Searched refs:i0 (Results 1 - 25 of 58) sorted by relevance

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/frameworks/ml/nn/tools/test_generator/tests/P_explicit/
H A Dexplicit_add.mod.py3 i0 = Internal("op0", "TENSOR_FLOAT32", "{1, 8, 8, 3}") # intermediate result variable
5 model = model.RawAdd(i1, i1).To(i0)
6 model = model.RawAdd(i0, i1).To(i2)
/frameworks/ml/nn/tools/test_generator/tests/P_vts_full/
H A Dvts_full.mod.py5 i0 = Input("operand0","TENSOR_FLOAT32", "{1, 2, 2, 1}") variable
10 model.Operation("ADD", i0, p0, b0).To(o)
12 input0 = {i0: # input 0
/frameworks/ml/nn/runtime/test/generated/models/
H A Dconv_1_h3_w2_SAME.model.py8 i0 = Parameter("op0", "TENSOR_FLOAT32", "{1, 3, 2, 3}", [-0.966213, -0.467474, -0.82203, -0.579455, 0.0278809, -0.79946, -0.684259, 0.563238, 0.37289, 0.738216, 0.386045, -0.917775, 0.184325, -0.270568, 0.82236, 0.0973683, -0.941308, -0.144706]) # parameters variable
10 model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3)
H A Dconv_1_h3_w2_VALID.model.py8 i0 = Parameter("op0", "TENSOR_FLOAT32", "{1, 3, 2, 3}", [-0.966213, -0.467474, -0.82203, -0.579455, 0.0278809, -0.79946, -0.684259, 0.563238, 0.37289, 0.738216, 0.386045, -0.917775, 0.184325, -0.270568, 0.82236, 0.0973683, -0.941308, -0.144706]) # parameters variable
10 model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3)
H A Dconv_3_h3_w2_SAME.model.py8 i0 = Parameter("op0", "TENSOR_FLOAT32", "{3, 3, 2, 3}", [-0.966213, -0.579455, -0.684259, 0.738216, 0.184325, 0.0973683, -0.176863, -0.23936, -0.000233404, 0.055546, -0.232658, -0.316404, -0.012904, 0.320705, -0.326657, -0.919674, 0.868081, -0.824608, -0.467474, 0.0278809, 0.563238, 0.386045, -0.270568, -0.941308, -0.779227, -0.261492, -0.774804, -0.79665, 0.22473, -0.414312, 0.685897, -0.327792, 0.77395, -0.714578, -0.972365, 0.0696099, -0.82203, -0.79946, 0.37289, -0.917775, 0.82236, -0.144706, -0.167188, 0.268062, 0.702641, -0.412223, 0.755759, 0.721547, -0.43637, -0.274905, -0.269165, 0.16102, 0.819857, -0.312008]) # parameters variable
10 model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3)
H A Dconv_3_h3_w2_VALID.model.py8 i0 = Parameter("op0", "TENSOR_FLOAT32", "{3, 3, 2, 3}", [-0.966213, -0.579455, -0.684259, 0.738216, 0.184325, 0.0973683, -0.176863, -0.23936, -0.000233404, 0.055546, -0.232658, -0.316404, -0.012904, 0.320705, -0.326657, -0.919674, 0.868081, -0.824608, -0.467474, 0.0278809, 0.563238, 0.386045, -0.270568, -0.941308, -0.779227, -0.261492, -0.774804, -0.79665, 0.22473, -0.414312, 0.685897, -0.327792, 0.77395, -0.714578, -0.972365, 0.0696099, -0.82203, -0.79946, 0.37289, -0.917775, 0.82236, -0.144706, -0.167188, 0.268062, 0.702641, -0.412223, 0.755759, 0.721547, -0.43637, -0.274905, -0.269165, 0.16102, 0.819857, -0.312008]) # parameters variable
10 model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3)
H A Ddepthwise_conv.model.py9 i0 = Parameter("op0", "TENSOR_FLOAT32", "{1, 1, 1, 3}", [-0.966213, -0.467474, -0.82203]) # parameters variable
11 model = model.DepthWiseConv(i2, i0, i1, i4, i5, i6, i7, i8).To(i3)
H A Davg_pool_float_2.model.cpp7 auto i0 = model->addOperand(&type0); local
22 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
25 {i0},
H A Davg_pool_float_3.model.cpp7 auto i0 = model->addOperand(&type0); local
22 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
25 {i0},
H A Davg_pool_float_4.model.cpp7 auto i0 = model->addOperand(&type0); local
22 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, relu6_activation}, {output});
25 {i0},
H A Davg_pool_quant8_2.model.cpp7 auto i0 = model->addOperand(&type0); local
