diff options
Diffstat (limited to 'src/mlia/cli')
| -rw-r--r-- | src/mlia/cli/commands.py | 14 | ||||
| -rw-r--r-- | src/mlia/cli/options.py | 10 |
2 files changed, 13 insertions, 11 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() diff --git a/src/mlia/cli/options.py b/src/mlia/cli/options.py index f7f95c0..e5e85f0 100644 --- a/src/mlia/cli/options.py +++ b/src/mlia/cli/options.py @@ -62,15 +62,17 @@ def add_multi_optimization_options(parser: argparse.ArgumentParser) -> None: def add_optional_tflite_model_options(parser: argparse.ArgumentParser) -> None: """Add optional model specific options.""" - model_group = parser.add_argument_group("TFLite model options") + model_group = parser.add_argument_group("TensorFlow Lite model options") # make model parameter optional - model_group.add_argument("model", nargs="?", help="TFLite model (optional)") + model_group.add_argument( + "model", nargs="?", help="TensorFlow Lite model (optional)" + ) def add_tflite_model_options(parser: argparse.ArgumentParser) -> None: """Add model specific options.""" - model_group = parser.add_argument_group("TFLite model options") - model_group.add_argument("model", help="TFLite model") + model_group = parser.add_argument_group("TensorFlow Lite model options") + model_group.add_argument("model", help="TensorFlow Lite model") def add_output_options(parser: argparse.ArgumentParser) -> None: |