/external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
H A D | serialization_test.py | 21 from tensorflow.python.keras._impl import keras namespace 28 layer = keras.layers.Dense( 30 config = keras.layers.serialize(layer) 31 new_layer = keras.layers.deserialize(config) 32 self.assertEqual(new_layer.activation, keras.activations.relu) 34 keras.regularizers.L1L2) 36 keras.initializers.Ones)
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H A D | embeddings_test.py | 21 from tensorflow.python.keras._impl import keras namespace 22 from tensorflow.python.keras._impl.keras import testing_utils 31 keras.layers.Embedding, 41 keras.layers.Embedding, 51 keras.layers.Embedding, 61 keras.layers.Embedding,
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H A D | noise_test.py | 21 from tensorflow.python.keras._impl import keras namespace 22 from tensorflow.python.keras._impl.keras import testing_utils 31 keras.layers.GaussianNoise, 38 keras.layers.GaussianDropout, 45 keras.layers.AlphaDropout,
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H A D | advanced_activations_test.py | 21 from tensorflow.python.keras._impl import keras namespace 22 from tensorflow.python.keras._impl.keras import testing_utils 31 testing_utils.layer_test(keras.layers.LeakyReLU, 37 testing_utils.layer_test(keras.layers.PReLU, kwargs={}, 42 testing_utils.layer_test(keras.layers.PReLU, 49 testing_utils.layer_test(keras.layers.ELU, 55 testing_utils.layer_test(keras.layers.ThresholdedReLU, 61 testing_utils.layer_test(keras [all...] |
H A D | convolutional_recurrent_test.py | 23 from tensorflow.python.keras._impl import keras namespace 24 from tensorflow.python.keras._impl.keras import testing_utils 52 x = keras.Input(batch_shape=inputs.shape) 60 layer = keras.layers.ConvLSTM2D(**kwargs) 65 model = keras.models.Model(x, states[0]) 68 keras.backend.eval(layer.states[0]), state, atol=1e-4) 72 keras.layers.ConvLSTM2D, 95 model = keras [all...] |
H A D | local_test.py | 23 from tensorflow.python.keras._impl import keras namespace 24 from tensorflow.python.keras._impl.keras import testing_utils 44 keras.layers.LocallyConnected1D, 68 layer = keras.layers.LocallyConnected1D(**kwargs) 72 keras.backend.variable(np.ones((num_samples, num_steps, input_dim)))) 75 k_constraint = keras.constraints.max_norm(0.01) 76 b_constraint = keras.constraints.max_norm(0.01) 84 layer = keras [all...] |
H A D | normalization_test.py | 23 from tensorflow.python.keras._impl import keras namespace 24 from tensorflow.python.keras._impl.keras import testing_utils 33 keras.layers.BatchNormalization, 37 'gamma_regularizer': keras.regularizers.l2(0.01), 38 'beta_regularizer': keras.regularizers.l2(0.01) 42 keras.layers.BatchNormalization, 51 keras.layers.BatchNormalization, 58 layer = keras [all...] |
/external/tensorflow/tensorflow/python/keras/_impl/keras/applications/ |
H A D | resnet50_test.py | 21 from tensorflow.python.keras._impl import keras namespace 28 model = keras.applications.ResNet50(weights=None) 32 model = keras.applications.ResNet50(weights=None, include_top=False) 36 model = keras.applications.ResNet50(weights=None, 43 keras.applications.ResNet50(weights='unknown', 47 keras.applications.ResNet50(weights='imagenet',
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H A D | vgg16_test.py | 21 from tensorflow.python.keras._impl import keras namespace 28 model = keras.applications.VGG16(weights=None) 32 model = keras.applications.VGG16(weights=None, include_top=False) 36 model = keras.applications.VGG16(weights=None, 43 keras.applications.VGG16(weights='unknown', 46 keras.applications.VGG16(weights='imagenet',
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H A D | vgg19_test.py | 21 from tensorflow.python.keras._impl import keras namespace 28 model = keras.applications.VGG19(weights=None) 32 model = keras.applications.VGG19(weights=None, include_top=False) 36 model = keras.applications.VGG19(weights=None, 43 keras.applications.VGG19(weights='unknown', 46 keras.applications.VGG19(weights='imagenet',
