def load_from_cache():
if self._cache is None or not util.get_file_size(self._cache):
return None
try:
return util.load_file(self._cache, description="calibration cache")
except:
G_LOGGER.warning("Could not read from calibration cache: {:}".format(self._cache))
return None
def load_from_cache():
if self._cache is None or not util.get_file_size(self._cache):
return None
try:
return util.load_file(self._cache,
description="calibration cache")
except Exception as err:
G_LOGGER.error(
"Could not read from calibration cache: {:}\nNote: Error was: {:}"
.format(self._cache, err))
return None
def parse(self, args):
trt_min_shapes = util.default(args_util.get(args, "trt_min_shapes"),
[])
trt_max_shapes = util.default(args_util.get(args, "trt_max_shapes"),
[])
trt_opt_shapes = util.default(args_util.get(args, "trt_opt_shapes"),
[])
default_shapes = TensorMetadata()
if self.model_args is not None:
assert hasattr(self.model_args, "input_shapes"
), "ModelArgs must be parsed before TrtConfigArgs!"
default_shapes = self.model_args.input_shapes
self.profile_dicts = parse_profile_shapes(default_shapes,
trt_min_shapes,
trt_opt_shapes,
trt_max_shapes)
workspace = args_util.get(args, "workspace")
self.workspace = int(workspace) if workspace is not None else workspace
self.tf32 = args_util.get(args, "tf32")
self.fp16 = args_util.get(args, "fp16")
self.int8 = args_util.get(args, "int8")
self.strict_types = args_util.get(args, "strict_types")
self.restricted = args_util.get(args, "restricted")
self.calibration_cache = args_util.get(args, "calibration_cache")
calib_base = args_util.get(args, "calibration_base_class")
self.calibration_base_class = None
if calib_base is not None:
calib_base = safe(assert_identifier(calib_base))
self.calibration_base_class = inline(
safe("trt.{:}", inline(calib_base)))
self.quantile = args_util.get(args, "quantile")
self.regression_cutoff = args_util.get(args, "regression_cutoff")
self.sparse_weights = args_util.get(args, "sparse_weights")
self.timing_cache = args_util.get(args, "timing_cache")
tactic_replay = args_util.get(args, "tactic_replay")
self.load_tactics = args_util.get(args, "load_tactics")
self.save_tactics = args_util.get(args, "save_tactics")
if tactic_replay is not None:
mod.warn_deprecated("--tactic-replay",
"--save-tactics or --load-tactics",
remove_in="0.35.0")
G_LOGGER.warning(
"--tactic-replay is deprecated. Use either --save-tactics or --load-tactics instead."
)
if os.path.exists(
tactic_replay) and util.get_file_size(tactic_replay) > 0:
self.load_tactics = tactic_replay
else:
self.save_tactics = tactic_replay
tactic_sources = args_util.get(args, "tactic_sources")
self.tactic_sources = None
if tactic_sources is not None:
self.tactic_sources = []
for source in tactic_sources:
source = safe(assert_identifier(source.upper()))
source_str = safe("trt.TacticSource.{:}", inline(source))
self.tactic_sources.append(inline(source_str))
self.trt_config_script = args_util.get(args, "trt_config_script")
self.trt_config_func_name = args_util.get(args, "trt_config_func_name")