From 49efec606f4886ae477c4c30b4157beec92f5b3e Mon Sep 17 00:00:00 2001 From: Karim Nosir Date: Thu, 25 Jun 2020 20:18:40 -0700 Subject: [PATCH] Remove explicit line "experimental_new_converter = True" the converter launched and is now the default. PiperOrigin-RevId: 318401041 Change-Id: If14b594d3d2a1997dfbdd615b55db0a06ff22809 --- .../experimental_new_converter/keras_lstm.ipynb | 3 --- .../stack_trace_example.py | 2 -- tensorflow/lite/python/lite_test.py | 7 ------- tensorflow/lite/python/lite_v2_test.py | 14 -------------- 4 files changed, 26 deletions(-) diff --git a/tensorflow/lite/examples/experimental_new_converter/keras_lstm.ipynb b/tensorflow/lite/examples/experimental_new_converter/keras_lstm.ipynb index b68a232f1d1..4bb16ae706c 100644 --- a/tensorflow/lite/examples/experimental_new_converter/keras_lstm.ipynb +++ b/tensorflow/lite/examples/experimental_new_converter/keras_lstm.ipynb @@ -156,9 +156,6 @@ "outputs": [], "source": [ "converter = tf.lite.TFLiteConverter.from_keras_model(model)\n", - "# Note: It will NOT work without enabling the experimental converter!\n", - "# `experimental_new_converter` flag.\n", - "converter.experimental_new_converter = True\n", "tflite_model = converter.convert()" ] }, diff --git a/tensorflow/lite/examples/experimental_new_converter/stack_trace_example.py b/tensorflow/lite/examples/experimental_new_converter/stack_trace_example.py index f0940db79e0..ba6733661e7 100644 --- a/tensorflow/lite/examples/experimental_new_converter/stack_trace_example.py +++ b/tensorflow/lite/examples/experimental_new_converter/stack_trace_example.py @@ -63,7 +63,6 @@ def test_from_saved_model(): # load the model and convert converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_path) - converter.experimental_new_converter = True converter.convert() @@ -78,7 +77,6 @@ def test_from_concrete_function(): func = model.get_concrete_function() converter = tf.lite.TFLiteConverter.from_concrete_functions([func]) - converter.experimental_new_converter = True converter.convert() diff --git a/tensorflow/lite/python/lite_test.py b/tensorflow/lite/python/lite_test.py index 478840c5549..4f445cf50d4 100644 --- a/tensorflow/lite/python/lite_test.py +++ b/tensorflow/lite/python/lite_test.py @@ -435,7 +435,6 @@ class FromSessionTest(TestModels, parameterized.TestCase): # Test None after 1st dimension. converter = lite.TFLiteConverter.from_session(sess, [in_tensor], [out_tensor]) - converter.experimental_new_converter = True tflite_model = converter.convert() # Check values from converted model. @@ -666,8 +665,6 @@ class FromSessionTest(TestModels, parameterized.TestCase): [out_tensor]) log_dir = self.get_temp_dir() converter.conversion_summary_dir = log_dir - # Conversion logs will only be generated when the mlir converter is enabled. - converter.experimental_new_converter = True tflite_model = converter.convert() self.assertTrue(tflite_model) @@ -1390,7 +1387,6 @@ class FromSessionTest(TestModels, parameterized.TestCase): converter = lite.TFLiteConverter.from_session(sess, [in_tensor], [out_tensor]) - converter.experimental_new_converter = True tflite_model = converter.convert() # Check values from converted model. @@ -1797,7 +1793,6 @@ class FromSavedModelTest(TestModels): 'If you encountered a problem') # Convert model and ensure model is not None. converter = lite.TFLiteConverter.from_saved_model(saved_model_dir) - converter.experimental_new_converter = True tflite_model = converter.convert() self.assertTrue(tflite_model) self.assertIn(optout_message, log.getvalue()) @@ -2385,8 +2380,6 @@ class GrapplerTest(TestModels, parameterized.TestCase): # Convert model. converter = lite.TFLiteConverter.from_session(sess, [in_tensor], [out_tensor]) - # Only disable this path in MLIR conversion for toco compatibility. - converter.experimental_new_converter = True tflite_model = converter.convert() # Check values from converted model. diff --git a/tensorflow/lite/python/lite_v2_test.py b/tensorflow/lite/python/lite_v2_test.py index ea8db15abc2..3b51991d674 100644 --- a/tensorflow/lite/python/lite_v2_test.py +++ b/tensorflow/lite/python/lite_v2_test.py @@ -830,7 +830,6 @@ class ControlFlowTest(lite_v2_test_util.ModelTest): # Convert