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authorDmitrii Agibov <dmitrii.agibov@arm.com>2022-10-07 11:39:37 +0100
committerDmitrii Agibov <dmitrii.agibov@arm.com>2022-10-07 11:40:21 +0100
commit3083f7ee68ce08147db08fca2474e5f4712fc8d7 (patch)
treec52e668c01a6a1041c08190e52a15944fd65b453 /src/mlia/devices
parentbb7fb49484bb3687041061b2fdbbfae3959be54b (diff)
downloadmlia-3083f7ee68ce08147db08fca2474e5f4712fc8d7.tar.gz
MLIA-607 Update documentation and comments
Use "TensorFlow Lite" instead of "TFLite" in documentation and comments Change-Id: Ie4450d72fb2e5261d152d72ab8bd94c3da914c46
Diffstat (limited to 'src/mlia/devices')
-rw-r--r--src/mlia/devices/ethosu/advice_generation.py2
-rw-r--r--src/mlia/devices/ethosu/advisor.py4
2 files changed, 3 insertions, 3 deletions
diff --git a/src/mlia/devices/ethosu/advice_generation.py b/src/mlia/devices/ethosu/advice_generation.py
index dee1650..8a38d2c 100644
--- a/src/mlia/devices/ethosu/advice_generation.py
+++ b/src/mlia/devices/ethosu/advice_generation.py
@@ -196,7 +196,7 @@ class EthosUStaticAdviceProducer(ContextAwareAdviceProducer):
Advice(
[
"For better performance, make sure that all the operators "
- "of your final TFLite model are supported by the NPU.",
+ "of your final TensorFlow Lite model are supported by the NPU.",
]
+ self.context.action_resolver.operator_compatibility_details()
)
diff --git a/src/mlia/devices/ethosu/advisor.py b/src/mlia/devices/ethosu/advisor.py
index be58de7..2c25f6c 100644
--- a/src/mlia/devices/ethosu/advisor.py
+++ b/src/mlia/devices/ethosu/advisor.py
@@ -52,10 +52,10 @@ class EthosUInferenceAdvisor(DefaultInferenceAdvisor):
# Performance and optimization are mutually exclusive.
# Decide which one to use (taking into account the model format).
if is_tflite_model(model):
- # TFLite models do not support optimization (only performance)!
+ # TensorFlow Lite models do not support optimization (only performance)!
if context.advice_category == AdviceCategory.OPTIMIZATION:
raise Exception(
- "Command 'optimization' is not supported for TFLite files."
+ "Command 'optimization' is not supported for TensorFlow Lite files."
)
if AdviceCategory.PERFORMANCE in context.advice_category:
collectors.append(EthosUPerformance(model, device, backends))