/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/ |
D | fully_connected_quant8_signed.mod.py | 18 in0 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{4, 1, 5, 1}, 0.5f, -1") variable 26 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act_relu).To(out0) 29 input0 = {in0: # input 0 41 in0 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 5}, 0.2, -128") # batch = 1, input_size = 5 variable 46 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 49 input0 = {in0: # input 0 60 in0 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 5}, 0.2, -128") # batch = 1, input_size = 5 variable 65 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 68 input0 = {in0: # input 0 83 in0 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{3, 1}, 0.5f, -128") variable [all …]
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/packages/services/BuiltInPrintService/jni/plugins/ |
D | wprint_scaler.c | 430 static inline void _scale_row_down_9in(uint8 *_RESTRICT_ in0, uint8 *_RESTRICT_ in1, in _scale_row_down_9in() argument 449 acc_r += (uint32) in0[(in_col * 3) + 0] * curr_weight * top_weight; in _scale_row_down_9in() 459 acc_g += (uint32) in0[(in_col * 3) + 1] * curr_weight * top_weight; in _scale_row_down_9in() 469 acc_b += (uint32) in0[(in_col * 3) + 2] * curr_weight * top_weight; in _scale_row_down_9in() 493 static inline void _scale_row_down_8in(uint8 *_RESTRICT_ in0, uint8 *_RESTRICT_ in1, in _scale_row_down_8in() argument 513 acc_r += (uint32) in0[(in_col * 3) + 0] * curr_weight * top_weight; in _scale_row_down_8in() 522 acc_g += (uint32) in0[(in_col * 3) + 1] * curr_weight * top_weight; in _scale_row_down_8in() 531 acc_b += (uint32) in0[(in_col * 3) + 2] * curr_weight * top_weight; in _scale_row_down_8in() 554 static inline void _scale_row_down_7in(uint8 *_RESTRICT_ in0, uint8 *_RESTRICT_ in1, in _scale_row_down_7in() argument 572 acc_r += (uint32) in0[(in_col * 3) + 0] * curr_weight * top_weight; in _scale_row_down_7in() [all …]
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/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/ |
D | fully_connected_v1_2.mod.py | 19 in0 = Input("op1", "TENSOR_FLOAT32", "{3, 1}") variable 24 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 27 in0: ("TENSOR_QUANT8_ASYMM", 0.5, 127), 34 input0 = {in0: # input 0
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/packages/modules/NeuralNetworks/runtime/test/specs/V1_0/ |
D | fully_connected_float.mod.py | 18 in0 = Input("op1", "TENSOR_FLOAT32", "{3, 1}") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 26 input0 = {in0: # input 0
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D | fully_connected_quant8.mod.py | 18 in0 = Input("op1", "TENSOR_QUANT8_ASYMM", "{3, 1}, 0.5f, 0") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 26 input0 = {in0: # input 0
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D | fully_connected_float_2.mod.py | 18 in0 = Input("op1", "TENSOR_FLOAT32", "{2, 8}") variable 48 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act_relu).To(out0) 51 input0 = {in0: # input 0
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D | fully_connected_quant8_2.mod.py | 18 in0 = Input("op1", "TENSOR_QUANT8_ASYMM", "{4, 1, 5, 1}, 0.5f, 127") variable 26 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act_relu).To(out0) 29 input0 = {in0: # input 0
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D | fully_connected_float_3.mod.py | 18 in0 = Input("op1", "TENSOR_FLOAT32", "{2, 2}") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 26 input0 = {in0: # input 0
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D | fully_connected_quant8_large.mod.py | 18 in0 = Input("op1", "TENSOR_QUANT8_ASYMM", "{1, 5}, 0.2, 0") # batch = 1, input_size = 5 variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 26 input0 = {in0: # input 0
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D | fully_connected_float_large.mod.py | 18 in0 = Input("op1", "TENSOR_FLOAT32", "{1, 5}") # batch = 1, input_size = 5 variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 26 input0 = {in0: # input 0
