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Searched refs:outputSize (Results 1 – 16 of 16) sorted by relevance

/packages/modules/NeuralNetworks/common/operations/
DQuantizedLSTMTest.cpp62 const uint32_t outputSize = in QuantizedLSTMOpModel() local
64 outputSize_ = outputSize; in QuantizedLSTMOpModel()
67 OperandType cellStateOutOperandType(Type::TENSOR_QUANT16_SYMM, {numBatches, outputSize}, in QuantizedLSTMOpModel()
70 OperandType outputOperandType(Type::TENSOR_QUANT8_ASYMM, {numBatches, outputSize}, in QuantizedLSTMOpModel()
83 cellStateOut_.resize(numBatches * outputSize, 0); in QuantizedLSTMOpModel()
84 output_.resize(numBatches * outputSize, 0); in QuantizedLSTMOpModel()
155 int outputSize() { return outputSize_; } in outputSize() function in android::nn::wrapper::QuantizedLSTMOpModel
256 const int outputSize = lstm->outputSize(); in VerifyGoldens() local
259 const uint8_t* goldenBatchStart = output[b].data() + i * outputSize; in VerifyGoldens()
260 const uint8_t* goldenBatchEnd = goldenBatchStart + outputSize; in VerifyGoldens()
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DQuantizedLSTM.cpp259 const uint32_t outputSize = SizeOfDimension(prevOutput, 1); in prepare() local
268 NN_RET_CHECK_EQ(SizeOfDimension(weights, 0), outputSize); in prepare()
287 NN_RET_CHECK(checkWeightsShape(recurrentToInputWeights, outputSize)); in prepare()
288 NN_RET_CHECK(checkWeightsShape(recurrentToForgetWeights, outputSize)); in prepare()
289 NN_RET_CHECK(checkWeightsShape(recurrentToCellWeights, outputSize)); in prepare()
290 NN_RET_CHECK(checkWeightsShape(recurrentToOutputWeights, outputSize)); in prepare()
300 NN_RET_CHECK_EQ(SizeOfDimension(bias, 0), outputSize); in prepare()
317 NN_CHECK_EQ(SizeOfDimension(prevCellState, 1), outputSize); in prepare()
351 const int outputSize = SizeOfDimension(inputToInputWeights_, 0); in concatenateWeights() local
353 assignWeightsSubmatrix(inputToInputWeights_, 0 * outputSize, outputSize, weightsDims, weights); in concatenateWeights()
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DQLSTM.cpp194 const uint32_t outputSize = getSizeOfDimension(recurrentToOutputShape, 1); in prepare() local
216 NN_RET_CHECK_EQ(getSizeOfDimension(recurrentToInputShape, 1), outputSize); in prepare()
222 NN_RET_CHECK_EQ(getSizeOfDimension(recurrentToForgetShape, 1), outputSize); in prepare()
226 NN_RET_CHECK_EQ(getSizeOfDimension(recurrentToCellShape, 1), outputSize); in prepare()
288 NN_RET_CHECK_EQ(getSizeOfDimension(projectionShape, 0), outputSize); in prepare()
295 NN_RET_CHECK_EQ(getSizeOfDimension(projectionBiasShape, 0), outputSize); in prepare()
301 NN_RET_CHECK_EQ(getSizeOfDimension(outputStateShape, 1), outputSize); in prepare()
395 const uint32_t outputSize = recurrentToOutputWeightsShape.dimensions[1]; in execute() local
682 outputSize, numUnits, in execute()
686 cellToForgetBuffer, outputSize, cellStateBuffer, batchSize, in execute()
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DUnidirectionalSequenceLSTM.cpp216 const uint32_t outputSize = getSizeOfDimension(recurrentToOutputShape, 1); in prepare() local
238 NN_RET_CHECK_EQ(getSizeOfDimension(recurrentToInputShape, 1), outputSize); in prepare()
244 NN_RET_CHECK_EQ(getSizeOfDimension(recurrentToForgetShape, 1), outputSize); in prepare()
248 NN_RET_CHECK_EQ(getSizeOfDimension(recurrentToCellShape, 1), outputSize); in prepare()
310 NN_RET_CHECK_EQ(getSizeOfDimension(projectionShape, 0), outputSize); in prepare()
317 NN_RET_CHECK_EQ(getSizeOfDimension(projectionBiasShape, 0), outputSize); in prepare()
323 NN_RET_CHECK_EQ(getSizeOfDimension(outputStateShape, 1), outputSize); in prepare()
378 outputShape.dimensions[2] = outputSize; in prepare()
387 outputStateOutTensor.dimensions[1] = outputSize; in prepare()
DLSTM.cpp438 const uint32_t outputSize = getSizeOfDimension(recurrent_to_output_weights_shape, 1); in LSTMEvalFloat32() local
443 const uint32_t batchOutputSize = batchSize * outputSize; in LSTMEvalFloat32()
462 transposedOutputShape.dimensions[2] = outputSize; in LSTMEvalFloat32()
470 output_state_in_buffer, output_state_in_buffer + batchSize * outputSize); in LSTMEvalFloat32()
507 output_state_out_buffer + batchSize * outputSize); in LSTMEvalFloat32()
558 const uint32_t outputSize = getSizeOfDimension(recurrent_to_output_weights_shape, 1); in LSTMEvalFloat16() local
563 const uint32_t batchOutputSize = batchSize * outputSize; in LSTMEvalFloat16()
578 std::vector<float> recurrent_to_input_weights_float32(numCells * outputSize); in LSTMEvalFloat16()
583 std::vector<float> recurrent_to_forget_weights_float32(numCells * outputSize); in LSTMEvalFloat16()
586 std::vector<float> recurrent_to_cell_weights_float32(numCells * outputSize); in LSTMEvalFloat16()
