CK MLPerf inference 0.7 (image classification • tflite mobilenet v2 0.75 160 non quantized)

solution:ck-mlperf-inference-0.7-image-classification-tflite-mobilenet-v2-0.75-160-non-quantized (v1.0.0)

CK solution description  

Installation

Follow this guide to install CK. Then pull CK repositories with AI/ML workflows and components:

 ck pull repo:ai

MLPerf Inference - Image Classification - TFLite

This C++ implementation runs TFLite models for Image Classification using TFLite.

Prerequisites

Preprocess ImageNet on an x86 machine

model-tflite-mlperf-resnet*, model-tflite-mlperf-efficientnet-lite0, model-tf-and-tflite-mlperf-mobilenet* (resolution 224)

$ ck install package --tags=dataset,imagenet,preprocessed,using-opencv,side.224,full --ask

model-tf-and-tflite-mlperf-mobilenet* (resolution 192)

$ ck install package --tags=dataset,imagenet,preprocessed,using-opencv,side.192,full --ask

model-tf-and-tflite-mlperf-mobilenet* (resolution 160)

$ ck install package --tags=dataset,imagenet,preprocessed,using-opencv,side.160,full --ask

model-tf-and-tflite-mlperf-mobilenet* (resolution 128)

$ ck install package --tags=dataset,imagenet,preprocessed,using-opencv,side.128,full --ask

model-tf-and-tflite-mlperf-mobilenet* (resolution 96)

$ ck install package --tags=dataset,imagenet,preprocessed,using-opencv,side.96,full --ask

model-tflite-mlperf-efficientnet-lite1

$ ck install package --tags=dataset,imagenet,preprocessed,using-opencv,side.240,full --ask

model-tflite-mlperf-efficientnet-lite2

$ ck install package --tags=dataset,imagenet,preprocessed,using-opencv,side.260,full --ask

model-tflite-mlperf-efficientnet-lite3

$ ck install package --tags=dataset,imagenet,preprocessed,using-opencv,side.280,full --ask

model-tflite-mlperf-efficientnet-lite4

$ ck install package --tags=dataset,imagenet,preprocessed,using-opencv,side.300,full --ask

Detect ImageNet on a dev board

Copy a preprocessed ImageNet dataset onto a dev board e.g. under /datasets and register it with CK according to its resolution e.g.:

$ echo opencv-side.240 | ck detect soft --tags=dataset,imagenet,preprocessed,rgb8 \
--extra_tags=using-opencv,crop.875,full,inter.linear,side.240 \
--full_path=/datasets/dataset-imagenet-preprocessed-using-opencv-crop.875-full-inter.linear-side.240/ILSVRC2012_val_00000001.rgb8

Run once (classical CK interface)

Running this program is similar to running ck-tensorflow:program:image-classification-tflite, as described in the MLPerf Inference repo.

firefly $ ck benchmark program:image-classification-tflite-loadgen \
--speed --repetitions=1 \
--env.CK_VERBOSE=1 \
--env.CK_LOADGEN_SCENARIO=SingleStream \
--env.CK_LOADGEN_MODE=PerformanceOnly \
--env.CK_LOADGEN_DATASET_SIZE=1024 \
--env.CK_LOADGEN_BUFFER_SIZE=1024 \
--dep_add_tags.weights=model,tflite,resnet \
--dep_add_tags.library=tflite,v1.15 \
--dep_add_tags.compiler=gcc,v7 \
--dep_add_tags.images=side.224,preprocessed \
--dep_add_tags.loadgen-config-file=image-classification-tflite \
--dep_add_tags.python=v3 \
--skip_print_timers
...
------------------------------------------------------------
|            LATENCIES (in nanoseconds and fps)            |
------------------------------------------------------------
Number of queries run: 1024
Min latency:                      397952762ns  (2.51286 fps)
Median latency:                   426440993ns  (2.34499 fps)
Average latency:                  433287227ns  (2.30794 fps)
90 percentile latency:            460194271ns  (2.173 fps)
Max latency:                      679467557ns  (1.47174 fps)
------------------------------------------------------------

Explore different models

TODO

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