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/frameworks/ml/nn/runtime/test/specs/V1_3/
Dbox_with_nms_limit_quant8_signed.mod.py20 i3 = Input("batchSplit", "TENSOR_INT32", "{19}") # batchSplit variable
26 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 2, 0.4, 0.5, 0.3).To(o1, o2, o…
78 i3: [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] # batch split
117 i3 = Input("batchSplit", "TENSOR_INT32", "{19}") # batchSplit variable
123 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, 5, 2, 0.4, 0.5, 0.3).To(o1, o2, o3…
175 i3: [1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3] # batch split
206 i3 = Input("batchSplit", "TENSOR_INT32", "{19}") # batchSplit variable
212 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, o2, o…
264 i3: [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] # batch split
294 i3 = Input("batchSplit", "TENSOR_INT32", "{19}") # batchSplit variable
[all …]
Dgenerate_proposals_quant8_signed.mod.py22 i3 = Input("anchors", "TENSOR_FLOAT32", "{2, 4}") # anchors variable
28 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3)
33 i3: ("TENSOR_QUANT16_SYMM", 0.125, 0),
50 i3: [0, 1, 4, 3, 1, 0, 3, 4], # anchors
72 i3 = Input("anchors", "TENSOR_FLOAT32", "{4, 4}") # anchors variable
78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3)
83 i3: ("TENSOR_QUANT16_SYMM", 0.125, 0),
158 i3: [ # anchors
Dmul_quant8_signed.mod.py21 i3 = Output("op3", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 2}, 2.0, -128") variable
22 model = model.Operation("MUL", i1, i2, act).To(i3)
30 output0 = {i3: # output 0
42 i3 = Output("op3", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 2.0, -128") variable
43 model = model.Operation("MUL", i1, i2, act).To(i3)
51 output0 = {i3: # output 0
Dadd_quant8_signed.mod.py21 i3 = Output("op3", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 1.0, 0") variable
22 model = model.Operation("ADD", i1, i2, act).To(i3)
30 output0 = {i3: # output 0
42 i3 = Output("op3", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 2}, 1.0, 0") variable
43 model = model.Operation("ADD", i1, i2, act).To(i3)
51 output0 = {i3: # output 0
Droi_pooling_quant8_signed.mod.py116 i3 = Input("in", "TENSOR_FLOAT32", "{4, 4, 4, 1}") variable
119 Model().Operation("ROI_POOLING", i3, roi3, [2, 2, 2, 2, 2], 2, 2, 2.0, 1.0, layout).To(o3)
122 i3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, 0),
129 i3: [
152 }).AddNchw(i3, o3, layout).AddVariations(quant8_signed, includeDefault=False)
/frameworks/ml/nn/runtime/test/specs/V1_2/
Ddetection_postprocess.mod.py20 i3 = Input("anchors", "TENSOR_FLOAT32", "{6, 4}") # anchors variable
26 Model("regular").Operation("DETECTION_POSTPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, True, 3, 1…
45 i3: [ # six anchors in center-size encoding
71 i3 = Input("anchors", "TENSOR_FLOAT32", "{6, 4}") # anchors variable
77 Model().Operation("DETECTION_POSTPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, False, 3, 1, 1, 0.0…
96 i3: [ # six anchors in center-size encoding
122 i3 = Input("anchors", "TENSOR_FLOAT32", "{6, 4}") # anchors variable
128 Model().Operation("DETECTION_POSTPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, False, 3, 1, 1, 0.0…
147 i3: [ # six anchors in center-size encoding
173 i3 = Input("anchors", "TENSOR_FLOAT32", "{6, 4}") # anchors variable
[all …]
Dgenerate_proposals.mod.py23 i3 = Input("anchors", "TENSOR_FLOAT32", "{2, 4}") # anchors variable
29 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3)
34 i3: ("TENSOR_QUANT16_SYMM", 0.125, 0),
51 i3: [0, 1, 4, 3, 1, 0, 3, 4], # anchors
72 i3 = Input("anchors", "TENSOR_FLOAT32", "{4, 4}") # anchors variable
78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3)
83 i3: ("TENSOR_QUANT16_SYMM", 0.125, 0),
158 i3: [ # anchors
