| /external/apache-commons-math/src/main/java/org/apache/commons/math/ode/ |
| D | ContinuousOutputModel.java | 108 private List<StepInterpolator> steps; field in ContinuousOutputModel
114 steps = new ArrayList<StepInterpolator>(); in ContinuousOutputModel()
129 if (model.steps.size() == 0) { in append()
133 if (steps.size() == 0) { in append()
149 final StepInterpolator lastInterpolator = steps.get(index); in append()
161 for (StepInterpolator interpolator : model.steps) { in append()
162 steps.add(interpolator.copy()); in append()
165 index = steps.size() - 1; in append()
166 finalTime = (steps.get(index)).getCurrentTime(); in append()
189 steps.clear(); in reset()
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| D | linear_test.py | 97 classifier.fit(input_fn=input_fn, steps=100)
98 loss1 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
99 classifier.fit(input_fn=input_fn, steps=200)
100 loss2 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
123 classifier.fit(input_fn=input_fn, steps=100)
124 loss1 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
125 classifier.fit(input_fn=input_fn, steps=200)
126 loss2 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
138 classifier.fit(input_fn=test_data.iris_input_multiclass_fn, steps=100)
140 input_fn=test_data.iris_input_multiclass_fn, steps=100)
[all …]
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| D | dnn_linear_combined_test.py | 106 def steps(self): member in _StepCounterHook
221 estimator.fit(input_fn=test_data.iris_input_multiclass_fn, steps=10)
224 estimator.evaluate(input_fn=test_data.iris_input_multiclass_fn, steps=10)
277 classifier.fit(input_fn=_input_fn, steps=2)
297 input_fn=test_data.iris_input_multiclass_fn, steps=100,
348 classifier.fit(input_fn=_input_fn_float_label, steps=50)
370 classifier.fit(input_fn=test_data.iris_input_logistic_fn, steps=100)
372 input_fn=test_data.iris_input_logistic_fn, steps=100)
420 classifier.fit(input_fn=_input_fn, steps=100)
421 scores = classifier.evaluate(input_fn=_input_fn, steps=100)
[all …]
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| D | debug_test.py | 97 input_fn=_input_fn_builder(train_features, train_labels), steps=50)
116 input_fn=_input_fn_builder(train_features, train_labels), steps=50)
133 input_fn=_input_fn_builder(train_features, train_labels), steps=50)
155 input_fn=_input_fn_builder(train_features, train_labels), steps=50)
178 input_fn=_input_fn_builder(train_features, train_labels), steps=50)
199 input_fn=_input_fn_builder(train_features, train_labels), steps=50)
225 classifier.fit(input_fn=input_fn, steps=5)
226 scores = classifier.evaluate(input_fn=input_fn, steps=1)
242 classifier.fit(input_fn=_input_fn, steps=5)
243 scores = classifier.evaluate(input_fn=_input_fn, steps=1)
[all …]
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| D | svm_test.py | 46 svm_classifier.fit(input_fn=input_fn, steps=30)
47 metrics = svm_classifier.evaluate(input_fn=input_fn, steps=1)
72 svm_classifier.fit(input_fn=input_fn, steps=30)
73 metrics = svm_classifier.evaluate(input_fn=input_fn, steps=1)
104 svm_classifier.fit(input_fn=input_fn, steps=30)
105 metrics = svm_classifier.evaluate(input_fn=input_fn, steps=1)
127 svm_classifier.fit(input_fn=input_fn, steps=30)
128 metrics = svm_classifier.evaluate(input_fn=input_fn, steps=1)
155 svm_classifier.fit(input_fn=input_fn, steps=30)
156 metrics = svm_classifier.evaluate(input_fn=input_fn, steps=1)
[all …]
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| D | dnn_test.py | 212 dnn_estimator.fit(input_fn=_input_fn_train, steps=5)
213 scores = dnn_estimator.evaluate(input_fn=_input_fn_eval, steps=1)
287 classifier.fit(input_fn=_input_fn_float_label, steps=50)
304 classifier.fit(input_fn=input_fn, steps=5)
305 scores = classifier.evaluate(input_fn=input_fn, steps=1)
327 classifier.fit(input_fn=_input_fn, steps=5)
328 scores = classifier.evaluate(input_fn=_input_fn, steps=1)
342 classifier.fit(x=train_x, y=train_y, steps=5)
