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/external/tensorflow/tensorflow/python/keras/feature_column/
Ddense_features_v2_test.py149 price2 = fc.numeric_column('price2')
156 return transformation_cache.get(price2, state_manager, training=training)
162 price2.key, state_manager, training=training)
168 price2.get_dense_tensor = training_aware_get_dense_tensor
169 price2.transform_feature = training_aware_transform_feature
172 train_mode = df.DenseFeatures([price1, price2])(features, training=True)
173 predict_mode = df.DenseFeatures([price1, price2
261 price2 = fc.numeric_column('price2', shape=4)
267 dense_features = df.DenseFeatures([price1, price2])
299 price2 = fc.numeric_column('price2')
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Ddense_features_test.py281 price2 = fc.numeric_column('price2', shape=4)
287 dense_features = df.DenseFeatures([price1, price2])
319 price2 = fc.numeric_column('price2')
322 net = df.DenseFeatures([price1, price2])(features)
331 price2 = fc.numeric_column('price2')
335 dense_features = df.DenseFeatures([price1, price2])
343 self.assertAllClose([[3.], [4.]], self.evaluate(cols_dict[price2]))
376 price2 = fc.numeric_column('price2')
385 df.DenseFeatures([price1, price2])(features)
389 price2 = fc.numeric_column('price2')
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Dsequence_feature_column_test.py538 price2 = sfc.sequence_numeric_column('price2')
556 sequence_features = ksfc.SequenceFeatures([price1, price2])
/external/lzma/C/
DLzmaEnc.c1254 UInt32 price2 = price + GET_PRICE_LEN(&p->repLenEnc, posState, repLen); in GetOptimum() local
1256 if (price2 < opt->price) in GetOptimum()
1258 opt->price = price2; in GetOptimum()
1359 UInt32 price2 = p->opt[j].price; in GetOptimum() local
1360 if (price >= price2) in GetOptimum()
1362 price = price2; in GetOptimum()
1591 UInt32 price2; in GetOptimum() local
1595 price2 = price + GET_PRICE_LEN(&p->repLenEnc, posState2, len); in GetOptimum()
1599 if (price2 < opt->price) in GetOptimum()
1601 opt->price = price2; in GetOptimum()
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/external/tensorflow/tensorflow/python/feature_column/
Dfeature_column_test.py1603 price2 = fc._numeric_column('price2')
1609 predictions = fc.linear_model(features, [price1, price2])
1612 price2_var = get_linear_model_column_var(price2)
1625 price2 = fc._numeric_column('price2')
1629 fc.linear_model(features, [price1, price2], cols_to_vars=cols_to_vars)
1632 price2_var = get_linear_model_column_var(price2)
1635 self.assertAllEqual(cols_to_vars[price2], [price2_var])
1639 price2 = fc._numeric_column('price2', shape=3)
1649 fc.linear_model(features, [price1, price2], cols_to_vars=cols_to_vars)
1657 self.assertAllEqual([[0.], [0.]], cols_to_vars[price2][0])
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Dfeature_column_v2_test.py1745 price2 = fc.numeric_column('price2')
1748 predictions = fc_old.linear_model(features, [price1, price2])
1751 price2_var = get_linear_model_column_var(price2)
1764 price2 = fc.numeric_column('price2')
1768 fc_old.linear_model(features, [price1, price2], cols_to_vars=cols_to_vars)
1771 price2_var = get_linear_model_column_var(price2)
1774 self.assertAllEqual(cols_to_vars[price2], [price2_var])
1778 price2 = fc.numeric_column('price2', shape=3)
1789 features, [price1, price2], cols_to_vars=cols_to_vars)
1800 self.assertAllEqual([[0.], [0.]], self.evaluate(cols_to_vars[price2][0]))
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