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Searched refs:batch_size (Results 1 – 5 of 5) sorted by relevance

/frameworks/ml/nn/common/operations/
DSVDF.cpp66 const uint32_t batch_size = SizeOfDimension(input, 0); in Prepare() local
83 stateShape->dimensions = { batch_size, memory_size * num_filters }; in Prepare()
89 outputShape->dimensions = { batch_size, num_units }; in Prepare()
154 const int batch_size = SizeOfDimension(input_, 0); in EvalFloat32() local
160 memcpy(outputStateData, inputStateData, sizeof(float) * batch_size * memory_size * num_filters); in EvalFloat32()
162 for (int b = 0; b < batch_size; b++) { in EvalFloat32()
173 weightsFeatureData, num_filters, input_size, inputData, batch_size, in EvalFloat32()
180 float scratch[batch_size * num_filters]; in EvalFloat32()
181 for (int b = 0; b < batch_size; b++) { in EvalFloat32()
191 tflite::tensor_utils::VectorBatchVectorAssign(biasData, num_units, batch_size, outputData); in EvalFloat32()
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DMultinomial.cpp65 const uint32_t batch_size = SizeOfDimension(input, 0); in Prepare() local
70 outputShape->dimensions = {batch_size, sample_count}; in Prepare()
99 const int batch_size = SizeOfDimension(input_, 0); in EvalFloat32() local
111 random_generator.ReserveRandomOutputs(batch_size * sample_count_aligned, 256); in EvalFloat32()
114 for (uint64_t b = 0; b < batch_size; ++b) { in EvalFloat32()
DFullyConnected.cpp57 uint32_t batch_size = getSizeOfDimension(outputShape, 0); in fullyConnectedFloat32() local
59 if (batch_size * batch_size == input_n_elements) { in fullyConnectedFloat32()
216 uint32_t batch_size = input_n_elements / input_size; in prepare() local
218 NN_RET_CHECK_EQ(input_size * batch_size, input_n_elements); in prepare()
222 output.dimensions = {batch_size, num_units}; in prepare()
DRNN.cpp65 const uint32_t batch_size = SizeOfDimension(input, 0); in Prepare() local
76 hiddenStateShape->dimensions = { batch_size, num_units }; in Prepare()
80 outputShape->dimensions = { batch_size, num_units }; in Prepare()
149 const uint32_t batch_size = inputShape.dimensions[0]; in RNNStep() local
164 for (uint32_t b = 0; b < batch_size; b++) { in RNNStep()
DMultinomialTest.cpp39 MultinomialOpModel(uint32_t batch_size, uint32_t class_size, uint32_t sample_size) in MultinomialOpModel() argument
40 : batch_size_(batch_size), class_size_(class_size), sample_size_(sample_size) { in MultinomialOpModel()