343 scores = classifier.evaluate(x=train_x, y=train_y, steps=1)
395 classifier.fit(input_fn=_input_fn, steps=50)
[all …]
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| D | composable_model_test.py | 137 classifier.fit(input_fn=input_fn, steps=1000)
138 loss1 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
139 classifier.fit(input_fn=input_fn, steps=2000)
140 loss2 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
163 classifier.fit(input_fn=input_fn, steps=1000)
164 loss1 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
165 classifier.fit(input_fn=input_fn, steps=2000)
166 loss2 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
178 classifier.fit(input_fn=_iris_input_fn, steps=1000)
179 classifier.evaluate(input_fn=_iris_input_fn, steps=100)
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| D | estimator_test.py | 205 est.fit(input_fn=_input_fn, steps=20)
268 est.fit(input_fn=_input_fn, steps=1)
353 est.fit(input_fn=_make_input_fn(features, labels), steps=1)
388 est.fit(input_fn=_make_input_fn(features, labels), steps=1)
412 est.fit(input_fn=boston_input_fn, steps=1)
426 est.fit(input_fn=boston_input_fn, steps=1)
443 est.fit(input_fn=boston_input_fn, steps=1)
445 est.evaluate(input_fn=boston_eval_fn, steps=1)
459 est.fit(input_fn=boston_input_fn, steps=1)
461 est.evaluate(input_fn=boston_eval_fn, steps=1)
[all …]
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| /external/python/cpython3/Lib/ |
| D | pipes.py | 92 return '<Template instance, steps=%r>' % (self.steps,)
96 self.steps = []
102 t.steps = self.steps[:]
118 if self.steps and self.steps[-1][1] == SINK:
124 self.steps.append((cmd, kind))
134 if self.steps and self.steps[0][1] == SOURCE:
140 self.steps.insert(0, (cmd, kind))
155 if not self.steps:
157 if self.steps[-1][1] == SINK:
163 if not self.steps:
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| /external/python/cpython2/Lib/ |
| D | pipes.py | 90 return '<Template instance, steps=%r>' % (self.steps,)
94 self.steps = []
100 t.steps = self.steps[:]
119 if self.steps and self.steps[-1][1] == SINK:
128 self.steps.append((cmd, kind))
141 if self.steps and self.steps[0][1] == SOURCE:
150 self.steps.insert(0, (cmd, kind))
165 if not self.steps:
167 if self.steps[-1][1] == SINK:
174 if not self.steps:
[all …]
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| /external/tensorflow/tensorflow/contrib/linear_optimizer/python/ |
| D | sdca_estimator_test.py | 60 classifier.fit(input_fn=input_fn, steps=100)
61 loss = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
82 classifier.fit(input_fn=input_fn, steps=100)
83 loss = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
109 classifier.fit(input_fn=input_fn, steps=50)
110 metrics = classifier.evaluate(input_fn=input_fn, steps=1)
139 classifier.fit(input_fn=input_fn, steps=50)
140 metrics = classifier.evaluate(input_fn=input_fn, steps=1)
170 classifier.fit(input_fn=input_fn, steps=50)
171 metrics = classifier.evaluate(input_fn=input_fn, steps=1)
[all …]
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| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | training_distributed.py | 141 steps=None, argument
147 steps, batch_size = distributed_training_utils.get_input_params(
148 model._distribution_strategy, first_x_value, steps, batch_size)
149 batch_size = model._validate_or_infer_batch_size(batch_size, steps, x)
157 model, dataset, verbose=verbose, steps=steps, callbacks=callbacks)
164 steps=steps,
172 steps=None, argument
179 steps, batch_size = distributed_training_utils.get_input_params(
180 model._distribution_strategy, first_x_value, steps,
182 batch_size = model._validate_or_infer_batch_size(batch_size, steps, x)
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| D | training_generator_test.py | 121 steps=5,
127 steps=5,
131 steps=5,
147 steps=5,
152 steps=5,
156 steps=5,
161 steps=5,
166 steps=5,
170 steps=5,
200 steps=5,
[all …]
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| /external/libxml2/ |
