mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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148 lines
4.2 KiB
Python
148 lines
4.2 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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File to house data classes related to perf runs.
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Compatible with data_export.py for exporting data.
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"""
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class Data:
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"""Base class to support easier ways to interface and assign data to class."""
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def __init__(self, **kwargs):
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"""
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Simple constructor that supports optional params
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to hook to class objects.
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"""
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for key, value in kwargs.items():
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if hasattr(self, key):
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setattr(self, key, value)
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else:
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raise KeyError("Unable to assign value to PerfResult: " + key)
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def __str__(self):
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return str(self.__dict__)
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def __repr__(self):
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return str(self.__dict__)
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def get(self, key, *args, **kwargs):
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"""
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Args:
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key - Get key of the data
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default (optional) - Returns given default value if key is None.
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"""
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if len(args) > 1:
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raise RuntimeError(
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"Expected 1-2 parameters, but {} were given: {}".format(
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len(args), args[1:]))
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has_default = False
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default = None
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if "default" in kwargs and len(args) == 1:
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raise RuntimeError(
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"Expected default={} but did not expect {} in parameters".
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format(kwargs["default"], args[0]))
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if "default" in kwargs:
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has_default = True
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default = kwargs["default"]
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elif len(args) == 1:
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has_default = True
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default = args[0]
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# Used so that the class can act like a dictionary
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# Works for now instead of meta class
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return getattr(self, key, default) if has_default else getattr(
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self, key)
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def update(self, dct):
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for key, value in dct.items():
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setattr(self, key, value)
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class SessionData(Data):
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"""
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Class to store session specific results for perf runs.
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"""
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start_timestamp = None
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end_timestamp = None
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# Native NRSU specific collection
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os_properties = None
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cpu_properties = None
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gpu_properties = None
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nvidia_device_count = None
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nvidia_driver_version = None
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# OS Specific
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username = None
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hostname = None
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ip = None
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# TensorRT specific properties
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trt_change_id = None
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trt_branch = None
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commit_timestamp = None
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cuda_version = None
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cublas_version = None
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cudnn_version = None
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#trt_version = None
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class PerfResult(Data):
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"""
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Stores all relevant data from a perf run. Using class over dictionary
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for easier documentation and reference to what values are stored
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inside class. Can be more intuitive via key mappings with meta class.
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"""
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# Class attributes can be set in initialization
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start_time = None
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end_time = None
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total_time = None
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engine_build_time = None
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engine_load_time = None
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engine_file_size = None
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throughput = None
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perf_time = None
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trt_peak_cpu_mem = None
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trt_peak_gpu_mem = None
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build_engine_allocated_cpu_mem = None
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build_engine_allocated_gpu_mem = None
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deserialize_engine_allocated_cpu_mem = None
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deserialize_engine_allocated_gpu_mem = None
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execution_context_allocated_cpu_mem = None
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execution_context_allocated_gpu_mem = None
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state = None
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gpu_monitor = None
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# Session specific information
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sm_clk = None
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mem_clk = None
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gpu_idx = None
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raw_result = None
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command_str = None
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# ARIA v3 Specific
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network_name = None
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framework = None
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network_hash = None
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flags = None
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# Log File Location, Used for Reading Later
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log_file = None
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return_code = None
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