Searched defs:weights (Results 1 - 16 of 16) sorted by relevance

/frameworks/ml/nn/runtime/test/specs/
H A Dfully_connected_float.mod.py19 weights = Parameter("op2", "TENSOR_FLOAT32", "{1, 1}", [2]) variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
H A Dfully_connected_float_large.mod.py19 weights = Parameter("op2", "TENSOR_FLOAT32", "{1, 5}", [2, 3, 4, 5, 6]) # num_units = 1, input_size = 5 variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
H A Dfully_connected_float_large_weights_as_inputs.mod.py19 weights = Input("op2", "TENSOR_FLOAT32", "{1, 5}") # num_units = 1, input_size = 5 variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
28 weights:
H A Dfully_connected_float_weights_as_inputs.mod.py19 weights = Input("op2", "TENSOR_FLOAT32", "{1, 1}") variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
28 weights: [2],
H A Dfully_connected_quant8.mod.py19 weights = Parameter("op2", "TENSOR_QUANT8_ASYMM", "{1, 1}, 0.5f, 0", [2]) variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
H A Dfully_connected_quant8_large.mod.py19 weights = Parameter("op2", "TENSOR_QUANT8_ASYMM", "{1, 5}, 0.2, 0", [10, 20, 20, 20, 10]) # num_units = 1, input_size = 5 variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
H A Dfully_connected_quant8_large_weights_as_inputs.mod.py19 weights = Input("op2", "TENSOR_QUANT8_ASYMM", "{1, 5}, 0.2, 0") # num_units = 1, input_size = 5 variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
28 weights:
H A Dfully_connected_quant8_weights_as_inputs.mod.py19 weights = Input("op2", "TENSOR_QUANT8_ASYMM", "{1, 1}, 0.5f, 0") variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
28 weights: [2],
H A Drnn_state.mod.py24 weights = Input("weights", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size)) variable
34 model = model.Operation("RNN", input, weights, recurrent_weights, bias, hidden_state_in,
38 weights: [
H A Drnn.mod.py24 weights = Input("weights", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size)) variable
34 model = model.Operation("RNN", input, weights, recurrent_weights, bias, hidden_state_in,
38 weights: [
/frameworks/ml/nn/runtime/test/generated/models/
H A Drnn.model.cpp11 auto weights = model->addOperand(&type1); local
19 model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
22 {input, weights, recurrent_weights, bias, hidden_state_in, activation_param},
H A Drnn_state.model.cpp11 auto weights = model->addOperand(&type1); local
19 model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
22 {input, weights, recurrent_weights, bias, hidden_state_in, activation_param},
/frameworks/base/libs/hwui/utils/
H A DBlur.cpp61 void Blur::generateGaussianWeights(float* weights, float radius) { argument
64 // Compute gaussian weights for the blur
83 weights[r + intRadius] = coeff1 * pow(e, floatR * floatR * coeff2);
84 normalizeFactor += weights[r + intRadius];
87 //Now we need to normalize the weights because all our coefficients need to add up to one
90 weights[r + intRadius] *= normalizeFactor;
94 void Blur::horizontal(float* weights, int32_t radius, argument
106 const float* gPtr = weights;
138 void Blur::vertical(float* weights, int32_t radius, argument
148 const float* gPtr = weights;
[all...]
/frameworks/support/v17/leanback/src/android/support/v17/leanback/widget/
H A DParallaxEffect.java95 * @param weights A list of Float objects that represents weight associated with each variable
99 public final void setWeights(float... weights) { argument
100 for (float weight : weights) {
108 for (float weight : weights) {
119 * @param weights A list of Float objects that represents weight associated with each variable
124 public final ParallaxEffect weights(float... weights) { argument
125 setWeights(weights);
257 // use weights user defined
/frameworks/ml/nn/common/
H A DCpuExecutor.cpp935 RunTimeOperandInfo& weights = mOperands[ins[1]]; local
944 success = fullyConnectedPrepare(input.shape(), weights.shape(), bias.shape(),
949 reinterpret_cast<const float*>(weights.buffer),
950 weights.shape(),
957 success = fullyConnectedPrepare(input.shape(), weights.shape(), bias.shape(),
962 reinterpret_cast<const uint8_t*>(weights.buffer),
963 weights.shape(),
/frameworks/rs/driver/runtime/
H A Drs_sample.c268 getBilinearSample1D(const Allocation_t *alloc, float2 weights, argument
276 return getSample_RGBA(p, iPixel, next, weights.x, weights.y);
278 return getSample_A(p, iPixel, next, weights.x, weights.y);
281 return getSample_565(p, iPixel, next, weights.x, weights.y);
283 return getSample_RGB(p, iPixel, next, weights.x, weights.y);
285 return getSample_L(p, iPixel, next, weights
440 float2 weights; local
[all...]

Completed in 148 milliseconds