From 507c7549317221bcf5b418a66fd0212cd4a7443b Mon Sep 17 00:00:00 2001 From: Elena Zhelezina Date: Tue, 9 Jun 2020 17:47:16 +0100 Subject: [PATCH] Fix for pylint errors. Change-Id: Idd96d7a41fd459c86ab0f6fbb63e5d543509145d --- tensorflow/lite/python/convert.py | 3 ++- tensorflow/lite/python/lite.py | 27 ++++++++++--------- tensorflow/lite/python/lite_test.py | 10 ++++--- tensorflow/lite/python/optimize/calibrator.py | 3 ++- .../lite/python/optimize/calibrator_test.py | 3 ++- 5 files changed, 28 insertions(+), 18 deletions(-) diff --git a/tensorflow/lite/python/convert.py b/tensorflow/lite/python/convert.py index 52edb700195..68e23634b2e 100644 --- a/tensorflow/lite/python/convert.py +++ b/tensorflow/lite/python/convert.py @@ -103,7 +103,8 @@ class OpsSet(enum.Enum): # significantly, but only slightly increases the model size. # WARNING: These ops are currently experimental and have not yet been finalized. # They are only compatible with CPU execution, and have not been optimized for production. - EXPERIMENTAL_TFLITE_BUILTINS_ACTIVATIONS_INT16_WEIGHTS_INT8 = "EXPERIMENTAL_TFLITE_BUILTINS_ACTIVATIONS_INT16_WEIGHTS_INT8" + EXPERIMENTAL_TFLITE_BUILTINS_ACTIVATIONS_INT16_WEIGHTS_INT8 = \ + "EXPERIMENTAL_TFLITE_BUILTINS_ACTIVATIONS_INT16_WEIGHTS_INT8" def __str__(self): return self.value diff --git a/tensorflow/lite/python/lite.py b/tensorflow/lite/python/lite.py index 26c6f0855af..bed48860b00 100644 --- a/tensorflow/lite/python/lite.py +++ b/tensorflow/lite/python/lite.py @@ -251,7 +251,8 @@ class QuantizationMode(object): self.post_training_fp16()) def activations_type(self): - return constants.INT16 if self._is_int16x8_target_required() else constants.INT8 + return constants.INT16 if self._is_int16x8_target_required() \ + else constants.INT8 def converter_flags(self, inference_ty=None, inference_input_ty=None): """Flags to the converter.""" @@ -262,7 +263,8 @@ class QuantizationMode(object): if self.training_time_int8_allow_float(): return { - "inference_type": inference_ty if inference_ty else self.activations_type(), + "inference_type": inference_ty if inference_ty else \ + self.activations_type(), "inference_input_type": inference_input_ty if inference_input_ty else constants.FLOAT, "post_training_quantize": False, # disable dynamic range quantization @@ -359,15 +361,15 @@ class QuantizationMode(object): def _is_int16x8_target_required(self): return bool( - set(self._target_spec.supported_ops).intersection([ - OpsSet.EXPERIMENTAL_TFLITE_BUILTINS_ACTIVATIONS_INT16_WEIGHTS_INT8 - ])) + set(self._target_spec.supported_ops).intersection([ + OpsSet.EXPERIMENTAL_TFLITE_BUILTINS_ACTIVATIONS_INT16_WEIGHTS_INT8 + ])) def _is_allow_float(self): return bool( - set(self._target_spec.supported_ops).intersection([ - OpsSet.TFLITE_BUILTINS - ])) + set(self._target_spec.supported_ops).intersection([ + OpsSet.TFLITE_BUILTINS + ])) def _any_optimization_enabled(self): return bool( @@ -441,7 +443,8 @@ class TFLiteConverterBase(object): return _get_grappler_config(optimizers) def _calibrate_quantize_model(self, result, inference_input_type, - inference_output_type, activations_type, allow_float): + inference_output_type, activations_type, + allow_float): """Calibrate and quantize the model.""" if not isinstance(self.representative_dataset, RepresentativeDataset): self.representative_dataset = RepresentativeDataset( @@ -458,8 +461,8 @@ class TFLiteConverterBase(object): return _mlir_quantize(calibrated) else: