Home
last modified time | relevance | path

Searched refs:regressor (Results 1 – 17 of 17) sorted by relevance

/external/tensorflow/tensorflow/contrib/linear_optimizer/python/
Dsdca_estimator_test.py343 regressor = sdca_estimator.SDCALinearRegressor(
347 regressor.fit(input_fn=input_fn, steps=20)
348 loss = regressor.evaluate(input_fn=input_fn, steps=1)['loss']
350 self.assertIn('linear/x/weight', regressor.get_variable_names())
351 regressor_weights = regressor.get_variable_value('linear/x/weight')
384 regressor = sdca_estimator.SDCALinearRegressor(
391 regressor.fit(input_fn=input_fn, steps=20)
392 loss = regressor.evaluate(input_fn=input_fn, steps=1)['loss']
424 regressor = sdca_estimator.SDCALinearRegressor(
433 regressor.fit(input_fn=input_fn, steps=20)
[all …]
/external/webrtc/webrtc/modules/audio_coding/codecs/ilbc/
Dxcorr_coef.c28 int16_t *regressor, /* (i) second array */ in WebRtcIlbcfix_XcorrCoef() argument
58 max=WebRtcSpl_MaxAbsValueW16(regressor, subl + searchLen - 1); in WebRtcIlbcfix_XcorrCoef()
59 rp_beg = regressor; in WebRtcIlbcfix_XcorrCoef()
60 rp_end = regressor + subl; in WebRtcIlbcfix_XcorrCoef()
62 max = WebRtcSpl_MaxAbsValueW16(regressor - searchLen, subl + searchLen - 1); in WebRtcIlbcfix_XcorrCoef()
63 rp_beg = regressor - 1; in WebRtcIlbcfix_XcorrCoef()
64 rp_end = regressor + subl - 1; in WebRtcIlbcfix_XcorrCoef()
78 Energy=WebRtcSpl_DotProductWithScale(regressor, regressor, subl, shifts); in WebRtcIlbcfix_XcorrCoef()
82 rp = &regressor[pos]; in WebRtcIlbcfix_XcorrCoef()
Denhancer_interface.c57 int16_t *target, *regressor; in WebRtcIlbcfix_EnhancerInterface() local
119 regressor = target - 10; in WebRtcIlbcfix_EnhancerInterface()
122 max16 = WebRtcSpl_MaxAbsValueW16(&regressor[-50], ENH_BLOCKL_HALF + 50 - 1); in WebRtcIlbcfix_EnhancerInterface()
127 WebRtcSpl_CrossCorrelation(corr32, target, regressor, ENH_BLOCKL_HALF, 50, in WebRtcIlbcfix_EnhancerInterface()
148 ener = WebRtcSpl_DotProductWithScale(regressor - lagmax[i], in WebRtcIlbcfix_EnhancerInterface()
149 regressor - lagmax[i], in WebRtcIlbcfix_EnhancerInterface()
201 regressor=in+tlag-1; in WebRtcIlbcfix_EnhancerInterface()
204 max16 = WebRtcSpl_MaxAbsValueW16(regressor, plc_blockl + 3 - 1); in WebRtcIlbcfix_EnhancerInterface()
211 WebRtcSpl_CrossCorrelation(corr32, target, regressor, plc_blockl, 3, shifts, in WebRtcIlbcfix_EnhancerInterface()
Dxcorr_coef.h31 int16_t *regressor, /* (i) second array */
/external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/
Dlinear_test.py1105 regressor = linear.LinearRegressor(
1109 regressor.fit(input_fn=test_data.iris_input_multiclass_fn, steps=100)
1110 scores = regressor.evaluate(
1138 regressor = linear.LinearRegressor(
1142 regressor.fit(input_fn=_input_fn, steps=100)
1144 scores = regressor.evaluate(input_fn=_input_fn, steps=1)
1157 regressor = linear.LinearRegressor(
1161 regressor.fit(input_fn=_input_fn_train, steps=100)
1162 scores = regressor.evaluate(input_fn=_input_fn_train, steps=1)
1190 regressor = linear.LinearRegressor(
[all …]
Dnonlinear_test.py67 regressor = dnn.DNNRegressor(
71 regressor.fit(boston.data,
75 weights = ([regressor.get_variable_value("dnn/hiddenlayer_0/weights")] +
76 [regressor.get_variable_value("dnn/hiddenlayer_1/weights")] +
77 [regressor.get_variable_value("dnn/hiddenlayer_2/weights")] +
78 [regressor.get_variable_value("dnn/logits/weights")])
84 biases = ([regressor.get_variable_value("dnn/hiddenlayer_0/biases")] +
85 [regressor.get_variable_value("dnn/hiddenlayer_1/biases")] +
86 [regressor.get_variable_value("dnn/hiddenlayer_2/biases")] +
87 [regressor.get_variable_value("dnn/logits/biases")])
Ddnn_test.py1052 regressor = dnn.DNNRegressor(
1058 regressor.fit(input_fn=input_fn, steps=200)
1059 scores = regressor.evaluate(input_fn=input_fn, steps=1)
1075 regressor = dnn.DNNRegressor(
1080 regressor.fit(input_fn=_input_fn, steps=200)
1081 scores = regressor.evaluate(input_fn=_input_fn, steps=1)
1090 regressor = dnn.DNNRegressor(
1095 regressor.fit(x=train_x, y=train_y, steps=200)
1096 scores = regressor.evaluate(x=train_x, y=train_y, steps=1)
1125 regressor = dnn.DNNRegressor(
[all …]
Ddnn_linear_combined_test.py1213 regressor = dnn_linear_combined.DNNLinearCombinedRegressor(
1219 regressor.fit(input_fn=test_data.iris_input_logistic_fn, steps=10)
1220 scores = regressor.evaluate(
1252 regressor = dnn_linear_combined.DNNLinearCombinedRegressor(
