| /external/lz4/tests/ |
| datagencli.c | 80 double proba = (double)COMPRESSIBILITY_DEFAULT / 100; local
130 proba=0.0;
133 proba *= 10;
134 proba += *argument - '0';
137 if (proba>100.) proba=100.;
138 proba /= 100.;
166 if (proba!=COMPRESSIBILITY_DEFAULT) DISPLAYLEVEL(3, "Compressibility : %i%%\n", (U32)(proba*100));
168 RDG_genOut(size, proba, litProba, seed)
[all...] |
| frametest.c | 124 static void FUZ_fillCompressibleNoiseBuffer(void* buffer, size_t bufferSize, double proba, U32* seed)
128 U32 P32 = (U32)(32768 * proba);
751 int proba = FUZ_COMPRESSIBILITY_DEFAULT; local
[all...] |
| fuzzer.c | 122 static void FUZ_fillCompressibleNoiseBuffer(void* buffer, size_t bufferSize, double proba, U32* seed)
126 U32 const P32 = (U32)(32768 * proba);
992 int proba = FUZ_COMPRESSIBILITY_DEFAULT; local
[all...] |
| /external/webp/src/enc/ |
| cost_enc.h | 44 // Record proba context used.
58 // Cost of coding one event with probability 'proba'.
59 static WEBP_INLINE int VP8BitCost(int bit, uint8_t proba) {
60 return !bit ? VP8EntropyCost[proba] : VP8EntropyCost[255 - proba];
65 void VP8CalculateLevelCosts(VP8EncProba* const proba);
|
| frame_enc.c | 92 // Reset the statistics about: number of skips, token proba, level cost,...
95 VP8EncProba* const proba = &enc->proba_; local
96 VP8CalculateLevelCosts(proba);
97 proba->nb_skip_ = 0;
111 VP8EncProba* const proba = &enc->proba_; local
113 const int nb_events = proba->nb_skip_;
115 proba->skip_proba_ = CalcSkipProba(nb_events, nb_mbs);
116 proba->use_skip_proba_ = (proba->skip_proba_ < SKIP_PROBA_THRESHOLD);
118 if (proba->use_skip_proba_)
139 VP8EncProba* const proba = &enc->proba_; local
766 VP8EncProba* const proba = &enc->proba_; local
[all...] |
| cost_enc.c | 60 void VP8CalculateLevelCosts(VP8EncProba* const proba) {
63 if (!proba->dirty_) return; // nothing to do.
69 const uint8_t* const p = proba->coeffs_[ctype][band][ctx];
70 uint16_t* const table = proba->level_cost_[ctype][band][ctx];
84 proba->remapped_costs_[ctype][n][ctx] =
85 proba->level_cost_[ctype][VP8EncBands[n]][ctx];
89 proba->dirty_ = 0;
|
| token_enc.c | 34 // bit #14: flags for constant proba or idx
35 // bits #0..13: slot or constant proba
104 uint32_t bit, uint32_t proba) {
105 assert(proba < 256);
109 b->tokens_[slot] = (bit << 15) | FIXED_PROBA_BIT | proba;
213 VP8PutBit(bw, bit, token & 0xffu); // constant proba
|
| syntax_enc.c | 190 const VP8EncProba* const proba = &enc->proba_; local
208 if (VP8PutBitUniform(bw, (proba->segments_[s] != 255u))) {
209 VP8PutBits(bw, proba->segments_[s], 8);
284 VP8PutBitUniform(bw, 0); // no proba update
|
| /external/webp/src/dec/ |
| tree_dec.c | 284 void VP8ResetProba(VP8Proba* const proba) {
285 memset(proba->segments_, 255u, sizeof(proba->segments_));
286 // proba->bands_[][] is initialized later
511 VP8Proba* const proba = &dec->proba_; local
519 proba->bands_[t][b].probas_[c][p] = v;
524 proba->bands_ptr_[t][b] = &proba->bands_[t][kBands[b]];
|
| vp8i_dec.h | 275 void VP8ResetProba(VP8Proba* const proba);
|
| vp8_dec.c | 161 VP8SegmentHeader* hdr, VP8Proba* proba) {
180 proba->segments_[s] = VP8Get(br) ? VP8GetValue(br, 8) : 255u;
|
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| target_column.py | 163 def logits_to_predictions(self, logits, proba=False):
271 def logits_to_predictions(self, logits, proba=False):
280 predictions = self.logits_to_predictions(logits, proba=False)
301 def logits_to_predictions(self, logits, proba=False):
305 if proba:
354 class_predictions = self.logits_to_predictions(logits, proba=False)
359 predictions = self.logits_to_predictions(logits, proba=True)
386 def logits_to_predictions(self, logits, proba=False):
387 if proba:
|
| /external/tensorflow/tensorflow/python/keras/_impl/keras/wrappers/ |
| scikit_learn_test.py | 67 proba = clf.predict_proba(x_test, batch_size=BATCH_SIZE)
68 assert proba.shape == (TEST_SAMPLES, NUM_CLASSES)
69 assert np.allclose(np.sum(proba, axis=1), np.ones(TEST_SAMPLES))
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| quantized_distribution_test.py | 336 proba = qdist.log_prob(x)
337 grads = gradients_impl.gradients(proba, [mu, sigma])
340 self._assert_all_finite(proba.eval())
355 proba = qdist.prob(x)
356 self._assert_all_finite(proba.eval())
358 grads = gradients_impl.gradients(proba, [mu, sigma])
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| rnn_common.py | 281 flattened_activations, proba=True)
295 flattened_activations, proba=False)
|
| dynamic_rnn_estimator.py | 291 last_activations, proba=True)
297 last_activations, proba=False)
|
| dynamic_rnn_estimator_test.py | 77 def logits_to_predictions(self, flattened_activations, proba=False):
|
| /external/tensorflow/tensorflow/python/keras/_impl/keras/ |
| models.py | [all...] |
| /external/libvpx/libvpx/vp8/encoder/ |
| bitstream.c | 195 const unsigned char *proba = b->prob; local
202 split = 1 + (((range - 1) * proba[i >> 1]) >> 8);
[all...] |
