-params."
+            "Argument --more_mpi_params is deprecated by --extra-mpi-params.",
+            _type=WarningType.DeprecatedArgument,
         )
         args.extra_mpi_params = args.more_mpi_params
     if args.ncore_per_instance != -1:
         logger.warning(
-            "Argument --ncore_per_instance is deprecated by --ncores-per-instance."
+            "Argument --ncore_per_instance is deprecated by --ncores-per-instance.",
+            _type=WarningType.DeprecatedArgument,
         )
         args.ncores_per_instance = args.ncore_per_instance
     if args.node_id != -1:
-        logger.warning("Argument --node_id is deprecated by --nodes-list.")
+        logger.warning(
+            "Argument --node_id is deprecated by --nodes-list.",
+            _type=WarningType.DeprecatedArgument,
+        )
         args.nodes_list = str(args.node_id)
     if args.core_list != "":
-        logger.warning("Argument --core_list is deprecated by --cores-list.")
+        logger.warning(
+            "Argument --core_list is deprecated by --cores-list.",
+            _type=WarningType.DeprecatedArgument,
+        )
         args.cores_list = args.core_list
     if args.logical_core_for_ccl:
         logger.warning(
-            "Argument --logical_core_for_ccl is deprecated by --logical-cores-for-ccl."
+            "Argument --logical_core_for_ccl is deprecated by --logical-cores-for-ccl.",
+            _type=WarningType.DeprecatedArgument,
         )
         args.logical_cores_for_ccl = args.logical_core_for_ccl
     if args.use_logical_core:
         logger.warning(
-            "Argument --use_logical_core is deprecated by --use-logical-cores."
+            "Argument --use_logical_core is deprecated by --use-logical-cores.",
+            _type=WarningType.DeprecatedArgument,
         )
         args.use_logical_cores = args.use_logical_core
     if args.log_path != "":
-        logger.warning("Argument --log_path is deprecated by --log-dir.")
+        logger.warning(
+            "Argument --log_path is deprecated by --log-dir.",
+            _type=WarningType.DeprecatedArgument,
+        )
         args.log_dir = args.log_path
 
     if args.multi_instance:
         logger.info(
-            "Argument --multi_instance is deprecated. Will be removed. \
-                If you are using the deprecated argument, please update it to the new one."
+            "Argument --multi_instance is deprecated. Will be removed."
+            + "If you are using the deprecated argument, please update it to the new one.",
+            _type=WarningType.DeprecatedArgument,
         )
     if args.distributed:
         logger.info(
-            "Argument --distributed is deprecated. Will be removed. \
-                If you are using the deprecated argument, please update it to the new one."
+            "Argument --distributed is deprecated. Will be removed."
+            + "If you are using the deprecated argument, please update it to the new one.",
+            _type=WarningType.DeprecatedArgument,
         )
 
     if args.enable_tcmalloc or args.enable_jemalloc or args.use_default_allocator:
         logger.warning(
-            "Arguments --enable_tcmalloc, --enable_jemalloc and --use_default_allocator \
-                are deprecated by --memory-allocator."
+            "Arguments --enable_tcmalloc, --enable_jemalloc and --use_default_allocator"
+            + "are deprecated by --memory-allocator tcmalloc/jemalloc/auto.",
+            _type=WarningType.DeprecatedArgument,
         )
         if args.use_default_allocator:
             args.memory_allocator = "default"
@@ -276,16 +296,21 @@ def process_deprecated_params(args, logger):
             args.memory_allocator = "tcmalloc"
     if args.disable_numactl:
         logger.warning(
-            "Argument --disable_numactl is deprecated by --multi-task-manager."
+            "Argument --disable_numactl is deprecated by --multi-task-manager taskset.",
+            _type=WarningType.DeprecatedArgument,
         )
         args.multi_task_manager = "taskset"
     if args.disable_taskset:
         logger.warning(
-            "Argument --disable_taskset is deprecated by --multi-task-manager."
+            "Argument --disable_taskset is deprecated by --multi-task-manager numactl.",
+            _type=WarningType.DeprecatedArgument,
         )
         args.multi_task_manager = "numactl"
     if args.disable_iomp:
-        logger.warning("Argument --disable_iomp is deprecated by --omp-runtime.")
+        logger.warning(
+            "Argument --disable_iomp is deprecated by --omp-runtime default.",
+            _type=WarningType.DeprecatedArgument,
+        )
         args.omp_runtime = "default"
 
 
@@ -383,10 +408,6 @@ def run_main_with_args(args):
     if platform.system() == "Windows":
         raise RuntimeError("Windows platform is not supported!!!")
 
-    format_str = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
-    logging.basicConfig(level=logging.INFO, format=format_str)
-    logger = logging.getLogger(__name__)
-
     launcher_distributed = DistributedTrainingLauncher(logger)
     launcher_multi_instances = MultiInstancesLauncher(logger)