return calibrate_quantize.calibrate_and_quantize( - self.representative_dataset.input_gen, inference_input_type, - inference_output_type, allow_float, activations_type) + self.representative_dataset.input_gen, inference_input_type, + inference_output_type, allow_float, activations_type) def _is_unknown_shapes_allowed(self): # Unknown dimensions are only allowed with the new converter. @@ -1992,7 +1995,7 @@ class TocoConverter(object): @classmethod @_deprecation.deprecated( - None, "Use `lite.TFLiteConverter.from_keras_model_file` instead.") + None, "Use `lite.TFLiteConverter.from_keras_model_file` instead.") def from_keras_model_file(cls, model_file, input_arrays=None, diff --git a/tensorflow/lite/python/lite_test.py b/tensorflow/lite/python/lite_test.py index 044b1211e17..cae49cb147f 100644 --- a/tensorflow/lite/python/lite_test.py +++ b/tensorflow/lite/python/lite_test.py @@ -882,11 +882,15 @@ class FromSessionTest(TestModels, parameterized.TestCase): @parameterized.named_parameters( # Quantize model to Int8: with enable mlir - ('UseTfliteBuiltinsIntEnableMLIR', [lite.OpsSet.TFLITE_BUILTINS_INT8], True), + ('UseTfliteBuiltinsIntEnableMLIR', + [lite.OpsSet.TFLITE_BUILTINS_INT8], True), # Quantize model to Int8: with disable mlir - ('UseTfliteBuiltinsIntDisableMLIR', [lite.OpsSet.TFLITE_BUILTINS_INT8], False), + ('UseTfliteBuiltinsIntDisableMLIR', + [lite.OpsSet.TFLITE_BUILTINS_INT8], False), # Quantize model to Int16: with disable mlir - ('UseTfliteBuiltinsInt16DisableMLIR', [lite.OpsSet.EXPERIMENTAL_TFLITE_BUILTINS_ACTIVATIONS_INT16_WEIGHTS_INT8], False)) + ('UseTfliteBuiltinsInt16DisableMLIR', + [lite.OpsSet.EXPERIMENTAL_TFLITE_BUILTINS_ACTIVATIONS_INT16_WEIGHTS_INT8], + False)) def testCalibrateAndQuantizeBuiltinInt(self, supported_ops, enable_mlir): with ops.Graph().as_default(): inp, output, calibration_gen = self._getCalibrationQuantizeModel() diff --git a/tensorflow/lite/python/optimize/calibrator.py b/tensorflow/lite/python/optimize/calibrator.py index 90c43fcddfa..2b08ec690ff 100644 --- a/tensorflow/lite/python/optimize/calibrator.py +++ b/tensorflow/lite/python/optimize/calibrator.py @@ -78,7 +78,8 @@ class Calibrator(object): computation, useful when targeting an integer-only backend. If False, an error will be thrown if an operation cannot be quantized, otherwise the model will fallback to float ops. - activations_type: A tf.dtype representing the desired type for activations. + activations_type: A tf.dtype representing the desired type for + activations. resize_input: A boolean. True if the shape of the sample data is different from the input. """ diff --git a/tensorflow/lite/python/optimize/calibrator_test.py b/tensorflow/lite/python/optimize/calibrator_test.py index f778c8a555d..d79d76b09ed 100644 --- a/tensorflow/lite/python/optimize/calibrator_test.py +++ b/tensorflow/lite/python/optimize/calibrator_test.py @@ -96,7 +96,8 @@ class CalibratorTest(test_util.TensorFlowTestCase, parameterized.TestCase): ('UseActivationTypeInt8 - EnableMlirQuantizer', constants.INT8), # Activation type Int16 ('UseActivationTypeInt16 - DisableEnableMlirQuantizer', constants.INT16)) - def test_calibration_with_quantization_multiple_inputs(self, activations_type): + def test_calibration_with_quantization_multiple_inputs(self, + activations_type): # Load multi add model from test data. # This model has 4 inputs of size (1, 8, 8, 3). model_path = resource_loader.get_path_to_datafile(