Searched refs:val_a (Results 1 – 11 of 11) sorted by relevance
/external/tensorflow/tensorflow/python/keras/layers/ |
D | normalization_test.py | 443 val_a = np.random.random((10, 4)) 454 x1 = model.predict(val_a) 455 model.train_on_batch(val_a, val_out) 456 x2 = model.predict(val_a) 462 model.train_on_batch(val_a, val_out) 463 x2 = model.predict(val_a) 469 x1 = model.predict(val_a) 470 model.train_on_batch(val_a, val_out) 471 x2 = model.predict(val_a) 488 val_a = np.expand_dims(np.arange(10.), axis=1) [all …]
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/external/llvm/test/Analysis/ScalarEvolution/ |
D | overflow-intrinsics.ll | 284 define i32 @f_smul(i32 %val_a, i32 %val_b) { 286 %agg = tail call { i32, i1 } @llvm.smul.with.overflow.i32(i32 %val_a, i32 %val_b) 288 ; CHECK-NEXT: --> (%val_a * %val_b) U: full-set S: full-set 293 define i32 @f_umul(i32 %val_a, i32 %val_b) { 295 %agg = tail call { i32, i1 } @llvm.umul.with.overflow.i32(i32 %val_a, i32 %val_b) 297 ; CHECK-NEXT: --> (%val_a * %val_b) U: full-set S: full-set
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/external/tensorflow/tensorflow/python/keras/ |
D | models_test.py | 110 val_a = np.random.random((10, 4)) 146 input_a = keras.backend.variable(val_a) 166 val_a = np.random.random((10, 4)) 191 new_model.train_on_batch([val_a, val_b], val_out) 204 new_model.train_on_batch([val_a, val_b], val_out) 210 input_a = keras.backend.variable(val_a)
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/external/llvm-project/llvm/test/Analysis/ScalarEvolution/ |
D | overflow-intrinsics.ll | 285 define i32 @f_smul(i32 %val_a, i32 %val_b) { 287 %agg = tail call { i32, i1 } @llvm.smul.with.overflow.i32(i32 %val_a, i32 %val_b) 289 ; CHECK-NEXT: --> (%val_a * %val_b) U: full-set S: full-set 294 define i32 @f_umul(i32 %val_a, i32 %val_b) { 296 %agg = tail call { i32, i1 } @llvm.umul.with.overflow.i32(i32 %val_a, i32 %val_b) 298 ; CHECK-NEXT: --> (%val_a * %val_b) U: full-set S: full-set
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/external/tensorflow/tensorflow/python/keras/engine/ |
D | sequential_test.py | 238 val_a = np.random.random((10, 4)) 247 x1 = model.predict(val_a) 248 model.train_on_batch(val_a, val_out) 249 x2 = model.predict(val_a) 255 model.train_on_batch(val_a, val_out) 256 x2 = model.predict(val_a)
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D | training_test.py | 715 val_a = np.random.random((10, 4)) 734 x1 = model.predict(val_a) 735 model.train_on_batch(val_a, val_out) 736 x2 = model.predict(val_a) 747 model.train_on_batch(val_a, val_out) 748 x2 = model.predict(val_a) 759 x1 = model.predict(val_a) 760 model.train_on_batch(val_a, val_out) 761 x2 = model.predict(val_a)
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/external/libaom/libaom/test/ |
D | coding_path_sync.cc | 87 const int val_a = rnd_.Rand8(); in ReadFrame() local 91 buf[i] = (i + phase) % period < period / 2 ? val_a : val_b; in ReadFrame()
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/external/llvm-project/lldb/test/API/python_api/value/ |
D | TestValueAPI.py | 151 val_a = target.EvaluateExpression('a') 159 val_a.Cast(
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/external/icu/icu4c/source/test/perf/collperf/ |
D | collperf.cpp | 276 int val_a = 0; in q_random() local 278 while (*key_a != 0) {val_a += val_a*37 + *key_a++;} in q_random() 280 return val_a - val_b; in q_random()
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | padding_fifo_queue_test.py | 1121 val_a, val_b = self.evaluate([cleanup_dequeue_a_t, cleanup_dequeue_b_t]) 1122 self.assertEqual(elem_a, val_a)
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D | fifo_queue_test.py | 1180 val_a, val_b = self.evaluate([cleanup_dequeue_a_t, cleanup_dequeue_b_t]) 1181 self.assertEqual(elem_a, val_a)
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