/aosp12/hardware/interfaces/wifi/1.5/default/tests/ |
H A D | ringbuffer_unit_tests.cpp | 42 const std::vector<uint8_t> input2(maxBufferSize_ / 2, '1'); in TEST_F() local 44 buffer_.append(input2); in TEST_F() 47 EXPECT_EQ(input2, buffer_.getData().back()); in TEST_F() 52 const std::vector<uint8_t> input2(maxBufferSize_ / 2, '1'); in TEST_F() local 55 buffer_.append(input2); in TEST_F() 58 EXPECT_EQ(input2, buffer_.getData().front()); in TEST_F() 64 const std::vector<uint8_t> input2(maxBufferSize_ / 2, '1'); in TEST_F() local 67 buffer_.append(input2); in TEST_F() 87 const std::vector<uint8_t> input2(maxBufferSize_ + 1, '1'); in TEST_F() local 89 buffer_.append(input2); in TEST_F()
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/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/ |
H A D | concat_quant8_signed.mod.py | 21 input2 = Input("input2", "TENSOR_FLOAT32", "{2, 1, 2}") variable 26 model = Model().Operation("CONCATENATION", input0, input1, input2, input3, axis).To(output0) 32 input2: [1.2, -3.2, -4.2, 7.2], 38 input2: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.089, -5], 47 input2: [1.2, -3.2, -4.2, 7.2], 53 input2: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.089, -5], 85 input2 = Input("input2", "TENSOR_QUANT8_ASYMM_SIGNED", "{%d, %d}, 0.5f, -128" % (row2, col)) variable 88 model = model.Operation("CONCATENATION", input1, input2, axis0).To(output) 95 input2: [x - 128 for x in input2_values]} 115 model = model.Operation("CONCATENATION", input1, input2, axis1).To(output) [all …]
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H A D | select_quant8_signed.mod.py | 16 def test(name, input0, input1, input2, output0, input0_data, input1_data, input2_data, output_data): argument 17 model = Model().Operation("SELECT", input0, input1, input2).To(output0) 20 input2: ["TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -1], 26 input2: input2_data, 34 input2=Input("input2", "TENSOR_FLOAT32", "{3}"), 46 input2=Input("input2", "TENSOR_FLOAT32", "{2, 2}"), 58 input2=Input("input2", "TENSOR_FLOAT32", "{2, 1, 2, 1, 2}"),
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/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/ |
H A D | select_v1_2.mod.py | 16 def test(name, input0, input1, input2, output0, input0_data, input1_data, input2_data, output_data): argument 17 model = Model().Operation("SELECT", input0, input1, input2).To(output0) 20 input2: ["TENSOR_QUANT8_ASYMM", 0.5, 127], 26 input2: input2_data, 34 input2=Input("input2", "TENSOR_FLOAT32", "{3}"), 46 input2=Input("input2", "TENSOR_FLOAT32", "{2, 2}"), 58 input2=Input("input2", "TENSOR_FLOAT32", "{2, 1, 2, 1, 2}"),
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H A D | concat_mixed_quant.mod.py | 21 input2 = Input("input2", "TENSOR_FLOAT32", "{2, 1, 2}") variable 26 model = Model().Operation("CONCATENATION", input0, input1, input2, input3, axis).To(output0) 32 input2: [1.2, -3.2, -4.2, 7.2], 38 input2: ["TENSOR_QUANT8_ASYMM", 0.089, 123], 47 input2: [1.2, -3.2, -4.2, 7.2], 53 input2: ["TENSOR_QUANT8_ASYMM", 0.089, 123],
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H A D | concat_float16_2.mod.py | 26 input2 = Input("input2", "TENSOR_FLOAT16", "{%d, %d}" % (row2, col)) # input tensor 2 variable 29 model = model.Operation("CONCATENATION", input1, input2, axis0).To(output) 36 input2: input2_values}
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H A D | concat_float16_3.mod.py | 26 input2 = Input("input2", "TENSOR_FLOAT16", "{%d, %d}" % (row, col2)) # input tensor 2 variable 29 model = model.Operation("CONCATENATION", input1, input2, axis1).To(output) 35 input2: input2_values}
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/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_0/ |
