| /hardware/interfaces/neuralnetworks/1.3/ |
| D | IBuffer.hal | 45 * @param dimensions Updated dimensional information. If the dimensions of the IBuffer object
46 * are not fully specified, then the dimensions must be fully specified here. If the
47 * dimensions of the IBuffer object are fully specified, then the dimensions may be empty
48 * here. If dimensions.size() > 0, then all dimensions must be specified here, and any
54 * - INVALID_ARGUMENT if provided memory is invalid, or if the dimensions is invalid
56 copyFrom(memory src, vec<uint32_t> dimensions) generates (ErrorStatus status);
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| /hardware/interfaces/neuralnetworks/1.2/utils/src/ |
| D | ExecutionBurstUtils.cpp | 75 count += input.dimensions.size(); in serialize()
78 count += output.dimensions.size(); in serialize()
101 .numberOfDimensions = static_cast<uint32_t>(input.dimensions.size())}); in serialize()
104 for (uint32_t dimension : input.dimensions) { in serialize()
117 .numberOfDimensions = static_cast<uint32_t>(output.dimensions.size())}); in serialize()
120 for (uint32_t dimension : output.dimensions) { in serialize()
149 count += outputShape.dimensions.size(); in serialize()
168 .numberOfDimensions = static_cast<uint32_t>(operand.dimensions.size())}); in serialize()
171 for (uint32_t dimension : operand.dimensions) { in serialize()
230 std::vector<uint32_t> dimensions; in deserialize() local
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| /hardware/interfaces/neuralnetworks/1.1/ |
| D | types.hal | 33 * dimensions of shape block_shape + [batch], interleaves these blocks back
34 * into the grid defined by the spatial dimensions [1, ..., M], to obtain a
63 * dimensions. The output is the result of dividing the first input tensor
66 * Two dimensions are compatible when:
71 * input operands. It starts with the trailing dimensions, and works its way
86 * * 1: A tensor of the same {@link OperandType}, and compatible dimensions
98 * Computes the mean of elements across dimensions of a tensor.
100 * Reduces the input tensor along the given dimensions to reduce. Unless
102 * in axis. If keep_dims is true, the reduced dimensions are retained with
113 * * 1: A 1-D Tensor of {@link OperandType::TENSOR_INT32}. The dimensions
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| /hardware/interfaces/neuralnetworks/1.0/vts/functional/ |
| D | BasicTests.cpp | 81 .dimensions = {1}, in TEST_P()
91 .dimensions = {1}, in TEST_P()
101 .dimensions = {}, in TEST_P()
111 .dimensions = {1}, in TEST_P()
121 .dimensions = {1}, in TEST_P()
131 .dimensions = {1}, in TEST_P()
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| D | Utils.cpp | 118 inputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}}; in createRequest()
140 outputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}}; in createRequest()
213 if (isTensor(operand.type) && operand.dimensions.size() == 0) return 0; in sizeOfData()
214 return std::accumulate(operand.dimensions.begin(), operand.dimensions.end(), dataSize, in sizeOfData()
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| /hardware/interfaces/neuralnetworks/1.1/vts/functional/ |
| D | BasicTests.cpp | 88 .dimensions = {1}, in TEST_P()
98 .dimensions = {1}, in TEST_P()
108 .dimensions = {}, in TEST_P()
118 .dimensions = {1}, in TEST_P()
128 .dimensions = {1}, in TEST_P()
138 .dimensions = {1}, in TEST_P()
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| /hardware/interfaces/neuralnetworks/utils/adapter/src/ |
| D | Buffer.cpp | 50 const hidl_vec<uint32_t>& dimensions) { in copyFrom() argument
52 NN_TRY(buffer->copyFrom(memory, dimensions)); in copyFrom()
73 const hidl_vec<uint32_t>& dimensions) { in copyFrom() argument
74 auto result = adapter::copyFrom(kBuffer, src, dimensions); in copyFrom()
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| /hardware/interfaces/neuralnetworks/aidl/vts/functional/ |
| D | BasicTests.cpp | 94 .dimensions = {1}, in TEST_P()
103 .dimensions = {1}, in TEST_P()
112 .dimensions = {}, in TEST_P()
121 .dimensions = {1}, in TEST_P()
130 .dimensions = {1}, in TEST_P()
139 .dimensions = {1}, in TEST_P()
