Clarify that MLIR is now the default for the TFLite converter.
PiperOrigin-RevId: 314625466
Change-Id: I0000e7f3fe91f0024d2871a2d1e8be3af0c0cad5
diff --git a/tensorflow/lite/python/lite.py b/tensorflow/lite/python/lite.py
index f610681..d87072f 100644
--- a/tensorflow/lite/python/lite.py
+++ b/tensorflow/lite/python/lite.py
@@ -579,10 +579,9 @@
converter_kwargs.update(quant_mode.converter_flags())
if not self.experimental_new_converter:
logging.warning(
- "Please consider switching to use new converter by setting "
- "experimental_new_converter to true. "
- "Old converter (TOCO) is deprecated and flow will be switched on "
- "by default to use new converter soon.")
+ "Please consider switching to the new converter by setting "
+ "experimental_new_converter=True. "
+ "The old converter (TOCO) is deprecated.")
else:
logging.info("Using experimental converter: If you encountered a problem "
"please file a bug. You can opt-out "
@@ -875,7 +874,7 @@
training integer quantization. (default tf.float32, must be in
{tf.float32, tf.int8, tf.uint8})
experimental_new_converter: Experimental flag, subject to change. Enables
- MLIR-based conversion instead of TOCO conversion.
+ MLIR-based conversion instead of TOCO conversion. (default True)
Example usage:
@@ -1095,7 +1094,7 @@
generate input and output samples for the model. The converter can use the
dataset to evaluate different optimizations.
experimental_new_converter: Experimental flag, subject to change. Enables
- MLIR-based conversion instead of TOCO conversion.
+ MLIR-based conversion instead of TOCO conversion. (default True)
"""
def __init__(self, experimental_debug_info_func):
@@ -1256,10 +1255,9 @@
if not self.experimental_new_converter:
logging.warning(
- "Please consider switching to use new converter by setting "
- "experimental_new_converter to true. "
- "Old converter (TOCO) is deprecated and flow will be switched on "
- "by default to use new converter soon.")
+ "Please consider switching to the new converter by setting "
+ "experimental_new_converter=True. "
+ "The old converter (TOCO) is deprecated.")
else:
logging.info("Using experimental converter: If you encountered a problem "
"please file a bug. You can opt-out "
@@ -1637,7 +1635,7 @@
generate input and output samples for the model. The converter can use
the dataset to evaluate different optimizations.
experimental_new_converter: Experimental flag, subject to change.
- Enables MLIR-based conversion instead of TOCO conversion.
+ Enables MLIR-based conversion instead of TOCO conversion. (default True)
Example usage:
diff --git a/tensorflow/lite/python/lite_test.py b/tensorflow/lite/python/lite_test.py
index f7f1e3c..a20d7e8 100644
--- a/tensorflow/lite/python/lite_test.py
+++ b/tensorflow/lite/python/lite_test.py
@@ -1767,7 +1767,7 @@
log = io.BytesIO() if six.PY2 else io.StringIO()
handler = logging.StreamHandler(log)
logging.root.addHandler(handler)
- warning_message = 'Please consider switching to use new converter'
+ warning_message = 'Please consider switching to the new converter'
# Convert model and ensure model is not None.
converter = lite.TFLiteConverter.from_saved_model(saved_model_dir)
converter.experimental_new_converter = False
diff --git a/tensorflow/lite/python/tflite_convert.py b/tensorflow/lite/python/tflite_convert.py
index c7504a3..b5eb66e 100644
--- a/tensorflow/lite/python/tflite_convert.py
+++ b/tensorflow/lite/python/tflite_convert.py
@@ -13,7 +13,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
-"""Python command line interface for running TOCO."""
+"""Python command line interface for converting TF models to TFLite models."""
from __future__ import absolute_import
from __future__ import division
@@ -71,7 +71,7 @@
"QUANTIZED_UINT8 are supported.".format(flag))
-def _get_toco_converter(flags):
+def _get_tflite_converter(flags):
"""Makes a TFLiteConverter object based on the flags provided.
Args:
@@ -129,7 +129,7 @@
ValueError: Invalid flags.
"""
# Create converter.
- converter = _get_toco_converter(flags)
+ converter = _get_tflite_converter(flags)
if flags.inference_type:
converter.inference_type = _parse_inference_type(flags.inference_type,
"inference_type")
@@ -589,7 +589,7 @@
action=_ParseExperimentalNewConverter,
nargs="?",
help=("Experimental flag, subject to change. Enables MLIR-based "
- "conversion instead of TOCO conversion."))
+ "conversion instead of TOCO conversion. (default True)"))
return parser
diff --git a/tensorflow/lite/python/tflite_convert_test.py b/tensorflow/lite/python/tflite_convert_test.py
index d6a35ba..17d466d 100644
--- a/tensorflow/lite/python/tflite_convert_test.py
+++ b/tensorflow/lite/python/tflite_convert_test.py
@@ -281,11 +281,11 @@
self._input_shapes,
custom_opdefs_str))
- # Ensure --experimental_new_converter.
+ # Ensure --allow_custom_ops.
flags_str_final = ('{} --allow_custom_ops').format(flags_str)
self._run(flags_str_final, should_succeed=False)
- # Ensure --allow_custom_ops.
+ # Ensure --experimental_new_converter.
flags_str_final = ('{} --experimental_new_converter').format(flags_str)
self._run(flags_str_final, should_succeed=False)
@@ -344,15 +344,18 @@
'--output_file=/tmp/output.tflite',
]
+ # Note that when the flag parses to None, the converter uses the default
+ # value, which is True.
+
# V1 parser.
- parser = tflite_convert._get_parser(False)
+ parser = tflite_convert._get_parser(use_v2_converter=False)
parsed_args = parser.parse_args(args)
- self.assertFalse(parsed_args.experimental_new_converter)
+ self.assertIsNone(parsed_args.experimental_new_converter)
# V2 parser.
- parser = tflite_convert._get_parser(True)
+ parser = tflite_convert._get_parser(use_v2_converter=True)
parsed_args = parser.parse_args(args)
- self.assertFalse(parsed_args.experimental_new_converter)
+ self.assertIsNone(parsed_args.experimental_new_converter)
def test_experimental_new_converter(self):
args = [
@@ -362,12 +365,12 @@
]
# V1 parser.
- parser = tflite_convert._get_parser(False)
+ parser = tflite_convert._get_parser(use_v2_converter=False)
parsed_args = parser.parse_args(args)
self.assertTrue(parsed_args.experimental_new_converter)
# V2 parser.
- parser = tflite_convert._get_parser(True)
+ parser = tflite_convert._get_parser(use_v2_converter=True)
parsed_args = parser.parse_args(args)
self.assertTrue(parsed_args.experimental_new_converter)
@@ -396,12 +399,12 @@
]
# V1 parser.
- parser = tflite_convert._get_parser(False)
+ parser = tflite_convert._get_parser(use_v2_converter=False)
parsed_args = parser.parse_args(args)
self.assertFalse(parsed_args.experimental_new_converter)
# V2 parser.
- parser = tflite_convert._get_parser(True)
+ parser = tflite_convert._get_parser(use_v2_converter=True)
parsed_args = parser.parse_args(args)
self.assertFalse(parsed_args.experimental_new_converter)
