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TFLite --int8 'flatbuffers==1.12' fix #6216

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Merged
glenn-jocher merged 3 commits into from
Jan 5, 2022
Merged

TFLite --int8 'flatbuffers==1.12' fix #6216

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1fa6f59
TFLite `--int8` 'flatbuffers==1.12' fix
glenn-jocher Jan 5, 2022
c29f828
Update export.py
glenn-jocher Jan 5, 2022
5428ed0
Update export.py
glenn-jocher Jan 5, 2022
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4 changes: 2 additions & 2 deletions export.py
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Original file line number Diff line number Diff line change
Expand Up @@ -277,8 +277,6 @@ def export_tflite(keras_model, im, file, int8, data, ncalib, prefix=colorstr('Te
try:
import tensorflow as tf

from models.tf import representative_dataset_gen

LOGGER.info(f'\n{prefix} starting export with tensorflow {tf.__version__}...')
batch_size, ch, *imgsz = list(im.shape) # BCHW
f = str(file).replace('.pt', '-fp16.tflite')
Expand All @@ -288,6 +286,8 @@ def export_tflite(keras_model, im, file, int8, data, ncalib, prefix=colorstr('Te
converter.target_spec.supported_types = [tf.float16]
converter.optimizations = [tf.lite.Optimize.DEFAULT]
if int8:
from models.tf import representative_dataset_gen
check_requirements(('flatbuffers==1.12',)) # https://github.com/ultralytics/yolov5/issues/5707
dataset = LoadImages(check_dataset(data)['train'], img_size=imgsz, auto=False) # representative data
converter.representative_dataset = lambda: representative_dataset_gen(dataset, ncalib)
converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
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