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| D | MemoryDomainTests.cpp | 78 static_cast<nn::OperandType>(operand.type), operand.dimensions); in createDummyData()
90 .dimensions = {}, in createInt32Scalar()
106 .dimensions = {operand.dimensions[3], 3, 3, operand.dimensions[3]}, in createConvModel()
114 .dimensions = {operand.dimensions[3]}, in createConvModel()
161 .dimensions = {}, in createSingleAddModel()
231 kTestOperand.dimensions)) {} in MemoryDomainTestBase()
270 .dimensions = {1, 32, 32, 8},
279 .dimensions = {1, 32, 32, 8},
288 .dimensions = {1, 32, 32, 8},
297 .dimensions = {1, 32, 32, 8},
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| /hardware/interfaces/neuralnetworks/1.3/vts/functional/ |
| D | BasicTests.cpp | 103 .dimensions = {1}, in TEST_P()
113 .dimensions = {1}, in TEST_P()
123 .dimensions = {}, in TEST_P()
133 .dimensions = {1}, in TEST_P()
143 .dimensions = {1}, in TEST_P()
153 .dimensions = {1}, in TEST_P()
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| D | Utils.cpp | 82 if (isTensor(operand.type) && operand.dimensions.size() == 0) return 0; in sizeOfData()
83 return std::accumulate(operand.dimensions.begin(), operand.dimensions.end(), dataSize, in sizeOfData()
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| /hardware/interfaces/neuralnetworks/1.2/vts/functional/ |
| D | Utils.cpp | 78 if (isTensor(operand.type) && operand.dimensions.size() == 0) return 0; in sizeOfData()
79 return std::accumulate(operand.dimensions.begin(), operand.dimensions.end(), dataSize, in sizeOfData()
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| D | BasicTests.cpp | 162 .dimensions = {1}, in TEST_P()
172 .dimensions = {1}, in TEST_P()
182 .dimensions = {}, in TEST_P()
192 .dimensions = {1}, in TEST_P()
202 .dimensions = {1}, in TEST_P()
212 .dimensions = {1}, in TEST_P()
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| /hardware/interfaces/neuralnetworks/utils/common/src/ |
| D | ResilientBuffer.cpp | 108 const nn::Dimensions& dimensions) const { in copyFrom()
109 const auto fn = [&src, &dimensions](const nn::IBuffer& buffer) { in copyFrom()
110 return buffer.copyFrom(src, dimensions); in copyFrom()
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| /hardware/interfaces/neuralnetworks/aidl/utils/src/ |
| D | Buffer.cpp | 68 const nn::Dimensions& dimensions) const { in copyFrom()
70 const auto aidlDimensions = NN_TRY(toSigned(dimensions)); in copyFrom()
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| /hardware/interfaces/neuralnetworks/1.3/utils/src/ |
| D | Buffer.cpp | 75 const nn::Dimensions& dimensions) const { in copyFrom()
77 const auto hidlDimensions = hidl_vec<uint32_t>(dimensions); in copyFrom()
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| /hardware/interfaces/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/ |
| D | BufferDesc.aidl | 37 int[] dimensions;
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| D | OutputShape.aidl | 37 int[] dimensions;
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| D | RequestArgument.aidl | 39 int[] dimensions;
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| /hardware/interfaces/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/1/android/hardware/neuralnetworks/ |
| D | BufferDesc.aidl | 37 int[] dimensions;
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| D | OutputShape.aidl | 37 int[] dimensions;
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| D | RequestArgument.aidl | 39 int[] dimensions;
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| /hardware/interfaces/neuralnetworks/aidl/android/hardware/neuralnetworks/ |
| D | BufferDesc.aidl | 29 int[] dimensions;
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| D | OutputShape.aidl | 27 int[] dimensions;
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| /hardware/interfaces/neuralnetworks/1.0/utils/src/ |
| D | Conversions.cpp | 129 .dimensions = operand.dimensions, in unvalidatedConvert()
188 .dimensions = argument.dimensions, in unvalidatedConvert()
313 .dimensions = operand.dimensions, in unvalidatedConvert()
375 .dimensions = requestArgument.dimensions, in unvalidatedConvert()
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