/frameworks/ml/nn/runtime/test/specs/V1_0/ |
D | fully_connected_float_2.mod.py | 46 out0 = Output("op3", "TENSOR_FLOAT32", "{2, 16}") variable 48 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act_relu).To(out0) 54 output0 = {out0: # output 0
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D | fully_connected_float.mod.py | 21 out0 = Output("op3", "TENSOR_FLOAT32", "{3, 1}") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 28 output0 = {out0: # output 0
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D | fully_connected_quant8.mod.py | 21 out0 = Output("op3", "TENSOR_QUANT8_ASYMM", "{3, 1}, 1.f, 0") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 28 output0 = {out0: # output 0
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D | fully_connected_quant8_2.mod.py | 24 out0 = Output("op3", "TENSOR_QUANT8_ASYMM", "{2, 3}, 1.f, 127") variable 26 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act_relu).To(out0) 32 output0 = {out0: # output 0
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D | fully_connected_quant8_large.mod.py | 21 out0 = Output("op3", "TENSOR_QUANT8_ASYMM", "{1, 1}, 1.f, 0") # batch = 1, number_units = 1 variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 28 output0 = {out0: # output 0
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D | fully_connected_float_3.mod.py | 21 out0 = Output("op3", "TENSOR_FLOAT32", "{2, 1}") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 28 output0 = {out0: # output 0
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D | fully_connected_float_large.mod.py | 21 out0 = Output("op3", "TENSOR_FLOAT32", "{1, 1}") # batch = 1, number_units = 1 variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 28 output0 = {out0: # output 0
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D | fully_connected_float_large_weights_as_inputs.mod.py | 21 out0 = Output("op3", "TENSOR_FLOAT32", "{1, 1}") # batch = 1, number_units = 1 variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 32 output0 = {out0: # output 0
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D | fully_connected_quant8_weights_as_inputs.mod.py | 21 out0 = Output("op3", "TENSOR_QUANT8_ASYMM", "{3, 1}, 1.f, 0") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 30 output0 = {out0: # output 0
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D | fully_connected_quant8_large_weights_as_inputs.mod.py | 21 out0 = Output("op3", "TENSOR_QUANT8_ASYMM", "{1, 1}, 1.f, 0") # batch = 1, number_units = 1 variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 32 output0 = {out0: # output 0
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D | fully_connected_float_weights_as_inputs.mod.py | 21 out0 = Output("op3", "TENSOR_FLOAT32", "{3, 1}") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 30 output0 = {out0: # output 0
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/frameworks/ml/nn/runtime/test/specs/V1_1/ |
D | fully_connected_float_4d_simple.mod.py | 29 out0 = Output("op3", "TENSOR_FLOAT32", "{2, 3}") variable 31 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 37 output0 = {out0: # output 0
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D | fully_connected_float_large_relaxed.mod.py | 21 out0 = Output("op3", "TENSOR_FLOAT32", "{1, 1}") # batch = 1, number_units = 1 variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 29 output0 = {out0: # output 0
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D | fully_connected_float_2_relaxed.mod.py | 46 out0 = Output("op3", "TENSOR_FLOAT32", "{2, 16}") variable 48 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act_relu).To(out0) 55 output0 = {out0: # output 0
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D | fully_connected_float_4d_simple_relaxed.mod.py | 29 out0 = Output("op3", "TENSOR_FLOAT32", "{2, 3}") variable 31 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 38 output0 = {out0: # output 0
