/frameworks/ml/nn/runtime/test/specs/V1_2/ |
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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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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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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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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/frameworks/ml/nn/runtime/test/specs/V1_3/ |
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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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]} 112 input2 = Input("input2", "TENSOR_QUANT8_ASYMM_SIGNED", "{%d, %d}, 0.5f, -128" % (row, col2)) variable [all …]
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/frameworks/ml/nn/runtime/test/specs/V1_0/ |
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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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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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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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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/frameworks/ml/nn/runtime/test/specs/V1_1/ |
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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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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/frameworks/av/services/audiopolicy/common/managerdefinitions/src/ |
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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/frameworks/base/opengl/java/android/opengl/ |
D | GLLogWrapper.java | 934 ByteBuffer input2 = (ByteBuffer) input; in toByteBuffer() local 935 int position = input2.position(); in toByteBuffer() 937 byteCount = input2.limit() - position; in toByteBuffer() 939 result = ByteBuffer.allocate(byteCount).order(input2.order()); in toByteBuffer() 941 result.put(input2.get()); in toByteBuffer() 943 input2.position(position); in toByteBuffer() 945 CharBuffer input2 = (CharBuffer) input; in toByteBuffer() local 946 int position = input2.position(); in toByteBuffer() 948 byteCount = (input2.limit() - position) * 2; in toByteBuffer() 950 result = ByteBuffer.allocate(byteCount).order(input2.order()); in toByteBuffer() [all …]
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/frameworks/base/tools/aapt2/format/ |
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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/frameworks/ml/nn/common/operations/ |
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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D | Select.cpp | 101 Shape input2 = context->getInputShape(kInputTensor2); in prepare() local 102 NN_RET_CHECK(SameShape(input1, input2)); in prepare()
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D | Broadcast.cpp | 457 Shape input2 = context->getInputShape(kInputTensor2); in validate() local 458 NN_RET_CHECK_GT(output.scale, input1.scale * input2.scale); in validate() 470 const Shape& input2 = context->getInputShape(kInputTensor2); in validate() local 471 if (hasKnownRank(input1) && hasKnownRank(input2)) { in validate() 473 NN_RET_CHECK_LE(getNumberOfDimensions(input2), 4); in validate() 481 Shape input2 = context->getInputShape(kInputTensor2); in prepare() local 484 NN_RET_CHECK_LE(getNumberOfDimensions(input2), 4); in prepare() 485 NN_RET_CHECK(calculateBroadcastedShape(input1, input2, &output)); in prepare()
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D | Comparisons.cpp | 150 Shape input2 = context->getInputShape(kInputTensor2); in prepare() local 152 NN_RET_CHECK(calculateBroadcastedShape(input1, input2, &output)); in prepare()
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/frameworks/ml/nn/runtime/test/ |
D | TestIntrospectionControl.cpp | 245 float input2[2] = {3.0f, 4.0f}; in TEST_F() local 249 EXPECT_EQ(ANeuralNetworksExecution_setInput(mExecution, 1, nullptr, input2, sizeof(input2)), in TEST_F() 258 EXPECT_EQ(output[0], input1[0] + input2[0]); in TEST_F() 259 EXPECT_EQ(output[1], input1[1] + input2[1]); in TEST_F() 854 float input2[2] = {3.0f, 4.0f}; in TEST_P() local 858 EXPECT_EQ(ANeuralNetworksExecution_setInput(mExecution, 1, nullptr, input2, sizeof(input2)), in TEST_P() 1289 float input2[2] = {3.0f, 4.0f}; in TEST_F() local 1293 EXPECT_EQ(ANeuralNetworksExecution_setInput(mExecution, 1, nullptr, input2, sizeof(input2)), in TEST_F() 1300 EXPECT_EQ(output[0], kSimpleMultiplier * (input1[0] + input2[0])); in TEST_F() 1301 EXPECT_EQ(output[1], kSimpleMultiplier * (input1[1] + input2[1])); in TEST_F()
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D | TestMemoryDomain.cpp | 153 uint32_t input2 = model.addOperand(&tensorTypeFullySpecified); in createTestModel() local 161 model.addOperation(ANEURALNETWORKS_SUB, {input1, input2, act}, {temp}); in createTestModel() 163 model.identifyInputsAndOutputs({input0, input1, input2}, {output0, output1}); in createTestModel()
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D | TestValidateOperations.cpp | 1119 ANeuralNetworksOperandType input2 = { in gatherTest() local 1126 OperationTestBase test(ANEURALNETWORKS_GATHER, {input0, axis, input2}, {output}); in gatherTest() 1294 ANeuralNetworksOperandType input2 = input1; in simpleMathOpTest() local 1303 operationCode, {input1, input2, activation}, {output}, in simpleMathOpTest() 1384 ANeuralNetworksOperandType input2 = input1; in TEST() local 1387 input2.scale = 1.0f; in TEST() 1395 OperationTestBase mulTest(ANEURALNETWORKS_MUL, {input1, input2, activation}, {output}); in TEST() 1403 ANeuralNetworksOperandType input2 = input1; in binaryOpTest() local 1406 OperationTestBase test(operationCode, {input1, input2}, {output}); in binaryOpTest() 2425 ANeuralNetworksOperandType input2 = input1; in concatenationTest() local [all …]
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D | TestValidation.cpp | 1800 int32_t input2[] = {0}; in TEST_F() local 1805 EXPECT_EQ(ANeuralNetworksExecution_setInput(execution1, 2, nullptr, input2, sizeof(input2)), in TEST_F() 1845 int32_t input2[] = {0}; in TEST_F() local 1850 EXPECT_EQ(ANeuralNetworksExecution_setInput(execution, 2, nullptr, input2, sizeof(input2)), in TEST_F() 2095 int32_t input2[] = {0}; in TEST_F() local 2113 EXPECT_EQ(ANeuralNetworksExecution_setInput(execution, 2, nullptr, input2, sizeof(input2)), in TEST_F() 2137 int32_t input2[] = {0}; in TEST_F() local 2154 EXPECT_EQ(ANeuralNetworksExecution_setInput(execution, 2, nullptr, input2, sizeof(input2)), in TEST_F()
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/frameworks/ml/nn/runtime/test/fibonacci_extension/ |
D | FibonacciExtensionTest.cpp | 284 uint32_t input2 = mModel.addOperand(&inputType); // Extra input. in TEST_F() local 288 {input1, input2}, {output}); in TEST_F() 289 mModel.identifyInputsAndOutputs({input1, input2}, {output}); in TEST_F()
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/frameworks/base/cmds/hid/jni/ |
D | com_android_commands_hid_Device.cpp | 215 ev.u.input2.size = report.size(); in sendReport() 216 memcpy(&ev.u.input2.data, report.data(), report.size() * sizeof(ev.u.input2.data[0])); in sendReport()
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