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-rw-r--r--src/mlia/cli/commands.py14
1 files changed, 7 insertions, 7 deletions
diff --git a/src/mlia/cli/commands.py b/src/mlia/cli/commands.py
index 5dd39f9..e044e1a 100644
--- a/src/mlia/cli/commands.py
+++ b/src/mlia/cli/commands.py
@@ -50,7 +50,7 @@ def all_tests(
This command runs a series of tests in order to generate a
comprehensive report/advice:
- - converts the input Keras model into TFLite format
+ - converts the input Keras model into TensorFlow Lite format
- checks the model for operator compatibility on the specified device
- applies optimizations to the model and estimates the resulting performance
on both the original and the optimized models
@@ -112,14 +112,14 @@ def operators(
:param ctx: execution context
:param target_profile: target profile identifier. Will load appropriate parameters
from the profile.json file based on this argument.
- :param model: path to the model, which can be TFLite or Keras
+ :param model: path to the model, which can be TensorFlow Lite or Keras
:param output: path to the file where the report will be saved
:param supported_ops_report: if True then generates supported operators
report in current directory and exits
Example:
Run command for the target profile ethos-u55-256 and the provided
- TFLite model and print report on the standard output
+ TensorFlow Lite model and print report on the standard output
>>> from mlia.api import ExecutionContext
>>> from mlia.cli.logging import setup_logging
@@ -161,13 +161,13 @@ def performance(
:param ctx: execution context
:param target_profile: target profile identifier. Will load appropriate parameters
from the profile.json file based on this argument.
- :param model: path to the model, which can be TFLite or Keras
+ :param model: path to the model, which can be TensorFlow Lite or Keras
:param output: path to the file where the report will be saved
:param evaluate_on: list of the backends to use for evaluation
Example:
Run command for the target profile ethos-u55-256 and
- the provided TFLite model and print report on the standard output
+ the provided TensorFlow Lite model and print report on the standard output
>>> from mlia.api import ExecutionContext
>>> from mlia.cli.logging import setup_logging
@@ -205,7 +205,7 @@ def optimization(
:param ctx: execution context
:param target: target profile identifier. Will load appropriate parameters
from the profile.json file based on this argument.
- :param model: path to the TFLite model
+ :param model: path to the TensorFlow Lite model
:param optimization_type: list of the optimization techniques separated
by comma, e.g. 'pruning,clustering'
:param optimization_target: list of the corresponding targets for
@@ -217,7 +217,7 @@ def optimization(
Example:
Run command for the target profile ethos-u55-256 and
- the provided TFLite model and print report on the standard output
+ the provided TensorFlow Lite model and print report on the standard output
>>> from mlia.cli.logging import setup_logging
>>> setup_logging()