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/frameworks/ml/nn/runtime/test/specs/V1_3/
Dfully_connected_quant8_signed.mod.py18 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
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/frameworks/rs/tests/java_api/RSUnitTests/src/com/android/rs/unittest/
Dforeach_multi.rscript47 uint32_t RS_KERNEL sum2(uint32_t in0, uint32_t in1, uint32_t x) {
48 _RS_ASSERT(in0 == x);
51 return in0 + in1;
55 sum2_struct(uint32_t in0, uint32_t in1, uint32_t x) {
57 _RS_ASSERT(in0 == x);
62 retval.i0 = in0 + in1;
63 retval.i1 = in0 + in1;
64 retval.i2 = in0 + in1;
65 retval.i3 = in0 + in1;
66 retval.i4 = in0 + in1;
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/frameworks/rs/tests/java_api/RSUnitTests/supportlibsrc_gen/com/android/rs/unittest/
Dforeach_multi.rscript49 uint32_t RS_KERNEL sum2(uint32_t in0, uint32_t in1, uint32_t x) {
50 _RS_ASSERT(in0 == x);
53 return in0 + in1;
57 sum2_struct(uint32_t in0, uint32_t in1, uint32_t x) {
59 _RS_ASSERT(in0 == x);
64 retval.i0 = in0 + in1;
65 retval.i1 = in0 + in1;
66 retval.i2 = in0 + in1;
67 retval.i3 = in0 + in1;
68 retval.i4 = in0 + in1;
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/frameworks/ml/nn/runtime/test/specs/V1_0/
Dfully_connected_float_large.mod.py18 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
Dfully_connected_quant8_2.mod.py18 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
Dfully_connected_float.mod.py18 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
Dfully_connected_quant8_large.mod.py18 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
Dfully_connected_float_2.mod.py18 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
Dfully_connected_quant8.mod.py18 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
Dfully_connected_float_3.mod.py18 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
Dfully_connected_quant8_large_weights_as_inputs.mod.py18 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
Dfully_connected_float_large_weights_as_inputs.mod.py18 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
Dfully_connected_quant8_weights_as_inputs.mod.py18 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
Dfully_connected_float_weights_as_inputs.mod.py18 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
/frameworks/ml/nn/runtime/test/specs/V1_1/
Dfully_connected_float_4d_simple.mod.py22 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
Dfully_connected_float_large_relaxed.mod.py18 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
Dfully_connected_float_2_relaxed.mod.py18 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
Dfully_connected_float_relaxed.mod.py18 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
Dfully_connected_float_4d_simple_relaxed.mod.py22 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
Dfully_connected_float_large_weights_as_inputs_relaxed.mod.py18 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
Dfully_connected_float_weights_as_inputs_relaxed.mod.py18 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
/frameworks/ml/nn/runtime/test/specs/V1_2/
Dfully_connected_v1_2.mod.py19 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
/frameworks/rs/cpu_ref/
DrsCpuIntrinsics_x86.cpp762 __m128i in0, in1, out0, out1; in rsdIntrinsicBlendSrcOver_K() local
769 in0 = _mm_loadu_si128((const __m128i *)src); in rsdIntrinsicBlendSrcOver_K()
774 ins = _mm_unpacklo_epi8(in0, _mm_setzero_si128()); in rsdIntrinsicBlendSrcOver_K()
782 ins = _mm_unpackhi_epi8(in0, _mm_setzero_si128()); in rsdIntrinsicBlendSrcOver_K()
818 __m128i in0, in1, out0, out1; in rsdIntrinsicBlendDstOver_K() local
825 in0 = _mm_loadu_si128((const __m128i *)src); in rsdIntrinsicBlendDstOver_K()
834 t0 = _mm_unpacklo_epi8(in0, _mm_setzero_si128()); in rsdIntrinsicBlendDstOver_K()
842 t1 = _mm_unpackhi_epi8(in0, _mm_setzero_si128()); in rsdIntrinsicBlendDstOver_K()
875 __m128i in0, in1, out0, out1; in rsdIntrinsicBlendSrcIn_K() local
880 in0 = _mm_loadu_si128((const __m128i *)src); in rsdIntrinsicBlendSrcIn_K()
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/frameworks/compile/slang/tests/F_too_many_inputs/
Dtoo_many_inputs.rscript5 int RS_KERNEL good(int in0, int in1, int in2, int in3, int in4, int in5, int in6, int in7) {
9 int RS_KERNEL bad(int in0, int in1, int in2, int in3, int in4, int in5, int in6, int in7, int in8) {
/frameworks/av/media/libstagefright/codecs/amrwbenc/src/
Dwb_vad.c82 Word16 * in0, /* i/o : input values; output low-pass part */ in filter5() argument
89 temp0 = vo_sub(*in0, vo_mult(COEFF5_1, data[0])); in filter5()
97 *in0 = extract_h((vo_L_add(temp1, temp2) << 15)); in filter5()
110 Word16 * in0, /* i/o : input values; output low-pass part */ in filter3() argument
121 *in1 = extract_h((vo_L_sub(*in0, temp2) << 15)); in filter3()
122 *in0 = extract_h((vo_L_add(*in0, temp2) << 15)); in filter3()

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