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Searched refs:num_units (Results 1 – 13 of 13) sorted by relevance

/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/
H A Dunidirectional_sequence_rnn.mod.py50 num_units = 16 variable
182 "{{{}, {}}}".format(num_units, input_size)),
184 "{{{}, {}}}".format(num_units, num_units)),
185 bias=Input("bias", "TENSOR_FLOAT32", "{{{}}}".format(num_units)),
187 "{{{}, {}}}".format(num_batches, num_units)),
198 hidden_state_data=[0] * num_batches * num_units,
208 "{{{}, {}}}".format(num_units, input_size)),
210 "{{{}, {}}}".format(num_units, num_units)),
213 "{{{}, {}}}".format(num_batches, num_units)),
225 hidden_state_data=[0] * num_batches * num_units,
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H A Dqlstm_projection.mod.py24 num_units = 4 variable
30 InputWeightsType = ("TENSOR_QUANT8_SYMM", [num_units, input_size], 0.00784314, 0)
36 RecurrentWeightsType = ("TENSOR_QUANT8_SYMM", [num_units, output_size], 0.00784314, 0)
42 CellWeightsType = ("TENSOR_QUANT16_SYMM", [num_units], 1.0, 0)
48 BiasType = ("TENSOR_INT32", [num_units], 0.0, 0)
55 ("TENSOR_QUANT8_SYMM", [output_size, num_units], 0.00392157, 0))
59 CellStateType = ("TENSOR_QUANT16_SYMM", [batch_size, num_units], 3.05176e-05, 0)
63 LayerNormType = ("TENSOR_QUANT16_SYMM", [num_units], 3.05182e-05, 0)
135 cell_state_in: [ 0 for _ in range(batch_size * num_units) ],
192 cell_state_in: [ 0 for _ in range(batch_size * num_units) ],
H A Dqlstm_noprojection.mod.py24 num_units = 4 variable
30 InputWeightsType = ("TENSOR_QUANT8_SYMM", [num_units, input_size], 0.00784314, 0)
36 RecurrentWeightsType = ("TENSOR_QUANT8_SYMM", [num_units, output_size], 0.00784314, 0)
42 CellWeightsType = ("TENSOR_QUANT16_SYMM", [num_units], 1.0, 0)
48 BiasType = ("TENSOR_INT32", [num_units], 0.0, 0)
55 ("TENSOR_QUANT8_SYMM", [output_size, num_units], 0.00392157, 0))
59 CellStateType = ("TENSOR_QUANT16_SYMM", [batch_size, num_units], 3.05176e-05, 0)
63 LayerNormType = ("TENSOR_QUANT16_SYMM", [num_units], 3.05182e-05, 0)
129 cell_state_in: [ 0 for _ in range(batch_size * num_units) ],
/aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/
H A Dunidirectional_sequence_rnn.mod.py47 num_units = 16 variable
144 num_units, input_size)),
146 "{{{}, {}}}".format(num_units, num_units)),
149 num_batches, num_units)),
151 num_batches, max_time, num_units)),
158 hidden_state_data=[0] * num_batches * num_units,
166 num_units, input_size)),
168 "{{{}, {}}}".format(num_units, num_units)),
171 num_batches, num_units)),
173 max_time, num_batches, num_units)),
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/aosp12/packages/modules/NeuralNetworks/common/operations/
H A DRNN.cpp62 const uint32_t num_units = SizeOfDimension(input_weights, 0); in Prepare() local
72 hiddenStateShape->dimensions = {batch_size, num_units}; in Prepare()
76 outputShape->dimensions = {batch_size, num_units}; in Prepare()
146 const uint32_t num_units = weightsShape.dimensions[0]; in RNNStep() local
163 const T* hidden_state_in_ptr_batch = hiddenStateInputData + b * num_units; in RNNStep()
179 for (uint32_t o = 0; o < num_units; o++) { in RNNStep()
184 for (uint32_t o = 0; o < num_units; o++) { in RNNStep()
193 for (uint32_t o = 0; o < num_units; o++) { in RNNStep()
202 for (uint32_t o = 0; o < num_units; o++) { in RNNStep()
203 for (uint32_t h = 0; h < num_units; h++) { in RNNStep()
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H A DSVDF.cpp84 const uint32_t num_units = num_filters / rank; in Prepare() local
91 NN_CHECK_EQ(SizeOfDimension(bias, 0), num_units); in Prepare()
103 outputShape->dimensions = {batch_size, num_units}; in Prepare()
171 const int num_units = num_filters / rank; in EvalFloat32() local