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D | fully_connected_float_large_weights_as_inputs.mod.py | 18 in0 = Input("op1", "TENSOR_FLOAT32", "{1, 5}") # batch = 1, input_size = 5 variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 26 input0 = {in0: # input 0
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D | fully_connected_quant8_weights_as_inputs.mod.py | 18 in0 = Input("op1", "TENSOR_QUANT8_ASYMM", "{3, 1}, 0.5f, 0") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 26 input0 = {in0: # input 0
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D | fully_connected_quant8_large_weights_as_inputs.mod.py | 18 in0 = Input("op1", "TENSOR_QUANT8_ASYMM", "{1, 5}, 0.2, 0") # batch = 1, input_size = 5 variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 26 input0 = {in0: # input 0
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D | fully_connected_float_weights_as_inputs.mod.py | 18 in0 = Input("op1", "TENSOR_FLOAT32", "{3, 1}") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 26 input0 = {in0: # input 0
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/packages/modules/NeuralNetworks/runtime/test/specs/V1_1/ |
D | fully_connected_float_4d_simple.mod.py | 22 in0 = Input("op1", "TENSOR_FLOAT32", "{4, 1, 5, 1}") variable 31 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 34 input0 = {in0: # input 0
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D | fully_connected_float_2_relaxed.mod.py | 18 in0 = Input("op1", "TENSOR_FLOAT32", "{2, 8}") variable 48 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act_relu).To(out0) 52 input0 = {in0: # input 0
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D | fully_connected_float_4d_simple_relaxed.mod.py | 22 in0 = Input("op1", "TENSOR_FLOAT32", "{4, 1, 5, 1}") variable 31 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 35 input0 = {in0: # input 0
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D | fully_connected_float_large_relaxed.mod.py | 18 in0 = Input("op1", "TENSOR_FLOAT32", "{1, 5}") # batch = 1, input_size = 5 variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 27 input0 = {in0: # input 0
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D | fully_connected_float_relaxed.mod.py | 18 in0 = Input("op1", "TENSOR_FLOAT32", "{3, 1}") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 27 input0 = {in0: # input 0
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D | fully_connected_float_weights_as_inputs_relaxed.mod.py | 18 in0 = Input("op1", "TENSOR_FLOAT32", "{3, 1}") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 27 input0 = {in0: # input 0
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D | fully_connected_float_large_weights_as_inputs_relaxed.mod.py | 18 in0 = Input("op1", "TENSOR_FLOAT32", "{1, 5}") # batch = 1, input_size = 5 variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 27 input0 = {in0: # input 0
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/packages/modules/NeuralNetworks/runtime/test/ |
D | TestValidation.cpp | 1299 float in0[] = {0.0f, 0.0f}, in1[] = {1.0f, 1.0f}, out0[2]; in TEST_F() local 1301 ASSERT_EQ(ANeuralNetworksExecution_setInput(execution, 0, nullptr, &in0, sizeof(in0)), in TEST_F() 1311 const size_t memorySize = std::max(sizeof(in0), sizeof(out0)); in TEST_F() 1319 auto testTooLate = [this, execution, &in0, &out0, memory] { in TEST_F() 1338 ANeuralNetworksExecution_setInput(execution, 0, nullptr, &in0, sizeof(in0)), in TEST_F() 1344 0, sizeof(in0)), in TEST_F() 1490 float in0[] = {0.0f, 0.0f}, in1[] = {1.0f, 1.0f}, out0[2]; in testConcurrentExecution() local 1492 ASSERT_EQ(ANeuralNetworksExecution_setInput(execution, 0, nullptr, &in0, sizeof(in0)), in testConcurrentExecution() 3139 float in0[] = {0.0f, 0.0f}, in1[] = {1.0f, 1.0f}, out0[2]; in TEST_F() local 3141 ASSERT_EQ(ANeuralNetworksExecution_setInput(execution, 0, nullptr, &in0, sizeof(in0)), in TEST_F() [all …]
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