Searched refs:linear_model (Results 1 – 11 of 11) sorted by relevance
| /external/tensorflow/tensorflow/python/keras/premade/ |
| D | wide_deep_test.py | 43 linear_model = linear.LinearModel(units=1)
45 wide_deep_model = wide_deep.WideDeepModel(linear_model, dnn_model)
60 linear_model = linear.LinearModel(units=1, kernel_initializer='zeros')
63 wide_deep_model = wide_deep.WideDeepModel(linear_model, dnn_model)
79 self.evaluate(wide_deep_model.linear_model.dense_layers[0].kernel))
85 linear_model = linear.LinearModel(units=1)
87 wide_deep_model = wide_deep.WideDeepModel(linear_model, dnn_model)
101 linear_model = training.Model(inp, [l1, l2])
102 linear_model.set_weights([np.asarray([[0.5, 0.3]])])
107 wide_deep_model = wide_deep.WideDeepModel(linear_model, dnn_model)
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| D | wide_deep.py | 74 def __init__(self, linear_model, dnn_model, activation=None, **kwargs): argument
89 self.linear_model = linear_model
98 linear_output = self.linear_model(linear_inputs)
123 linear_vars = self.linear_model.trainable_variables
167 params=self.linear_model.trainable_weights, # pylint: disable=protected-access
197 linear_config = generic_utils.serialize_keras_object(self.linear_model)
210 linear_model = layer_module.deserialize(linear_config, custom_objects)
216 linear_model=linear_model,
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| D | linear_test.py | 167 linear_model = linear.LinearModel(
169 combined = sequential.Sequential([dense_feature_layer, linear_model])
178 linear_model = linear.LinearModel(units=3, use_bias=True)
179 config = linear_model.get_config()
181 self.assertEqual(linear_model.units, cloned_linear_model.units)
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| /external/tensorflow/tensorflow/python/feature_column/ |
| D | feature_column_v2_test.py | 438 predictions = fc_old.linear_model(features, [price])
668 predictions = fc_old.linear_model(features, [bucketized_price])
696 predictions = fc_old.linear_model(features, [bucketized_price])
725 predictions = fc_old.linear_model(features, [bucketized_price])
965 predictions = fc_old.linear_model({
1233 predictions = fc_old.linear_model({
1316 fc_old.linear_model({
1343 predictions = fc_old.linear_model({
1412 fc_old.linear_model(features={}, feature_columns=[])
1416 fc_old.linear_model(features={'a': [[0]]}, feature_columns='NotSupported')
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| D | feature_column_test.py | 355 predictions = fc.linear_model(features, [price])
549 predictions = fc.linear_model(features, [bucketized_price])
577 predictions = fc.linear_model(features, [bucketized_price])
853 predictions = fc.linear_model({
1113 predictions = fc.linear_model({
1170 fc.linear_model({
1311 fc.linear_model(features={}, feature_columns=[])
1315 fc.linear_model(features={'a': [[0]]}, feature_columns='NotSupported')
1334 fc.linear_model(
1340 fc.linear_model(
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| D | feature_column.py | 369 def linear_model(features, function
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| /external/tensorflow/tensorflow/python/keras/distribute/ |
| D | keras_premade_models_test.py | 85 linear_model = linear.LinearModel(units=1)
87 wide_deep_model = wide_deep.WideDeepModel(linear_model, dnn_model)
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.feature_column.pbtxt | 40 name: "linear_model"
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| D | tensorflow.keras.experimental.-wide-deep-model.pbtxt | 154 …argspec: "args=[\'self\', \'linear_model\', \'dnn_model\', \'activation\'], varargs=None, keywords…
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.keras.experimental.-wide-deep-model.pbtxt | 154 …argspec: "args=[\'self\', \'linear_model\', \'dnn_model\', \'activation\'], varargs=None, keywords…
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| /external/tensorflow/tensorflow/python/training/ |
| D | warm_starting_util_test.py | 106 fc.linear_model(
1147 fc.linear_model(
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