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H A D | densenet_test.py | 21 from tensorflow.python.keras._impl import keras namespace 28 model = keras.applications.DenseNet121(weights=None) 32 model = keras.applications.DenseNet121(weights=None, include_top=False) 36 model = keras.applications.DenseNet121(weights=None, 43 keras.applications.DenseNet121(weights='unknown', 46 keras.applications.DenseNet121(weights='imagenet', 53 model = keras.applications.DenseNet169(weights=None) 57 model = keras.applications.DenseNet169(weights=None, include_top=False) 61 model = keras [all...] |
H A D | imagenet_utils_test.py | 23 from tensorflow.python.keras._impl import keras namespace 24 from tensorflow.python.keras._impl.keras.applications.imagenet_utils import preprocess_input 48 inputs = keras.layers.Input(shape=x.shape[1:]) 49 outputs = keras.layers.Lambda( 51 model = keras.models.Model(inputs, outputs) 54 outputs1 = keras.layers.Lambda(lambda x: 57 model1 = keras.models.Model(inputs, outputs1) 60 inputs2 = keras [all...] |
H A D | inception_resnet_v2_test.py | 23 from tensorflow.python.keras._impl import keras namespace 30 model = keras.applications.InceptionResNetV2(weights=None) 34 model = keras.applications.InceptionResNetV2(weights=None, 39 model = keras.applications.InceptionResNetV2(weights=None, 46 keras.applications.InceptionResNetV2(weights='unknown', 49 keras.applications.InceptionResNetV2(weights='imagenet', 54 out1 = keras.applications.inception_resnet_v2.preprocess_input(x)
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H A D | inception_v3_test.py | 23 from tensorflow.python.keras._impl import keras namespace 30 model = keras.applications.InceptionV3(weights=None) 34 model = keras.applications.InceptionV3(weights=None, include_top=False) 38 model = keras.applications.InceptionV3(weights=None, 45 keras.applications.InceptionV3(weights='unknown', 48 keras.applications.InceptionV3(weights='imagenet', 53 out1 = keras.applications.inception_v3.preprocess_input(x)
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H A D | mobilenet_test.py | 23 from tensorflow.python.keras._impl import keras namespace 30 model = keras.applications.MobileNet(weights=None) 34 model = keras.applications.MobileNet(weights=None, include_top=False) 38 model = keras.applications.MobileNet(weights=None, 45 keras.applications.MobileNet(weights='unknown', 48 keras.applications.MobileNet(weights='imagenet', 53 out1 = keras.applications.mobilenet.preprocess_input(x) 57 keras.backend.set_image_data_format('channels_first') 58 model = keras [all...] |
H A D | nasnet_test.py | 21 from tensorflow.python.keras._impl import keras namespace 28 model = keras.applications.NASNetMobile(weights=None) 32 model = keras.applications.NASNetMobile(weights=None, include_top=False) 36 model = keras.applications.NASNetMobile(weights=None, 43 keras.applications.NASNetMobile(weights='unknown', 46 keras.applications.NASNetMobile(weights='imagenet', 53 model = keras.applications.NASNetLarge(weights=None) 57 model = keras.applications.NASNetLarge(weights=None, include_top=False) 61 model = keras [all...] |
H A D | xception_test.py | 23 from tensorflow.python.keras._impl import keras namespace 30 model = keras.applications.Xception(weights=None) 34 model = keras.applications.Xception(weights=None, include_top=False) 38 model = keras.applications.Xception(weights=None, 45 keras.applications.Xception(weights='unknown', 48 keras.applications.Xception(weights='imagenet', 53 out1 = keras.applications.xception.preprocess_input(x)
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/external/tensorflow/tensorflow/python/keras/_impl/keras/ |