206 tflite::tensor_utils::ReductionSumVector(scratch, outputData, batch_size * num_units, rank); in EvalFloat32()
210 tflite::tensor_utils::VectorBatchVectorAdd(biasData, num_units, batch_size, outputData); in EvalFloat32()
214 tflite::tensor_utils::ApplyActivationToVector(outputData, batch_size * num_units, in EvalFloat32()
H A DFullyConnected.cpp203 uint32_t num_units = getSizeOfDimension(weights, 0); in validateShapes() local
210 if (num_units != 0 && bias_len != 0) { in validateShapes()
211 NN_RET_CHECK_EQ(bias_len, num_units); in validateShapes()
215 NN_RET_CHECK_GT(num_units, 0); in validateShapes()
218 output->dimensions = {batch_size, num_units}; in validateShapes()
H A DRNNTest.cpp189 uint32_t num_units() const { return units_; } in num_units() function in android::nn::wrapper::BasicRNNOpModel
294 float* golden_start = rnn_golden_output + i * rnn.num_units(); in TEST()
295 float* golden_end = golden_start + rnn.num_units(); in TEST()
H A DSVDFTest.cpp296 int num_units() const { return units_; } in num_units() function in android::nn::wrapper::SVDFOpModel
340 const int svdf_num_units = svdf.num_units(); in TEST()
399 const int svdf_num_units = svdf.num_units(); in TEST()
/aosp12/hardware/interfaces/neuralnetworks/1.0/
H A Dtypes.hal555 * [num_units, input_size], where "num_units" corresponds to the number
934 * A 2-D tensor of shape [num_units, input_size], where “num_units”
953 * A 1-D tensor of shape [num_units].
955 * A 1-D tensor of shape [num_units].
957 * A 1-D tensor of shape [num_units].
959 * A 1-D tensor of shape [num_units].
961 * A 1-D tensor of shape [num_units].
1265 * A 2-D tensor of shape [num_units, input_size], where “num_units”
1268 * A 2-D tensor of shape [num_units, num_units], with columns
1409 * A 2-D tensor of shape [num_units, input_size], where “num_units”
[all …]
/aosp12/hardware/interfaces/neuralnetworks/1.2/
H A Dtypes.hal774 * [num_units, input_size], where "num_units" corresponds to the number
1220 * A 2-D tensor of shape [num_units, input_size], where “num_units”
1239 * A 1-D tensor of shape [num_units].
1241 * A 1-D tensor of shape [num_units].
1243 * A 1-D tensor of shape [num_units].
1245 * A 1-D tensor of shape [num_units].
1634 * A 2-D tensor of shape [num_units, input_size], where “num_units”
1637 * A 2-D tensor of shape [num_units, num_units], with columns
1796 * A 2-D tensor of shape [num_units, input_size], where “num_units”
1818 * [batch_size, num_units].
[all …]
/aosp12/hardware/interfaces/neuralnetworks/1.3/
H A Dtypes.hal762 * [num_units, input_size], where "num_units" corresponds to the number
1219 * A 2-D tensor of shape [num_units, input_size], where “num_units”
1238 * A 1-D tensor of shape [num_units].
1240 * A 1-D tensor of shape [num_units].
1242 * A 1-D tensor of shape [num_units].
1244 * A 1-D tensor of shape [num_units].
1672 * A 2-D tensor of shape [num_units, input_size], where “num_units”
1675 * A 2-D tensor of shape [num_units, num_units], with columns
1840 * A 2-D tensor of shape [num_units, input_size], where “num_units”
1862 * [batch_size, num_units].
[all …]
/aosp12/packages/modules/NeuralNetworks/tools/api/
H A Dtypes.spec1655 * A 2-D tensor of shape [num_units, input_size], where “num_units”
1674 * A 1-D tensor of shape [num_units].
1676 * A 1-D tensor of shape [num_units].
1678 * A 1-D tensor of shape [num_units].
1680 * A 1-D tensor of shape [num_units].
1682 * A 1-D tensor of shape [num_units].
1684 * A 1-D tensor of shape [num_units].
2200 * A 2-D tensor of shape [num_units, input_size], where “num_units”
2203 * A 2-D tensor of shape [num_units, num_units], with columns
2404 * A 2-D tensor of shape [num_units, input_size], where “num_units”
[all …]