nvidia--tensorrt/samples/trtexec/profiler.py

#!/usr/bin/env python3
#
# SPDX-FileCopyrightText: Copyright (c) 1993-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

"""
Print a trtexec profile from a JSON file

Given a JSON file containing a trtexec profile,
this program prints the profile in CSV table format.
Each row represents a layer in the profile.

The output format can be optionally converted to a
format suitable for GNUPlot.
"""

import sys
import json
import argparse
import prn_utils as pu


allFeatures = ["name", "timeMs", "averageMs", "percentage"]

defaultFeatures = ",".join(allFeatures)

descriptions = ["layer name", "total layer time", "average layer time", "percentage of total time"]

featuresDescription = pu.combineDescriptions("Features are (times in ms):", allFeatures, descriptions)


def hasNames(features):
    """Check if the name is included in the set"""

    return "name" in features


def totalData(features, profile):
    """Add row at the bottom with the total"""

    accumulator = {}
    for f in features:
        accumulator[f] = 0
    accumulator["name"] = "total"

    for row in profile:
        for f in features:
            if f in row and not f == "name":
                accumulator[f] += row[f]

    return accumulator


def findAndRemove(profile, name):
    """Find named row in profile and remove"""

    for r in range(len(profile)):
        if profile[r]["name"] == name:
            row = profile[r]
            del profile[r]
            return row

    return None


def refName(name):
    """Add prefix ref to name"""

    return "ref" + name[0].capitalize() + name[1:]


def refFeatures(names):
    """Add prefix ref to features names"""

    refNames = []
    for name in names:
        refNames.append(refName(name))
    return refNames


def mergeHeaders(features, skipFirst=True):
    """Duplicate feature names for reference and target profile"""

    if skipFirst:
        return [features[0]] + refFeatures(features[1:]) + features[1:] + ["% difference"]
    return refFeatures(features) + features + ["% difference"]


def addReference(row, reference):
    """Add reference results to results dictionary"""

    for k, v in reference.items():
        if k == "name":
            if k in row:
                continue
        else:
            k = refName(k)
        row[k] = v


def mergeRow(reference, profile, diff):
    """Merge reference and target profile results into a single row"""

    row = {}
    if profile:
        row = profile
    if reference:
        addReference(row, reference)
    if diff:
        row["% difference"] = diff

    return row


def alignData(reference, profile, threshold):
    """Align and merge reference and target profiles"""

    alignedData = []
    for ref in reference:
        prof = findAndRemove(profile, ref["name"])

        if prof:
            diff = (prof["averageMs"] / ref["averageMs"] - 1) * 100
            if abs(diff) >= threshold:
                alignedData.append(mergeRow(ref, prof, diff))
        else:
            alignedData.append(mergeRow(ref, None, None))

    for prof in profile:
        alignedData.append(mergeRow(None, prof, None))

    return alignedData


def main():
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument(
        "--features",
        metavar="F[,F]*",
        default=defaultFeatures,
        help="Comma separated list of features to print. " + featuresDescription,
    )
    parser.add_argument("--total", action="store_true", help="Add total time row.")
    parser.add_argument("--gp", action="store_true", help="Print GNUPlot format.")
    parser.add_argument("--no-header", action="store_true", help="Omit the header row.")
    parser.add_argument("--threshold", metavar="T", default=0.0, type=float, help="Threshold of percentage difference.")
    parser.add_argument("--reference", metavar="R", help="Reference profile file name.")
    parser.add_argument("name", metavar="filename", help="Profile file.")
    args = parser.parse_args()

    global allFeatures
    features = args.features.split(",")
    for f in features:
        if not f in allFeatures:
            print("Feature {} not recognized".format(f))
            return

    count = args.gp and not hasNames(features)

    profile = None
    reference = None
    referenceCount = 0

    with open(args.name) as f:
        profile = json.load(f)
        profileCount = profile[0]["count"]
        profile = profile[1:]

    if args.reference:
        with open(args.reference) as f:
            reference = json.load(f)
            referenceCount = reference[0]["count"]
            reference = reference[1:]
        allFeatures = mergeHeaders(allFeatures)
        features = mergeHeaders(features, hasNames(features))

    if not args.no_header:
        if reference:
            comment = "#" if args.gp else ""
            print(comment + "reference count: {} - profile count: {}".format(referenceCount, profileCount))
        pu.printHeader(allFeatures, features, args.gp, count)

    if reference:
        profile = alignData(reference, profile, args.threshold)

    if args.total:
        profile.append(totalData(allFeatures, profile))
        if reference:
            total = profile[len(profile) - 1]
            total["% difference"] = (total["averageMs"] / total["refAverageMs"] - 1) * 100

    profile = pu.filterData(profile, allFeatures, features)

    pu.printCsv(profile, count)


if __name__ == "__main__":
    sys.exit(main())