Searched refs:quantiles (Results 1 - 21 of 21) sorted by relevance

/external/ltp/testcases/realtime/include/
H A Dlibstats.h72 long *quantiles; member in struct:stats_quantiles
122 /* stats_container_init - allocate memory for new quantiles
124 * quantiles: stats_quantiles_t destination pointer
126 int stats_quantiles_init(stats_quantiles_t *quantiles, int nines);
128 /* stats_quantiles_free - free the quantiles array
131 int stats_quantiles_free(stats_quantiles_t *quantiles);
133 /* stats_quantiles_calc - calculate the quantiles of the supplied container
135 * quantiles: stats_quantiles_t structure for storing the results
137 int stats_quantiles_calc(stats_container_t *data, stats_quantiles_t *quantiles);
139 /* stats_quantiles_print - print the quantiles store
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/external/tensorflow/tensorflow/contrib/boosted_trees/lib/quantiles/
H A Dweighted_quantiles_buffer_test.cc15 #include "tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_buffer.h"
26 boosted_trees::quantiles::WeightedQuantilesBuffer<double, double>;
28 boosted_trees::quantiles::WeightedQuantilesBuffer<double,
36 boosted_trees::quantiles::WeightedQuantilesBuffer<double, double>
42 boosted_trees::quantiles::WeightedQuantilesBuffer<double, double>
H A Dweighted_quantiles_summary_test.cc15 #include "tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_summary.h"
25 using Buffer = boosted_trees::quantiles::WeightedQuantilesBuffer<float, float>;
27 boosted_trees::quantiles::WeightedQuantilesBuffer<float,
30 boosted_trees::quantiles::WeightedQuantilesSummary<float, float>;
32 boosted_trees::quantiles::WeightedQuantilesSummary<float,
H A Dweighted_quantiles_stream_test.cc15 #include "tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_stream.h"
27 boosted_trees::quantiles::WeightedQuantilesSummary<double, double>;
29 boosted_trees::quantiles::WeightedQuantilesSummary<double,
32 boosted_trees::quantiles::WeightedQuantilesStream<double, double>;
124 // Verify expected quantiles.
214 // Verify expected quantiles.
H A Dweighted_quantiles_buffer.h27 namespace quantiles { namespace in namespace:tensorflow::boosted_trees
128 } // namespace quantiles
H A Dweighted_quantiles_stream.h22 #include "tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_buffer.h"
23 #include "tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_summary.h"
28 namespace quantiles { namespace in namespace:tensorflow::boosted_trees
30 // Class to compute approximate quantiles with error bound guarantees for
36 // * (2007) A fast algorithm for approximate quantiles in high speed
139 // Generates requested number of quantiles after finalizing stream.
140 // The returned quantiles can be queried using std::lower_bound to get
145 << "Finalize() must be called before generating quantiles.";
153 // necessarily represent the actual quantiles of the distribution.
154 // Boundaries are preferable over quantiles whe
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H A Dweighted_quantiles_summary.h21 #include "tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_buffer.h"
25 namespace quantiles { namespace in namespace:tensorflow::boosted_trees
257 // To construct the desired n-quantiles we repetitively query n ranks from the
333 } // namespace quantiles
/external/ltp/testcases/realtime/lib/
H A Dlibstats.c206 int stats_quantiles_init(stats_quantiles_t * quantiles, int nines) argument
211 quantiles->nines = nines;
212 /* allocate space for quantiles, starting with 0.99 (two nines) */
213 quantiles->quantiles = calloc(sizeof(long), (nines - 1));
214 if (!quantiles->quantiles) {
220 int stats_quantiles_free(stats_quantiles_t * quantiles) argument
222 free(quantiles->quantiles);
226 stats_quantiles_calc(stats_container_t * data, stats_quantiles_t * quantiles) argument
249 stats_quantiles_print(stats_quantiles_t * quantiles) argument
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/external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/
H A Dtest_data.py28 quantiles = np.percentile(
31 return list(quantiles)
/external/ltp/testcases/realtime/func/periodic_cpu_load/
H A Dperiodic_cpu_load.c68 stats_quantiles_t quantiles[THREADS_PER_GROUP * NUM_GROUPS]; variable
199 stats_quantiles_init(&quantiles[i], (int)log10(iterations));
227 stats_quantiles_calc(&dat[i], &quantiles[i]);
228 stats_quantiles_print(&quantiles[i]);
243 stats_quantiles_free(&quantiles[i]);
H A Dperiodic_cpu_load_single.c90 stats_quantiles_t quantiles; local
102 stats_quantiles_init(&quantiles, (int)log10(iterations));
155 stats_quantiles_calc(&dat, &quantiles);
156 stats_quantiles_print(&quantiles);
/external/ltp/testcases/realtime/func/hrtimer-prio/
H A Dhrtimer-prio.c181 stats_quantiles_t quantiles; local
190 if (stats_quantiles_init(&quantiles, (int)log10(iterations))) {
191 printf("Cannot init stat quantiles\n");
224 stats_quantiles_calc(&dat, &quantiles);
225 stats_quantiles_print(&quantiles);
/external/tensorflow/tensorflow/contrib/distributions/python/ops/
H A Dpoisson_lognormal.py91 """Use LogNormal quantiles to form quadrature on positive-reals.