| D | pattern.c | 104 xmlStreamStepPtr steps; /* the array of steps */ member
172 xmlStepOpPtr steps; /* ops for computation */ member
214 cur->steps = (xmlStepOpPtr) xmlMalloc(cur->maxStep * sizeof(xmlStepOp)); in xmlNewPattern()
215 if (cur->steps == NULL) { in xmlNewPattern()
243 if (comp->steps != NULL) { in xmlFreePattern()
246 op = &comp->steps[i]; in xmlFreePattern()
253 xmlFree(comp->steps); in xmlFreePattern()
353 temp = (xmlStepOpPtr) xmlRealloc(comp->steps, comp->maxStep * 2 * in xmlPatternAdd()
360 comp->steps = temp; in xmlPatternAdd()
363 comp->steps[comp->nbStep].op = op; in xmlPatternAdd()
[all …]
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| /external/tensorflow/tensorflow/contrib/kernel_methods/python/ |
| D | kernel_estimators_test.py | 88 input_fn=_linearly_separable_binary_input_fn, steps=100)
91 input_fn=_linearly_separable_binary_input_fn, steps=1)
119 input_fn=_linearly_inseparable_binary_input_fn, steps=50)
121 input_fn=_linearly_inseparable_binary_input_fn, steps=1)
141 input_fn=_linearly_inseparable_binary_input_fn, steps=50)
143 input_fn=_linearly_inseparable_binary_input_fn, steps=1)
157 input_fn=_linearly_inseparable_binary_input_fn, steps=50)
171 input_fn=_linearly_inseparable_binary_input_fn, steps=50)
211 linear_classifier.fit(input_fn=input_fn, steps=100)
212 linear_metrics = linear_classifier.evaluate(input_fn=input_fn, steps=1)
[all …]
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| /external/droiddriver/src/io/appium/droiddriver/actions/ |
| D | SwipeAction.java | 99 private final int steps; field in SwipeAction
108 public SwipeAction(PhysicalDirection direction, int steps) { in SwipeAction() argument
109 this(direction, steps, false, 1000L); in SwipeAction()
115 public SwipeAction(PhysicalDirection direction, int steps, boolean drag, long timeoutMillis) { in SwipeAction() argument
116 this(direction, steps, drag, timeoutMillis, 0.1F, 0.1F, 0.1F, 0.1F); in SwipeAction()
131 public SwipeAction(PhysicalDirection direction, int steps, boolean drag, long timeoutMillis, in SwipeAction() argument
135 this.steps = Math.max(2, steps); in SwipeAction()
189 double xStep = ((double) (endX - startX)) / steps; in perform()
190 double yStep = ((double) (endY - startY)) / steps; in perform()
198 for (int i = 1; i < steps; i++) { in perform()
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| /external/tensorflow/tensorflow/contrib/distribute/python/ |
| D | keras_test.py | 361 input_fn=get_ds_test_input_fn, steps=1)
362 est_keras.train(input_fn=get_ds_train_input_fn, steps=_TRAIN_SIZE / 16)
364 steps=1)
390 input_fn=get_ds_test_input_fn, steps=1)
391 est_keras.train(input_fn=get_ds_train_input_fn, steps=_TRAIN_SIZE / 16)
393 steps=1)
446 input_fn=eval_input_fn, steps=1)
447 est_keras.train(input_fn=train_input_fn, steps=_TRAIN_SIZE / 16)
448 eval_results = est_keras.evaluate(input_fn=eval_input_fn, steps=1)
471 est_keras.train(input_fn=get_ds_train_input_fn, steps=_TRAIN_SIZE / 16)
[all …]
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| D | keras_multi_worker_test.py | 261 steps = 10
264 train_ds, _ = _mnist_synthetic_dataset(batch_size, steps)
267 orig_loss, orig_acc = model.evaluate(train_ds, steps=steps)
273 model.fit(x=train_ds, epochs=2, steps_per_epoch=steps)
277 trained_loss, trained_acc = model.evaluate(train_ds, steps=steps)
362 steps = 10
363 train_ds, _ = _mnist_synthetic_dataset(batch_size, steps)
366 orig_loss, _ = model.evaluate(train_ds, steps=steps)
372 steps_per_epoch=steps,
375 trained_loss, _ = model.evaluate(train_ds, steps=steps)
[all …]
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| /external/tensorflow/tensorflow/contrib/boosted_trees/estimator_batch/ |
| D | estimator_test.py | 159 classifier.fit(input_fn=_train_input_fn, steps=15)
160 classifier.evaluate(input_fn=_eval_input_fn, steps=1)
179 classifier.fit(input_fn=_train_input_fn, steps=15)
206 model.fit(input_fn=_train_input_fn, steps=15)
