| /frameworks/ml/nn/tools/test_generator/tests/P_explicit/ |
| H A D | explicit_add.mod.py | 3 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)
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| /frameworks/ml/nn/tools/test_generator/tests/P_vts_full/ |
| H A D | vts_full.mod.py | 5 i0 = Input("operand0","TENSOR_FLOAT32", "{1, 2, 2, 1}") variable
10 model.Operation("ADD", i0, p0, b0).To(o)
12 input0 = {i0: # input 0
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| /frameworks/ml/nn/tools/test_generator/tests/P_conv/ |
| H A D | conv_1_h3_w2_SAME.mod.py | 7 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 D | quantized.mod.py | 7 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/V1_0/ |
| H A D | logistic_float_2.mod.py | 25 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}
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| H A D | logistic_quant8_2.mod.py | 25 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 D | relu1_float_2.mod.py | 25 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 D | relu1_quant8_2.mod.py | 25 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 D | relu6_float_2.mod.py | 25 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 D | relu6_quant8_2.mod.py | 25 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 D | relu_float_2.mod.py | 25 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 D | relu_quant8_2.mod.py | 25 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}
|
| H A D | conv_1_h3_w2_SAME.mod.py | 8 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 D | conv_1_h3_w2_VALID.mod.py | 8 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 D | conv_3_h3_w2_SAME.mod.py | 8 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 D | conv_3_h3_w2_VALID.mod.py | 8 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 D | depthwise_conv.mod.py | 9 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/ml/nn/runtime/test/specs/V1_1/ |
| H A D | logistic_float_2_relaxed.mod.py | 25 i0 = Input("input", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (d0, d1, d2, d3)) variable
29 model = model.Operation("LOGISTIC", i0).To(output)
35 input0 = {i0: input_values}
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| H A D | relu1_float_2_relaxed.mod.py | 25 i0 = Input("input", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (d0, d1, d2, d3)) variable
29 model = model.Operation("RELU1", i0).To(output)
35 input0 = {i0: input_values}
|
| H A D | relu6_float_2_relaxed.mod.py | 25 i0 = Input("input", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (d0, d1, d2, d3)) variable
29 model = model.Operation("RELU6", i0).To(output)
35 input0 = {i0: input_values}
|
| H A D | relu_float_2_relaxed.mod.py | 25 i0 = Input("input", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (d0, d1, d2, d3)) variable
29 model = model.Operation("RELU", i0).To(output)
35 input0 = {i0: input_values}
|
| H A D | conv_1_h3_w2_SAME_relaxed.mod.py | 24 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
26 model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3)
|
| H A D | conv_1_h3_w2_VALID_relaxed.mod.py | 24 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
26 model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3)
|
| /frameworks/ml/nn/tools/test_generator/tests/P_depthwise_conv/ |
| H A D | depthwise_conv.bin.mod.py | 9 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 D | shared_mem_test.cpp | 137 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;
|