model. converter = lite.TFLiteConverterV2.from_concrete_functions([concrete_func]) - converter.experimental_new_converter = True tflite_model = converter.convert() # Check values from converted model. @@ -857,7 +856,6 @@ class ControlFlowTest(lite_v2_test_util.ModelTest): # Convert model. converter = lite.TFLiteConverterV2.from_concrete_functions([concrete_func]) - converter.experimental_new_converter = True tflite_model = converter.convert() # Check values from converted model. @@ -887,7 +885,6 @@ class ControlFlowTest(lite_v2_test_util.ModelTest): # Convert model. converter = lite.TFLiteConverterV2.from_concrete_functions([concrete_func]) - converter.experimental_new_converter = True tflite_model = converter.convert() # Check values from converted model. @@ -911,7 +908,6 @@ class ControlFlowTest(lite_v2_test_util.ModelTest): # Convert model. converter = lite.TFLiteConverterV2.from_concrete_functions([concrete_func]) - converter.experimental_new_converter = True tflite_model = converter.convert() # Check values from converted model. @@ -941,7 +937,6 @@ class ControlFlowTest(lite_v2_test_util.ModelTest): # Convert model. converter = lite.TFLiteConverterV2.from_keras_model(model) - converter.experimental_new_converter = True tflite_model = converter.convert() actual_value = self._evaluateTFLiteModel(tflite_model, [input_data])[0] @@ -963,7 +958,6 @@ class ControlFlowTest(lite_v2_test_util.ModelTest): # Convert model. converter = lite.TFLiteConverterV2.from_keras_model(model) - converter.experimental_new_converter = True tflite_model = converter.convert() actual_value = self._evaluateTFLiteModel(tflite_model, [input_data])[0] @@ -987,7 +981,6 @@ class ControlFlowTest(lite_v2_test_util.ModelTest): # Convert model. converter = lite.TFLiteConverterV2.from_keras_model(model) - converter.experimental_new_converter = True tflite_model = converter.convert() actual_value = self._evaluateTFLiteModel(tflite_model, [input_data])[0] @@ -1024,7 +1017,6 @@ class GrapplerTest(lite_v2_test_util.ModelTest): np.testing.assert_almost_equal(expected_value.numpy(), actual_value[0]) # Enable hybrid quantization, same result - converter.experimental_new_converter = True converter.optimizations = [lite.Optimize.DEFAULT] hybrid_tflite_model = converter.convert() actual_value = self._evaluateTFLiteModel(hybrid_tflite_model, [input_data]) @@ -1048,7 +1040,6 @@ class UnknownShapes(lite_v2_test_util.ModelTest): concrete_func = model.get_concrete_function() converter = lite.TFLiteConverterV2.from_concrete_functions([concrete_func]) - converter.experimental_new_converter = True tflite_model = converter.convert() # Check values from converted model. @@ -1090,12 +1081,10 @@ class UnknownShapes(lite_v2_test_util.ModelTest): concrete_func, _ = self._getQuantizedModel() float_converter = lite.TFLiteConverterV2.from_concrete_functions( [concrete_func]) - float_converter.experimental_new_converter = True float_tflite_model = float_converter.convert() quantized_converter = lite.TFLiteConverterV2.from_concrete_functions( [concrete_func]) - quantized_converter.experimental_new_converter = True quantized_converter.optimizations = [lite.Optimize.DEFAULT] quantized_tflite_model = quantized_converter.convert() @@ -1115,14 +1104,12 @@ class UnknownShapes(lite_v2_test_util.ModelTest): concrete_func, calibration_gen = self._getQuantizedModel() float_converter = lite.TFLiteConverterV2.from_concrete_functions( [concrete_func]) - float_converter.experimental_new_converter = True float_tflite_model = float_converter.convert() quantized_converter = lite.TFLiteConverterV2.from_concrete_functions( [concrete_func]) quantized_converter.optimizations = [lite.Optimize.DEFAULT] quantized_converter.representative_dataset = calibration_gen - quantized_converter.experimental_new_converter = True quantized_tflite_model = quantized_converter.convert() # The default input and output types should be float. @@ -1152,7 +1139,6 @@ class UnknownShapes(lite_v2_test_util.ModelTest): concrete_func = model.get_concrete_function() converter = lite.TFLiteConverterV2.from_concrete_functions([concrete_func]) - converter.experimental_new_converter = True tflite_model = converter.convert() # Check values from converted model.