1258 regressor.fit(input_fn=_input_fn_train, steps=100)
1259 scores = regressor.evaluate(input_fn=_input_fn_train, steps=1)
1287 regressor = dnn_linear_combined.DNNLinearCombinedRegressor(
1294 regressor.fit(input_fn=_input_fn_train, steps=100)
1295 scores = regressor.evaluate(input_fn=_input_fn_eval, steps=1)
1324 regressor = dnn_linear_combined.DNNLinearCombinedRegressor(
[all …]
Ddebug_test.py628 regressor = debug.DebugRegressor(
631 regressor.fit(input_fn=input_fn, steps=200)
632 scores = regressor.evaluate(input_fn=input_fn, steps=1)
645 regressor = debug.DebugRegressor(
648 regressor.fit(input_fn=_input_fn, steps=200)
649 scores = regressor.evaluate(input_fn=_input_fn, steps=1)
657 regressor = debug.DebugRegressor(
659 regressor.fit(x=train_x, y=train_y, steps=200)
660 scores = regressor.evaluate(x=train_x, y=train_y, steps=1)
681 regressor = debug.DebugRegressor(
[all …]
Dregression_test.py39 regressor = learn.LinearRegressor(
42 regressor.fit(x, y, steps=200)
43 self.assertIn("linear//weight", regressor.get_variable_names())
44 regressor_weights = regressor.get_variable_value("linear//weight")
Dlogistic_regressor_test.py71 regressor = logistic_regressor.LogisticRegressor(
75 regressor.fit(input_fn=_iris_data_input_fn, steps=1)
76 eval_metrics = regressor.evaluate(input_fn=_iris_data_input_fn, steps=1)
92 regressor.fit(input_fn=_iris_data_input_fn, steps=100)
93 eval_metrics = regressor.evaluate(input_fn=_iris_data_input_fn, steps=1)
Dmultioutput_test.py38 regressor = learn.LinearRegressor(
41 regressor.fit(x, y, steps=100)
42 score = mean_squared_error(np.array(list(regressor.predict_scores(x))), y)
/external/tensorflow/tensorflow/contrib/learn/python/learn/utils/
Dexport_test.py92 regressor = learn.LinearRegressor(feature_columns=cont_features)
96 regressor.fit(x, y, steps=10, monitors=[export_monitor])
110 regressor = learn.LinearRegressor(feature_columns=cont_features)
111 regressor.fit(x, y, steps=10, monitors=[export_monitor])
131 regressor = learn.LinearRegressor(feature_columns=[_X_COLUMN])
133 regressor.fit(input_fn=_training_input_fn, steps=10, monitors=[monitor])
149 regressor = learn.LinearRegressor(feature_columns=[_X_COLUMN])
152 regressor.fit(input_fn=_training_input_fn, steps=10, monitors=[monitor])
173 regressor = learn.LinearRegressor(feature_columns=[_X_COLUMN])
175 regressor.fit(input_fn=_training_input_fn, steps=10, monitors=[monitor])
[all …]
/external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/state_space_models/
Dstructural_ensemble_test.py107 regressor = estimators.StructuralEnsembleRegressor(
119 regressor.train(input_fn=train_input_fn, steps=1)
122 evaluation = regressor.evaluate(input_fn=eval_input_fn, steps=1)
126 regressor.predict(input_fn=predict_input_fn)
133 regressor = estimators.StructuralEnsembleRegressor(
143 regressor.train(input_fn=train_input_fn, steps=1)
146 evaluation = regressor.evaluate(input_fn=eval_input_fn, steps=1)
149 regressor.predict(input_fn=predict_input_fn)
/external/tensorflow/tensorflow/contrib/tensor_forest/client/
Drandom_forest_test.py96 regressor = random_forest.TensorForestEstimator(hparams.fill())
100 regressor.fit(input_fn=input_fn, steps=100)
101 res = regressor.evaluate(input_fn=input_fn, steps=10)
104 predictions = list(regressor.predict(input_fn=predict_input_fn))
210 regressor = random_forest.CoreTensorForestEstimator(
215 regressor.train(input_fn=input_fn, steps=100)
216 res = regressor.evaluate(input_fn=input_fn, steps=10)
219 predictions = list(regressor.predict(input_fn=predict_input_fn))
281 regressor = random_forest.CoreTensorForestEstimator(hparams.fill())
285 regressor.train(input_fn=input_fn, steps=100)
[all …]
/external/tensorflow/tensorflow/contrib/boosted_trees/estimator_batch/
Destimator_test.py237 regressor = estimator.GradientBoostedDecisionTreeRegressor(
246 regressor.fit(input_fn=_train_input_fn, steps=15)
247 regressor.evaluate(input_fn=_eval_input_fn, steps=1)
248 regressor.export(self._export_dir_base)
/external/tensorflow/tensorflow/contrib/autograph/examples/notebooks/
Drnn_keras_estimator.ipynb429 "regressor = tf.estimator.Estimator(\n",
433 "regressor.train(\n",
436 "eval_results = regressor.evaluate(\n",
1010 "def predict_with_estimator(color_name, regressor):\n",
1011 " predictions = regressor.predict(\n",
1031 " predict_with_estimator(color_name, regressor)\n",