| /external/tensorflow/tensorflow/python/keras/_impl/keras/ |
| integration_test.py | 36 (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data(
42 y_test = keras.utils.to_categorical(y_test)
55 validation_data=(x_test, y_test),
62 (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data(
68 y_test = keras.utils.to_categorical(y_test)
80 validation_data=(x_test, y_test),
87 (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data(
93 y_test = keras.utils.to_categorical(y_test
[all...] |
| callbacks_test.py | 67 (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data(
72 y_test = keras.utils.to_categorical(y_test)
100 validation_data=(x_test, y_test),
120 validation_data=(x_test, y_test),
141 validation_data=(x_test, y_test),
161 validation_data=(x_test, y_test),
179 validation_data=(x_test, y_test),
204 validation_data=(x_test, y_test),
225 (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data
[all...] |
| regularizers_test.py | 31 (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data(
37 y_test = keras.utils.to_categorical(y_test, NUM_CLASSES)
38 return (x_train, y_train), (x_test, y_test)
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| estimator_test.py | 72 (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data(
78 y_test = keras.utils.to_categorical(y_test)
88 x={input_name: x_test}, y=y_test, num_epochs=1, shuffle=False)
96 y_test), train_input_fn, inference_input_fn
158 x_test, y_test), _, eval_input_fn = get_resource_for_simple_model(
173 keras_eval = keras_model.evaluate(x_test, y_test, batch_size=32)
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| /external/tensorflow/tensorflow/python/keras/_impl/keras/datasets/ |
| cifar100.py | 39 Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
55 x_test, y_test = load_batch(fpath, label_key=label_mode + '_labels')
58 y_test = np.reshape(y_test, (len(y_test), 1))
64 return (x_train, y_train), (x_test, y_test)
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| cifar10.py | 36 Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
53 x_test, y_test = load_batch(fpath)
56 y_test = np.reshape(y_test, (len(y_test), 1))
62 return (x_train, y_train), (x_test, y_test)
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| mnist.py | 36 Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
44 x_test, y_test = f['x_test'], f['y_test']
46 return (x_train, y_train), (x_test, y_test)
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| fashion_mnist.py | 33 Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
54 y_test = np.frombuffer(lbpath.read(), np.uint8, offset=8)
58 imgpath.read(), np.uint8, offset=16).reshape(len(y_test), 28, 28)
60 return (x_train, y_train), (x_test, y_test)
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| boston_housing.py | 39 Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
61 y_test = np.array(y[int(len(x) * (1 - test_split)):])
62 return (x_train, y_train), (x_test, y_test)
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| imdb.py | 60 Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
86 x_test, labels_test = f['x_test'], f['y_test']
128 x_test, y_test = np.array(xs[idx:]), np.array(labels[idx:])
130 return (x_train, y_train), (x_test, y_test)
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| reuters.py | 62 Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
112 x_test, y_test = np.array(xs[idx:]), np.array(labels[idx:])
114 return (x_train, y_train), (x_test, y_test)
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| /external/tensorflow/tensorflow/examples/learn/ |
| hdf5_classification.py | 34 x_train, x_test, y_train, y_test = model_selection.train_test_split(
43 h5f.create_dataset('y_test', data=y_test)
50 y_test = np.array(h5f['y_test'])
66 x={X_FEATURE: x_test}, y=y_test, num_epochs=1, shuffle=False)
69 y_predicted = y_predicted.reshape(np.array(y_test).shape)
72 score = metrics.accuracy_score(y_test, y_predicted)
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| boston.py | 35 x_train, x_test, y_train, y_test = model_selection.train_test_split(
56 x={'x': x_transformed}, y=y_test, num_epochs=1, shuffle=False)
59 y_predicted = y_predicted.reshape(np.array(y_test).shape)
62 score_sklearn = metrics.mean_squared_error(y_predicted, y_test)
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| iris_run_config.py | 34 x_train, x_test, y_train, y_test = model_selection.train_test_split(
56 x={X_FEATURE: x_test}, y=y_test, num_epochs=1, shuffle=False)
59 y_predicted = y_predicted.reshape(np.array(y_test).shape)
62 score = metrics.accuracy_score(y_test, y_predicted)
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| iris_custom_decay_dnn.py | 73 x_train, x_test, y_train, y_test = model_selection.train_test_split(
85 x={X_FEATURE: x_test}, y=y_test, num_epochs=1, shuffle=False)
88 y_predicted = y_predicted.reshape(np.array(y_test).shape)
91 score = metrics.accuracy_score(y_test, y_predicted)
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| iris_custom_model.py | 70 x_train, x_test, y_train, y_test = model_selection.train_test_split(
82 x={X_FEATURE: x_test}, y=y_test, num_epochs=1, shuffle=False)
85 y_predicted = y_predicted.reshape(np.array(y_test).shape)
88 score = metrics.accuracy_score(y_test, y_predicted)
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| multiple_gpu.py | 89 x_train, x_test, y_train, y_test = model_selection.train_test_split(
101 x={X_FEATURE: x_test}, y=y_test, num_epochs=1, shuffle=False)
104 y_predicted = y_predicted.reshape(np.array(y_test).shape)
107 score = metrics.accuracy_score(y_test, y_predicted)
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| text_classification.py | 114 y_test = pandas.Series(dbpedia.test.target)
153 x={WORDS_FEATURE: x_test}, y=y_test, num_epochs=1, shuffle=False)
156 y_predicted = y_predicted.reshape(np.array(y_test).shape)
159 score = metrics.accuracy_score(y_test, y_predicted)
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| text_classification_character_rnn.py | 83 y_test = pandas.Series(dbpedia.test.target)
106 y=y_test,
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| text_classification_cnn.py | 112 y_test = pandas.Series(dbpedia.test.target)
137 y=y_test,
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| text_classification_character_cnn.py | 114 y_test = pandas.Series(dbpedia.test.target)
140 y=y_test,
145 y_predicted = y_predicted.reshape(np.array(y_test).shape)
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| /external/tensorflow/tensorflow/examples/get_started/regression/ |
| imports85.py | 182 `(x_train, y_train), (x_test, y_test) = get_imports85_dataset(...)`
201 y_test = x_test.pop(y_name)
203 return (x_train, y_train), (x_test, y_test)
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| /external/tensorflow/tensorflow/python/keras/_impl/keras/utils/ |
| io_utils_test.py | 70 y_test = keras.utils.io_utils.HDF5Matrix(
92 out_eval = model.evaluate(x_test, y_test, batch_size=32, verbose=False)
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| /external/tensorflow/tensorflow/contrib/boosted_trees/examples/ |
| boston.py | 89 y_test) = tf.keras.datasets.boston_housing.load_data()
98 x={"x": x_test}, y=y_test, num_epochs=1, shuffle=False)
|
| boston_combined.py | 81 y_test) = tf.keras.datasets.boston_housing.load_data()
90 x={"x": x_test}, y=y_test, num_epochs=1, shuffle=False)
|