H A D | testing_utils.py | 24 from tensorflow.python.keras._impl import keras namespace 106 x = keras.layers.Input(shape=input_shape[1:], dtype=input_dtype) 108 if keras.backend.dtype(y) != expected_output_dtype: 113 keras.backend.dtype(y), 117 model = keras.models.Model(x, y) 140 recovered_model = keras.models.Model.from_config(model_config) 156 model = keras.models.Sequential() 177 recovered_model = keras.models.Sequential.from_config(model_config)
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H A D | constraints_test.py | 23 from tensorflow.python.keras._impl import keras namespace 44 fn = keras.constraints.get(name) 45 ref_fn = getattr(keras.constraints, name)() 47 config = keras.constraints.serialize(fn) 48 fn = keras.constraints.deserialize(config) 55 norm_instance = keras.constraints.max_norm(m) 56 normed = norm_instance(keras.backend.variable(array)) 57 assert np.all(keras.backend.eval(normed) < m) 60 norm_instance = keras [all...] |
H A D | regularizers_test.py | 21 from tensorflow.python.keras._impl import keras namespace 22 from tensorflow.python.keras._impl.keras import testing_utils 36 y_train = keras.utils.to_categorical(y_train, NUM_CLASSES) 37 y_test = keras.utils.to_categorical(y_test, NUM_CLASSES) 42 model = keras.models.Sequential() 43 model.add(keras.layers.Dense(NUM_CLASSES, 55 for reg in [keras.regularizers.l1(), 56 keras [all...] |
/external/tensorflow/tensorflow/python/keras/_impl/keras/utils/ |
H A D | np_utils_test.py | 23 from tensorflow.python.keras._impl import keras namespace 39 keras.utils.to_categorical(label, num_classes) for label in labels]
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H A D | training_utils_test.py | 23 from tensorflow.python.keras._impl import keras namespace 39 model = keras.models.Sequential() 40 model.add(keras.layers.Dense(hidden_dim, 42 model.add(keras.layers.Dense(output_dim)) 47 parallel_model = keras.utils.multi_gpu_model(model, gpus=gpus) 51 parallel_model = keras.utils.multi_gpu_model(model, gpus=target_gpu_id) 67 input_a = keras.Input((input_dim_a,)) 68 input_b = keras.Input((input_dim_b,)) 69 a = keras [all...] |
H A D | generic_utils_test.py | 21 from tensorflow.python.keras._impl import keras namespace 40 self.assertTrue(keras.utils.generic_utils.has_arg( 42 self.assertFalse(keras.utils.generic_utils.has_arg( 44 self.assertTrue(keras.utils.generic_utils.has_arg( 46 self.assertFalse(keras.utils.generic_utils.has_arg( 48 self.assertTrue(keras.utils.generic_utils.has_arg( 50 self.assertFalse(keras.utils.generic_utils.has_arg( 52 self.assertTrue(keras.utils.generic_utils.has_arg( 66 with keras [all...] |
/external/tensorflow/tensorflow/python/keras/_impl/keras/preprocessing/ |
H A D | sequence_test.py | 23 from tensorflow.python.keras._impl import keras namespace 33 b = keras.preprocessing.sequence.pad_sequences(a, maxlen=3, padding='pre') 35 b = keras.preprocessing.sequence.pad_sequences(a, maxlen=3, padding='post') 39 b = keras.preprocessing.sequence.pad_sequences( 42 b = keras.preprocessing.sequence.pad_sequences( 47 b = keras.preprocessing.sequence.pad_sequences(a, maxlen=3, value=1) 54 b = keras.preprocessing.sequence.pad_sequences(a, maxlen=3, padding='pre') 57 b = keras.preprocessing.sequence.pad_sequences(a, maxlen=3, padding='post') 62 b = keras [all...] |
H A D | text_test.py | 23 from tensorflow.python.keras._impl import keras namespace 31 encoded = keras.preprocessing.text.one_hot(text, 5) 38 encoded = keras.preprocessing.text.one_hot(text, 5) 49 tokenizer = keras.preprocessing.text.Tokenizer(num_words=10) 66 encoded = keras.preprocessing.text.hashing_trick(text, 5) 73 encoded = keras.preprocessing.text.hashing_trick( 84 tokenizer = keras.preprocessing.text.Tokenizer() 90 tokenizer = keras.preprocessing.text.Tokenizer(oov_token='<unk>')
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