H A D | concat_float_2.mod.py | 26 input2 = Input("input2", "TENSOR_FLOAT32", "{%d, %d}" % (row2, col)) # input tensor 2 variable 29 model = model.Operation("CONCATENATION", input1, input2, axis0).To(output) 36 input2: input2_values}
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H A D | concat_quant8_2.mod.py | 26 input2 = Input("input2", "TENSOR_QUANT8_ASYMM", "{%d, %d}, 0.5f, 0" % (row2, col)) variable 29 model = model.Operation("CONCATENATION", input1, input2, axis0).To(output) 36 input2: input2_values}
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H A D | concat_float_3.mod.py | 26 input2 = Input("input2", "TENSOR_FLOAT32", "{%d, %d}" % (row, col2)) # input tensor 2 variable 29 model = model.Operation("CONCATENATION", input1, input2, axis1).To(output) 35 input2: input2_values}
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H A D | concat_quant8_3.mod.py | 26 input2 = Input("input2", "TENSOR_QUANT8_ASYMM", "{%d, %d}, 0.5f, 0" % (row, col2)) variable 29 model = model.Operation("CONCATENATION", input1, input2, axis1).To(output) 35 input2: input2_values}
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/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_1/ |
H A D | concat_float_2_relaxed.mod.py | 26 input2 = Input("input2", "TENSOR_FLOAT32", "{%d, %d}" % (row2, col)) # input tensor 2 variable 29 model = model.Operation("CONCATENATION", input1, input2, axis0).To(output) 37 input2: input2_values}
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H A D | concat_float_3_relaxed.mod.py | 26 input2 = Input("input2", "TENSOR_FLOAT32", "{%d, %d}" % (row, col2)) # input tensor 2 variable 29 model = model.Operation("CONCATENATION", input1, input2, axis1).To(output) 36 input2: input2_values}
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/aosp12/art/compiler/optimizing/ |
H A D | register_allocator_test.cc | 539 *input2 = new (GetAllocator()) HInstanceFieldGet(parameter, in BuildIfElseWithPhi() 549 else_->AddInstruction(*input2); in BuildIfElseWithPhi() 552 (*phi)->AddInput(*input2); in BuildIfElseWithPhi() 561 HInstruction *input1, *input2; in PhiHint() local 564 HGraph* graph = BuildIfElseWithPhi(&phi, &input1, &input2); in PhiHint() 575 ASSERT_EQ(input2->GetLiveInterval()->GetRegister(), 0); in PhiHint() 580 HGraph* graph = BuildIfElseWithPhi(&phi, &input1, &input2); in PhiHint() 593 ASSERT_EQ(input2->GetLiveInterval()->GetRegister(), 2); in PhiHint() 598 HGraph* graph = BuildIfElseWithPhi(&phi, &input1, &input2); in PhiHint() 611 ASSERT_EQ(input2->GetLiveInterval()->GetRegister(), 2); in PhiHint() [all …]
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/aosp12/frameworks/base/opengl/java/android/opengl/ |
H A D | GLLogWrapper.java | 941 result.put(input2.get()); in toByteBuffer() 943 input2.position(position); in toByteBuffer() 953 result2.put(input2.get()); in toByteBuffer() 955 input2.position(position); in toByteBuffer() 965 result2.put(input2.get()); in toByteBuffer() 967 input2.position(position); in toByteBuffer() 977 result2.put(input2.get()); in toByteBuffer() 979 input2.position(position); in toByteBuffer() 991 input2.position(position); in toByteBuffer() 1003 input2.position(position); in toByteBuffer() [all …]
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/aosp12/bionic/tests/ |
H A D | math_data_test.h | 50 T2 input2; member 72 T2 input2; member 79 T2 input2; member 219 … data[i].expected, f(data[i].input1, data[i].input2)) << "Failed on element " << i; 283 out1 = f(data[i].input1, data[i].input2, &out2); 298 … data[i].expected, f(data[i].input1, data[i].input2, data[i].input3)) << "Failed on element " << i;
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/aosp12/frameworks/av/services/audiopolicy/common/managerdefinitions/src/ |
H A D | AudioProfileVectorHelper.cpp | 371 const T& input1, const T& input2, const Order& order) in intersectFilterAndOrder() argument 374 std::set<typename T::value_type> set2{input2.begin(), input2.end()}; in intersectFilterAndOrder() 389 const T& input1, const T& input2, Compare comp) in intersectAndOrder() argument 392 std::set<typename T::value_type, Compare> set2{input2.begin(), input2.end(), comp}; in intersectAndOrder()
