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Searched refs:model_type (Results 1 – 11 of 11) sorted by relevance

/external/tensorflow/tensorflow/python/keras/
Dtesting_utils.py314 _thread_local_data.model_type = None
332 previous_value = _thread_local_data.model_type
334 _thread_local_data.model_type = value
338 _thread_local_data.model_type = previous_value
442 if _thread_local_data.model_type is None:
447 return _thread_local_data.model_type
524 model_type = get_model_type()
525 if model_type == 'subclass':
527 if model_type == 'subclass_custom_build':
529 if model_type == 'sequential':
[all …]
Dcombinations.py61 return combinations.combine(model_type=KERAS_MODEL_TYPES)
93 model_type = kwargs.pop('model_type', None)
94 if model_type in KERAS_MODEL_TYPES:
95 return [testing_utils.model_type_scope(model_type)]
Dkeras_parameterized.py286 def decorated(self, model_type, *args, **kwargs): argument
288 if model_type == 'functional':
290 elif model_type == 'subclass':
292 elif model_type == 'sequential':
295 raise ValueError('Unknown model type: %s' % (model_type,))
Dmodels_test.py459 def _clone_and_build_test_helper(self, model, model_type): argument
463 is_subclassed = (model_type == 'subclass')
Dcallbacks_test.py2097 model_type = testing_utils.get_model_type()
2116 self._strip_layer_names(summary_file.histograms, model_type),
2128 model_type = testing_utils.get_model_type()
2147 self._strip_layer_names(summary_file.histograms, model_type),
2166 self._strip_layer_names(summary_file.images, model_type),
2253 def _strip_layer_names(self, summaries, model_type): argument
2271 start_from = 2 if 'subclass' in model_type else 1
/external/tensorflow/tensorflow/python/keras/layers/
Dcudnn_recurrent_test.py275 model_nest_level=[1, 2], model_type=['seq', 'func']))
280 model_nest_level, model_type): argument
311 model_type)
313 model_nest_level, model_type)
323 def _make_nested_model(self, input_shape, layer, level=1, model_type='func'): argument
343 if model_type == 'func':
345 elif model_type == 'seq':
/external/tensorflow/tensorflow/python/keras/utils/
Dcomposite_tensor_support_test.py133 model_type = testing_utils.get_model_type()
134 if model_type == "subclass":
137 if model_type == "sequential":
147 if model_type == "functional":
160 raise ValueError("Unknown model type {}".format(model_type))
/external/tensorflow/tensorflow/lite/g3doc/performance/
Dpost_training_integer_quant.ipynb547 "def test_model(tflite_file, test_image_index, model_type):\n",
553 " template = model_type + \" Model \\n True:{true}, Predicted:{predict}\"\n",
575 "test_model(tflite_model_file, test_image_index, model_type=\"Float\")"
595 "test_model(tflite_model_quant_file, test_image_index, model_type=\"Quantized\")"
625 "def evaluate_model(tflite_file, model_type):\n",
635 " model_type, accuracy, len(test_images)))"
655 "evaluate_model(tflite_model_file, model_type=\"Float\")"
675 "evaluate_model(tflite_model_quant_file, model_type=\"Quantized\")"
/external/tensorflow/tensorflow/python/keras/applications/
Dmobilenet_v3.py154 model_type='large', argument
329 model = models.Model(inputs, x, name='MobilenetV3' + model_type)
334 model_type, '_minimalistic' if minimalistic else '', str(alpha))
/external/tensorflow/tensorflow/lite/micro/examples/micro_speech/train/
Dtrain_micro_speech_model.ipynb485 "def run_tflite_inference(tflite_model_path, model_type=\"Float\"):\n",
502 " if model_type == \"Quantized\":\n",
516 " model_type, (correct_predictions * 100) / len(test_data), len(test_data)))"
533 "run_tflite_inference(MODEL_TFLITE, model_type='Quantized')"
/external/tensorflow/tensorflow/python/keras/mixed_precision/
Dkeras_test.py473 model_type = testing_utils.get_model_type()
474 if save_format == 'h5' and model_type == 'subclass':
477 if (save_format == 'tf' and model_type == 'subclass' and