124 """Helper to build quantiles."""
131 quantiles = dist.quantile(edges)
135 quantiles = array_ops.transpose(quantiles, perm)
136 return quantiles
137 quantiles = _compute_quantiles()
140 grid = (quantiles[..., :-1] + quantiles[..., 1:]) / 2.
167 By default, the `grid` is chosen as quantiles o
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H A Dvector_diffeomixture.py117 """Use SoftmaxNormal quantiles to form quadrature on `K - 1` simplex.
176 """Helper to build quantiles."""
183 quantiles = dist.quantile(edges)
184 quantiles = SoftmaxCentered(event_ndims=1).forward(quantiles)
188 quantiles = array_ops.transpose(quantiles, perm)
189 quantiles.set_shape(_get_final_shape(quadrature_size + 1))
190 return quantiles
191 quantiles
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/external/ltp/testcases/realtime/func/gtod_latency/
H A Dgtod_latency.c235 stats_quantiles_t quantiles; local
253 stats_quantiles_init(&quantiles, (int)log10(iterations));
349 stats_quantiles_calc(&dat, &quantiles);
350 stats_quantiles_print(&quantiles);
354 stats_quantiles_free(&quantiles);
/external/ltp/testcases/realtime/func/sched_latency/
H A Dsched_latency.c76 stats_quantiles_t quantiles; variable
234 stats_quantiles_calc(&dat, &quantiles);
235 stats_quantiles_print(&quantiles);
282 /* use the highest value for the quantiles */
283 if (stats_quantiles_init(&quantiles, (int)log10(iterations))) {
301 stats_quantiles_free(&quantiles);
/external/ltp/testcases/realtime/func/pthread_kill_latency/
H A Dpthread_kill_latency.c121 stats_quantiles_t quantiles; local
126 stats_quantiles_init(&quantiles, (int)log10(ITERATIONS));
216 stats_quantiles_calc(&dat, &quantiles);
217 stats_quantiles_print(&quantiles);
/external/tensorflow/tensorflow/contrib/boosted_trees/resources/
H A Dquantile_stream_resource.h18 #include "tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_stream.h"
19 #include "tensorflow/contrib/boosted_trees/proto/quantiles.pb.h" // NOLINT
29 boosted_trees::quantiles::WeightedQuantilesStream<float, float>;
106 // Generate quantiles instead of approximate boundaries.
/external/tensorflow/tensorflow/contrib/boosted_trees/lib/learner/batch/
H A Dordinal_split_handler.py29 Weighted quantiles of the feature columns are computed in a distributed fashion
435 """Branch to execute when quantiles are ready."""
436 quantized_feature = quantile_ops.quantiles([float_column], [],
465 """The subgraph for when the quantiles are ready."""
466 quantized_feature = quantile_ops.quantiles([], [sparse_column_values], [],
509 """The subgraph for when the quantiles are not ready."""
/external/tensorflow/tensorflow/contrib/boosted_trees/kernels/
H A Dquantile_ops.cc20 #include "tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_stream.h"
23 #include "tensorflow/contrib/boosted_trees/proto/quantiles.pb.h"
72 boosted_trees::quantiles::WeightedQuantilesStream<float, float>;
74 boosted_trees::quantiles::WeightedQuantilesSummary<float, float>;
76 boosted_trees::quantiles::WeightedQuantilesSummary<float,
172 // Generates quantiles on a finalized QuantileStream.
183 // Generates quantiles on a finalized QuantileStream.
193 // Copies quantiles to output list.
855 // Given the calculated quantiles thresholds and input data, this operation
/external/tensorflow/tensorflow/contrib/boosted_trees/python/kernel_tests/
H A Dquantile_ops_test.py70 # Multi-dimensional feature that should have the same quantiles as Sparse 0.
215 # By default, use 3 quantiles, 4 boundaries for simplicity.
537 dense_quantiles, _ = quantile_ops.quantiles(
550 _, sparse_quantiles = quantile_ops.quantiles([], [
575 dense_quantiles, sparse_quantiles = quantile_ops.quantiles(

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