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DQuantizedLSTM.h89 void concatenateBiases(uint32_t outputSize, int32_t* bias);
DSlice.cpp56 const int outputSize = getNumberOfElements(outputShape); in evalGeneric() local
/packages/apps/Gallery2/src/com/android/gallery3d/filtershow/filters/
DImageFilterTinyPlanet.java79 int outputSize = (int) (w / 2f); in apply() local
90 if (outputSize != mBitmapOut.getHeight()) { in apply()
96 mBitmapOut = getEnvironment().getBitmap(outputSize, in apply()
97 outputSize, BitmapCache.TINY_PLANET); in apply()
100 outputSize /= 2; in apply()
105 outputSize, mParameters.getZoom() / 100f, mParameters.getAngle()); in apply()
/packages/modules/NeuralNetworks/runtime/test/
DTestMemoryInternal.cpp149 constexpr size_t outputSize = offsetForActual + sizeof(Matrix3x4); in TEST_F() local
150 int outputFd = ASharedMemory_create("output", outputSize); in TEST_F()
153 (uint8_t*)mmap(nullptr, outputSize, PROT_READ | PROT_WRITE, MAP_SHARED, outputFd, 0); in TEST_F()
155 memset(outputData, 0, outputSize); in TEST_F()
156 WrapperMemory actual(outputSize, PROT_READ | PROT_WRITE, outputFd, 0); in TEST_F()
174 munmap(outputData, outputSize); in TEST_F()
DTestValidateOperations.cpp4070 const uint32_t outputSize = 6; in unidirectionalSequenceLSTMTest() local
4074 uint32_t recurrentWeightsDims[2] = {numUnits, outputSize}; in unidirectionalSequenceLSTMTest()
4076 uint32_t projectionDims[2] = {outputSize, numUnits}; in unidirectionalSequenceLSTMTest()
4077 uint32_t projectionBiasDims[1] = {outputSize}; in unidirectionalSequenceLSTMTest()
4078 uint32_t outputStateDims[2] = {batchSize, outputSize}; in unidirectionalSequenceLSTMTest()
4081 uint32_t outputDims[3] = {maxTime, batchSize, outputSize}; in unidirectionalSequenceLSTMTest()
/packages/modules/NeuralNetworks/runtime/test/android_fuzzing/
DDriverFuzzTest.cpp201 size_t outputSize = 0; in createRequest() local
214 .offset = static_cast<uint32_t>(outputSize), in createRequest()
216 outputSize += op.data.size() == 0 ? TestBuffer::kAlignment : op.data.alignedSize(); in createRequest()
224 outputSize = std::max<size_t>(outputSize, 1); in createRequest()
225 auto outputMemory = nn::allocateSharedMemory(outputSize); in createRequest()
/packages/apps/Messaging/src/com/android/messaging/util/
DGifTranscoder.java52 final long outputSize = new File(outFilePath).length(); in transcode() local
53 final float compression = (inputSize > 0) ? ((float) outputSize / inputSize) : 0; in transcode()
60 Formatter.formatShortFileSize(context, outputSize), in transcode()
/packages/modules/NeuralNetworks/runtime/test/fuzzing/operation_signatures/
DSelection.cpp252 int32_t outputSize = op->outputs[0]->dimensions[i].getValue(); in sliceFinalizer() local
254 begin[i] = getUniform<int32_t>(0, inputSize - outputSize); in sliceFinalizer()
255 size[i] = outputSize; in sliceFinalizer()
325 int32_t outputSize = op->outputs[0]->dimensions[o++].getValue(); in stridedSliceFinalizer() local
326 int32_t maxStart = inputSize - (outputSize - 1) * stride - 1; in stridedSliceFinalizer()
329 int32_t minEnd = begin[i] + (outputSize - 1) * stride + 1; in stridedSliceFinalizer()
330 int32_t maxEnd = std::min(begin[i] + outputSize * stride, inputSize); in stridedSliceFinalizer()
/packages/apps/Camera2/src/com/android/camera/tinyplanet/
DTinyPlanetFragment.java349 int outputSize = width / 2; in createFinalTinyPlanet() local
350 Bitmap resultBitmap = Bitmap.createBitmap(outputSize, outputSize, in createFinalTinyPlanet()
354 outputSize, mCurrentZoom, mCurrentAngle); in createFinalTinyPlanet()
363 return new TinyPlanetImage(addExif(jpeg.toByteArray()), outputSize); in createFinalTinyPlanet()
DTinyPlanetNative.java40 public static native void process(Bitmap in, int width, int height, Bitmap out, int outputSize, in process() argument
/packages/modules/NeuralNetworks/tools/api/
Dtypes.spec4983 * and shape [outputSize, inputSize] specifying input-to-input part of
4989 * and shape [outputSize, inputSize] specifying input-to-forget part of
4995 * and shape [outputSize, inputSize] specifying input-to-cell part of
5001 * and shape [outputSize, inputSize] specifying input-to-output part of
5007 * and shape [outputSize, outputSize] specifying recurrent-to-input part
5013 * and shape [outputSize, outputSize] specifying recurrent-to-forget
5019 * and shape [outputSize, outputSize] specifying recurrent-to-cell part
5025 * and shape [outputSize, outputSize] specifying recurrent-to-output
5031 * [outputSize] specifying the bias for the fully-connected layer
5036 * [outputSize] specifying the bias for the fully-connected layer
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