Source code for

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# SPDX-License-Identifier: Apache-2.0
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from polygraphy import mod
from import util as args_util
from import TrtLoadEngineArgs
from import BaseRunnerArgs
from import make_invocable

[docs] @mod.export() class TrtRunnerArgs(BaseRunnerArgs): """ TensorRT Inference: running inference with TensorRT. Depends on: - TrtLoadEngineArgs """ def get_name_opt_impl(self): return "TensorRT", "trt" def add_parser_args_impl(self): "--optimization-profile", help="The index of optimization profile to use for inference", type=int, default=None, dest="optimization_profile", ) "--allocation-strategy", help="The way activation memory is allocated. " "static: Pre-allocate based on the max possible size across all profiles. " "profile: Allocate what's needed for the profile to use." "runtime: Allocate what's needed for the current input shapes.", type=str, default=None, dest="allocation_strategy", choices=["static", "profile", "runtime"], ) "--weight-streaming-budget", help="The amount of GPU memory in bytes that TensorRT can use for weights at runtime. The engine must be built with weight streaming enabled. It can take on the following values: " "None or 0: Disables weight streaming at runtime. " "-1: TensorRT will decide the streaming budget automatically. " "0 to 100%%: The percentage of weights TRT will stream. 100%% will stream the maximum number of weights. " ">0B: The exact amount of streamable weights that reside on the GPU (unit suffixes are supported).", type=str, default=None, )
[docs] def parse_impl(self, args): """ Parses command-line arguments and populates the following attributes: Attributes: optimization_profile (int): The index of the optimization profile to initialize the runner with. allocation_strategy (str): The way activation memory is allocated. weight_streaming_budget (int): The weight streaming budget in bytes. weight_streaming_percent (float): The percentage of weights streamed. """ self.optimization_profile = args_util.get(args, "optimization_profile") self.allocation_strategy = args_util.get(args, "allocation_strategy") self.weight_streaming_budget = None self.weight_streaming_percent = None ws_arg = args_util.get(args, "weight_streaming_budget") if ws_arg and ws_arg.endswith("%"): percent = float(ws_arg[:-1]) assert ( 0 <= percent <= 100 ), "Invalid percentage for --weight-streaming-budget!" self.weight_streaming_percent = percent elif ws_arg: budget = args_util.parse_num_bytes(ws_arg) assert ( budget == -1 or budget >= 0 ), "Invalid amount for --weight-streaming-budget!" self.weight_streaming_budget = budget
def add_to_script_impl(self, script): script.add_import(imports=["TrtRunner"], frm="polygraphy.backend.trt") loader_name = self.arg_groups[TrtLoadEngineArgs].add_to_script(script) script.add_runner( make_invocable( "TrtRunner", loader_name, optimization_profile=self.optimization_profile, allocation_strategy=self.allocation_strategy, weight_streaming_budget=self.weight_streaming_budget, weight_streaming_percent=self.weight_streaming_percent, ) )