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TFLite --int8 'flatbuffers==1.12' fix 2 #6217

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Jan 5, 2022
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TFLite --int8 'flatbuffers==1.12' fix 2 #6217

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5dc1707
TFLite `--int8` 'flatbuffers==1.12' fix 2
glenn-jocher Jan 5, 2022
36064ef
Update export.py
glenn-jocher Jan 5, 2022
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3 changes: 2 additions & 1 deletion export.py
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Original file line number Diff line number Diff line change
Expand Up @@ -287,7 +287,6 @@ def export_tflite(keras_model, im, file, int8, data, ncalib, prefix=colorstr('Te
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]
Expand Down Expand Up @@ -435,6 +434,8 @@ def run(data=ROOT / 'data/coco128.yaml', # 'dataset.yaml path'
# TensorFlow Exports
if any(tf_exports):
pb, tflite, edgetpu, tfjs = tf_exports[1:]
if (tflite or edgetpu) and int8: # TFLite --int8 bug https://github.com/ultralytics/yolov5/issues/5707
check_requirements(('flatbuffers==1.12',)) # required before `import tensorflow`
assert not (tflite and tfjs), 'TFLite and TF.js models must be exported separately, please pass only one type.'
model = export_saved_model(model, im, file, dynamic, tf_nms=nms or agnostic_nms or tfjs,
agnostic_nms=agnostic_nms or tfjs, topk_per_class=topk_per_class, topk_all=topk_all,
Expand Down