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/aosp12/art/test/565-checker-doublenegbitwise/src/ |
H A D | Main.java | 39 public static <T> T $noinline$runSmaliTest(String name, Class<T> klass, T input1, T input2) { in $noinline$runSmaliTest() argument 44 return inputKlass.cast(m.invoke(null, input1, input2)); in $noinline$runSmaliTest()
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/aosp12/frameworks/base/tools/aapt2/format/ |
H A D | Archive_test.cpp | 124 auto input2 = std::make_unique<TestData>(data2_copy, kTestDataLength); in TEST_F() local 128 ASSERT_TRUE(writer->WriteFile("test2", 0, input2.get())); in TEST_F() 184 auto input2 = std::make_unique<TestData>(data2_copy, kTestDataLength); in TEST_F() local 188 ASSERT_TRUE(writer->WriteFile("test2", 0, input2.get())); in TEST_F()
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/aosp12/packages/modules/NeuralNetworks/common/operations/ |
H A D | LogicalAndOr.cpp | 76 Shape input2 = context->getInputShape(kInputTensor2); in prepare() local 78 NN_RET_CHECK(calculateBroadcastedShape(input1, input2, &output)); in prepare()
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H A D | Broadcast.cpp | 461 Shape input2 = context->getInputShape(kInputTensor2); in validate() local 462 NN_RET_CHECK_GT(output.scale, input1.scale * input2.scale); in validate() 474 const Shape& input2 = context->getInputShape(kInputTensor2); in validate() local 475 if (hasKnownRank(input1) && hasKnownRank(input2)) { in validate() 477 NN_RET_CHECK_LE(getNumberOfDimensions(input2), 4); in validate() 487 Shape input2 = context->getInputShape(kInputTensor2); in prepare() local 490 NN_RET_CHECK_LE(getNumberOfDimensions(input2), 4); in prepare() 491 NN_RET_CHECK(calculateBroadcastedShape(input1, input2, &output)); in prepare()
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H A D | Select.cpp | 98 Shape input2 = context->getInputShape(kInputTensor2); in prepare() local 99 NN_RET_CHECK(SameShape(input1, input2)); in prepare()
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/aosp12/packages/modules/NeuralNetworks/runtime/test/ |
H A D | TestIntrospectionControl.cpp | 250 float input2[2] = {3.0f, 4.0f}; in TEST_F() local 254 EXPECT_EQ(ANeuralNetworksExecution_setInput(mExecution, 1, nullptr, input2, sizeof(input2)), in TEST_F() 263 EXPECT_EQ(output[0], input1[0] + input2[0]); in TEST_F() 264 EXPECT_EQ(output[1], input1[1] + input2[1]); in TEST_F() 878 float input2[2] = {3.0f, 4.0f}; in TEST_P() local 882 EXPECT_EQ(ANeuralNetworksExecution_setInput(mExecution, 1, nullptr, input2, sizeof(input2)), in TEST_P() 1490 float input2[2] = {3.0f, 4.0f}; in TEST_F() local 1494 EXPECT_EQ(ANeuralNetworksExecution_setInput(mExecution, 1, nullptr, input2, sizeof(input2)), in TEST_F() 1501 EXPECT_EQ(output[0], kSimpleMultiplier * (input1[0] + input2[0])); in TEST_F() 1502 EXPECT_EQ(output[1], kSimpleMultiplier * (input1[1] + input2[1])); in TEST_F()
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/aosp12/packages/modules/NeuralNetworks/runtime/test/fibonacci_extension/ |
H A D | FibonacciExtensionTest.cpp | 290 uint32_t input2 = mModel.addOperand(&inputType); // Extra input. in TEST_F() local 294 {input1, input2}, {output}); in TEST_F() 295 mModel.identifyInputsAndOutputs({input1, input2}, {output}); in TEST_F()
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/aosp12/frameworks/base/cmds/hid/jni/ |
H A D | com_android_commands_hid_Device.cpp | 223 ev.u.input2.size = report.size(); in sendReport() 224 memcpy(&ev.u.input2.data, report.data(), report.size() * sizeof(ev.u.input2.data[0])); in sendReport()
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