22 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
25 {i0},
H A Davg_pool_quant8_3.model.cpp7 auto i0 = model->addOperand(&type0); local
22 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
25 {i0},
/frameworks/ml/nn/tools/test_generator/tests/P_conv/
H A Dconv_1_h3_w2_SAME.mod.py7 i0 = Parameter("op0", "TENSOR_FLOAT32", "{1, 3, 2, 3}", [-0.966213, -0.467474, -0.82203, -0.579455, 0.0278809, -0.79946, -0.684259, 0.563238, 0.37289, 0.738216, 0.386045, -0.917775, 0.184325, -0.270568, 0.82236, 0.0973683, -0.941308, -0.144706]) # parameters variable
10 model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3)
/frameworks/ml/nn/tools/test_generator/tests/P_quantized_conv/
H A Dquantized.mod.py7 i0 = Parameter("op0", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 1}", [1, 1, 1, 1]) # parameters variable
10 model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3)
/frameworks/ml/nn/runtime/test/specs/
H A Dlogistic_float_2.mod.py25 i0 = Input("input", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (d0, d1, d2, d3)) variable
29 model = model.Operation("LOGISTIC", i0).To(output)
34 input0 = {i0: input_values}
H A Dlogistic_quant8_2.mod.py25 i0 = Input("input", "TENSOR_QUANT8_ASYMM", "{%d, %d, %d, %d}, .5f, 0" % (d0, d1, d2, d3)) variable
29 model = model.Operation("LOGISTIC", i0).To(output)
34 input0 = {i0: input_values}
H A Drelu1_float_2.mod.py25 i0 = Input("input", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (d0, d1, d2, d3)) variable
29 model = model.Operation("RELU1", i0).To(output)
34 input0 = {i0: input_values}
H A Drelu1_quant8_2.mod.py25 i0 = Input("input", "TENSOR_QUANT8_ASYMM", "{%d, %d, %d, %d}, 1.f, 128" % (d0, d1, d2, d3)) variable
29 model = model.Operation("RELU1", i0).To(output)
34 input0 = {i0: input_values}
H A Drelu6_float_2.mod.py25 i0 = Input("input", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (d0, d1, d2, d3)) variable
29 model = model.Operation("RELU6", i0).To(output)
34 input0 = {i0: input_values}
H A Drelu6_quant8_2.mod.py25 i0 = Input("input", "TENSOR_QUANT8_ASYMM", "{%d, %d, %d, %d}, 1.f, 128" % (d0, d1, d2, d3)) variable
29 model = model.Operation("RELU6", i0).To(output)
34 input0 = {i0: input_values}
H A Drelu_float_2.mod.py25 i0 = Input("input", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (d0, d1, d2, d3)) variable
29 model = model.Operation("RELU", i0).To(output)
34 input0 = {i0: input_values}
H A Drelu_quant8_2.mod.py25 i0 = Input("input", "TENSOR_QUANT8_ASYMM", "{%d, %d, %d, %d}, 1.f, 128" % (d0, d1, d2, d3)) variable
29 model = model.Operation("RELU", i0).To(output)
34 input0 = {i0: input_values}
/frameworks/ml/nn/tools/test_generator/tests/P_depthwise_conv/
H A Ddepthwise_conv.bin.mod.py9 i0 = Parameter("op0", "TENSOR_FLOAT32", "{1, 1, 1, 3}", [-0.966213, -0.467474, -0.82203]) # parameters variable
11 model = model.DepthWiseConv(i2, i0, i1, i4, i5, i6, i7, i8).To(i3)
/frameworks/base/media/tests/audiotests/
H A Dshared_mem_test.cpp137 for(int i0=0; i0<bufferSz; i0++) {
138 buffer[i0] = ComputeSine( amplitude, phi);
175 for(int i0 = 0; i0<SIN_SZ; i0++) {
182 sin1024[i0] = (short)d0;
/frameworks/rs/driver/runtime/
H A Drs_f16_math.c83 short i0, j0; local
85 GET_HALF_WORD(i0, x);
86 j0 = ((i0 >> 10) & 0x1f) - 15; // exponent of x
89 SET_HALF_WORD(*iptr, i0 & 0x8000); // *iptr = +/- 0
94 if ((i0 & i) == 0) { // no bits set in fractional part
96 SET_HALF_WORD(x, i0 & 0x8000);
100 SET_HALF_WORD(*iptr, i0 & ~i); // zero out fractional parts

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