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D | fully_connected_float_relaxed.mod.py | 21 out0 = Output("op3", "TENSOR_FLOAT32", "{3, 1}") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 29 output0 = {out0: # output 0
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D | fully_connected_float_weights_as_inputs_relaxed.mod.py | 21 out0 = Output("op3", "TENSOR_FLOAT32", "{3, 1}") variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 31 output0 = {out0: # output 0
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D | fully_connected_float_large_weights_as_inputs_relaxed.mod.py | 21 out0 = Output("op3", "TENSOR_FLOAT32", "{1, 1}") # batch = 1, number_units = 1 variable 23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 33 output0 = {out0: # output 0
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/frameworks/ml/nn/runtime/test/specs/V1_2/ |
D | fully_connected_v1_2.mod.py | 22 out0 = Output("op3", "TENSOR_FLOAT32", "{3, 1}") variable 24 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0) 30 out0: ("TENSOR_QUANT8_ASYMM", 0.1, 128), 36 output0 = {out0: # output 0
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/frameworks/rs/cpu_ref/ |
D | rsCpuIntrinsics_x86.cpp | 762 __m128i in0, in1, out0, out1; in rsdIntrinsicBlendSrcOver_K() local 771 out0 = _mm_loadu_si128((const __m128i *)dst); in rsdIntrinsicBlendSrcOver_K() 777 t0 = _mm_unpacklo_epi8(out0, _mm_setzero_si128()); in rsdIntrinsicBlendSrcOver_K() 785 t1 = _mm_unpackhi_epi8(out0, _mm_setzero_si128()); in rsdIntrinsicBlendSrcOver_K() 818 __m128i in0, in1, out0, out1; in rsdIntrinsicBlendDstOver_K() local 827 out0 = _mm_loadu_si128((const __m128i *)dst); in rsdIntrinsicBlendDstOver_K() 831 outs = _mm_unpacklo_epi8(out0, _mm_setzero_si128()); in rsdIntrinsicBlendDstOver_K() 839 outs = _mm_unpackhi_epi8(out0, _mm_setzero_si128()); in rsdIntrinsicBlendDstOver_K() 875 __m128i in0, in1, out0, out1; in rsdIntrinsicBlendSrcIn_K() local 882 out0 = _mm_loadu_si128((const __m128i *)dst); in rsdIntrinsicBlendSrcIn_K() [all …]
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/frameworks/rs/rsov/tests/RSoVTest/src/com/android/rs/rsov/test/ |
D | UT_multi_input.java | 72 float out0[] = new float[Xdim]; in run() local 77 Out0.copyTo(out0); in run() 94 if ((a[i] + b[i] - out0[i]) > tolerance) { in run() 96 Log.e(name, "expects " + expected + " got " + out0[i]); in run()
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/frameworks/rs/tests/java_api/VrDemo/src/com/example/android/rs/vr/engine/ |
D | VectorUtil.java | 44 double out0 = a[1] * b[2] - b[1] * a[2]; in cross() local 47 out[0] = out0; in cross()
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D | Quaternion.java | 38 double out0 = a[1] * b[2] - b[1] * a[2]; in cross() local 41 return new double[]{out0, out1, out2}; in cross()
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/frameworks/ml/nn/runtime/test/ |
D | TestValidation.cpp | 813 float in0[] = {0.0f, 0.0f}, in1[] = {1.0f, 1.0f}, out0[2]; in TEST_F() local 821 ASSERT_EQ(ANeuralNetworksExecution_setOutput(execution, 0, nullptr, &out0, sizeof(out0)), in TEST_F() 824 const size_t memorySize = std::max(sizeof(in0), sizeof(out0)); in TEST_F() 832 auto testTooLate = [this, execution, &in0, &out0, memory] { in TEST_F() 839 ANeuralNetworksExecution_setOutput(execution, 0, nullptr, &out0, sizeof(out0)), in TEST_F() 845 sizeof(out0)), in TEST_F() 1734 float in0[] = {0.0f, 0.0f}, in1[] = {1.0f, 1.0f}, out0[2]; in TEST_F() local 1742 ASSERT_EQ(ANeuralNetworksExecution_setOutput(execution, 0, nullptr, &out0, sizeof(out0)), in TEST_F()
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/frameworks/compile/slang/tests/F_reduce_general_bad_function/ |
D | reduce_general_bad_function.rs | 203 #pragma rs reduce(out0) accumulator(AccumInt) outconverter(out0) 204 static void out0() { }
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