207 model.evaluate(input_fn=_eval_input_fn, steps=1)
226 classifier.fit(input_fn=_train_input_fn, steps=15)
227 classifier.evaluate(input_fn=_eval_input_fn, steps=1)
246 regressor.fit(input_fn=_train_input_fn, steps=15)
247 regressor.evaluate(input_fn=_eval_input_fn, steps=1)
274 model.fit(input_fn=_ranking_train_input_fn, steps=1000)
[all …]
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| D | dnn_tree_combined_estimator_test.py | 86 classifier.fit(input_fn=_train_input_fn, steps=5)
108 classifier.fit(input_fn=_train_input_fn, steps=15)
109 classifier.evaluate(input_fn=_eval_input_fn, steps=1)
132 classifier.fit(input_fn=_train_input_fn, steps=15)
133 classifier.evaluate(input_fn=_eval_input_fn, steps=1)
166 est.train(input_fn=_train_input_fn, steps=1000)
169 res = est.evaluate(input_fn=_eval_input_fn, steps=1)
197 est.train(input_fn=_train_input_fn, steps=1000)
198 res = est.evaluate(input_fn=_eval_input_fn, steps=1)
228 est.train(input_fn=_train_input_fn, steps=1000)
[all …]
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| /external/skia/src/core/ |
| D | SkConvertPixels.cpp | 19 const SkColorSpaceXformSteps& steps) { in rect_memcpy() argument
25 && steps.flags.mask() != 0b00000) { in rect_memcpy()
36 const SkColorSpaceXformSteps& steps) { in swizzle_or_premul() argument
42 steps.flags.linearize || in swizzle_or_premul()
43 steps.flags.gamut_transform || in swizzle_or_premul()
44 steps.flags.unpremul || in swizzle_or_premul()
45 steps.flags.encode) { in swizzle_or_premul()
53 if (steps.flags.premul) { in swizzle_or_premul()
166 const SkColorSpaceXformSteps& steps) { in convert_with_pipeline() argument
173 steps.apply(&pipeline, srcInfo.colorType()); in convert_with_pipeline()
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| /external/skqp/src/core/ |
| D | SkConvertPixels.cpp | 19 const SkColorSpaceXformSteps& steps) { in rect_memcpy() argument
25 && steps.flags.mask() != 0b00000) { in rect_memcpy()
36 const SkColorSpaceXformSteps& steps) { in swizzle_or_premul() argument
42 steps.flags.linearize || in swizzle_or_premul()
43 steps.flags.gamut_transform || in swizzle_or_premul()
44 steps.flags.unpremul || in swizzle_or_premul()
45 steps.flags.encode) { in swizzle_or_premul()
53 if (steps.flags.premul) { in swizzle_or_premul()
165 const SkColorSpaceXformSteps& steps) { in convert_with_pipeline() argument
172 steps.apply(&pipeline, srcInfo.colorType()); in convert_with_pipeline()
[all …]
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| /external/tensorflow/tensorflow/contrib/tensor_forest/client/ |
| D | random_forest_test.py | 75 classifier.fit(input_fn=input_fn, steps=100)
76 res = classifier.evaluate(input_fn=input_fn, steps=10)
100 regressor.fit(input_fn=input_fn, steps=100)
101 res = regressor.evaluate(input_fn=input_fn, steps=10)
133 classifier.fit(input_fn=input_fn, steps=100)
162 classifier.fit(input_fn=input_fn, steps=100)
186 est.train(input_fn=input_fn, steps=100)
187 res = est.evaluate(input_fn=input_fn, steps=1)
215 regressor.train(input_fn=input_fn, steps=100)
216 res = regressor.evaluate(input_fn=input_fn, steps=10)
[all …]
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| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/ |
| D | estimators_test.py | 71 first_estimator.train(input_fn=train_input_fn, steps=1)
73 input_fn=eval_input_fn, steps=1)
77 first_estimator.train(input_fn=train_input_fn, steps=1)
79 input_fn=eval_input_fn, steps=1)["loss"]
82 second_estimator.train(input_fn=train_input_fn, steps=1)
86 input_fn=whole_dataset_input_fn, steps=1)
94 steps=10)
109 steps=10,
131 steps=1,
227 steps=1)
[all …]
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/ |
| D | experiment.py | 418 steps=self._eval_steps,
536 steps=self._eval_steps,
639 steps=self._eval_steps,
684 steps=self._eval_steps,
777 steps=train_steps_per_iteration,
786 steps=self._eval_steps,
832 steps=1,
838 steps=1,
866 steps=None, argument
880 steps=steps,
[all …]
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