Dbox_with_nms_limit_gaussian.mod.py20 i3 = Input("batchSplit", "TENSOR_INT32", "{19}") # batchSplit variable
26 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 2, 0.4, 0.5, 0.3).To(o1, o2, o…
78 i3: [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] # batch split
116 i3 = Input("batchSplit", "TENSOR_INT32", "{19}") # batchSplit variable
122 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, 5, 2, 0.4, 0.5, 0.3).To(o1, o2, o3…
174 i3: [1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3] # batch split
Dbox_with_nms_limit_linear.mod.py20 i3 = Input("batchSplit", "TENSOR_INT32", "{19}") # batchSplit variable
26 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 1, 0.4, 1.0, 0.3).To(o1, o2, o…
78 i3: [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] # batch split
114 i3 = Input("batchSplit", "TENSOR_INT32", "{19}") # batchSplit variable
120 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, 8, 1, 0.4, 0.5, 0.3).To(o1, o2, o3…
172 i3: [1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3] # batch split
Dbox_with_nms_limit_hard.mod.py20 i3 = Input("batchSplit", "TENSOR_INT32", "{19}") # batchSplit variable
26 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, o2, o…
78 i3: [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] # batch split
107 i3 = Input("batchSplit", "TENSOR_INT32", "{19}") # batchSplit variable
113 model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, 5, 0, 0.4, 0.5, 0.3).To(o1, o2, o3…
165 i3: [1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3] # batch split
Dadd_v1_2.mod.py22 i3 = Output("op3", "TENSOR_FLOAT16", "{3}") variable
23 model = model.Operation("ADD", i1, i2, act).To(i3)
32 output0 = {i3: # output 0
44 i3 = Output("op3", "TENSOR_FLOAT16", "{2, 2}") variable
45 model = model.Operation("ADD", i1, i2, act).To(i3)
53 output0 = {i3: # output 0
Dmul_v1_2.mod.py22 i3 = Output("op3", "TENSOR_FLOAT16", "{3}") variable
23 model = model.Operation("MUL", i1, i2, act).To(i3)
32 output0 = {i3: # output 0
44 i3 = Output("op3", "TENSOR_FLOAT16", "{2, 2}") variable
45 model = model.Operation("MUL", i1, i2, act).To(i3)
53 output0 = {i3: # output 0
Ddiv_v1_2.mod.py22 i3 = Output("op3", "TENSOR_FLOAT16", "{3}") variable
23 model = model.Operation("DIV", i1, i2, act).To(i3)
32 output0 = {i3: # output 0
44 i3 = Output("op3", "TENSOR_FLOAT16", "{2, 2}") variable
45 model = model.Operation("DIV", i1, i2, act).To(i3)
53 output0 = {i3: # output 0
Dspace_to_depth_v1_2.mod.py56 i3 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 4, 2}") variable
58 Model().Operation("SPACE_TO_DEPTH", i3, 2, layout).To(o3)
62 i3: ("TENSOR_QUANT8_ASYMM", 1.0, 0),
68 i3: [10, 20, 11, 21, 12, 22, 13, 23,
76 }).AddNchw(i3, o3, layout).AddVariations("relaxed", "float16", quant8)
Ddepth_to_space_v1_2.mod.py56 i3 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 8}") variable
58 Model().Operation("DEPTH_TO_SPACE", i3, 2, layout).To(o3)
62 i3: ("TENSOR_QUANT8_ASYMM", 1.0, 0),
68 i3: [10, 20, 11, 21, 14, 24, 15, 25,
76 }).AddNchw(i3, o3, layout).AddVariations("relaxed", "float16", quant8)
Droi_pooling.mod.py116 i3 = Input("in", "TENSOR_FLOAT32", "{4, 4, 4, 1}") variable
119 Model().Operation("ROI_POOLING", i3, roi3, [2, 2, 2, 2, 2], 2, 2, 2.0, 1.0, layout).To(o3)
122 i3: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
129 i3: [
152 }).AddNchw(i3, o3, layout).AddVariations("relaxed", quant8, "float16")
Dgrouped_conv2d.mod.py105 i3 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 9}") # input 0 variable
109 Model("channel").Operation("GROUPED_CONV_2D", i3, w3, b3, 1, 1, 1, 3, 0, layout).To(o3)
113 i3: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
120 i3: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
127 i3: [1, 2, 3, 4, 55, 4, 3, 2, 1,
135 }).AddNchw(i3, o3, layout).AddVariations("relaxed", quant8, channelQuant8, "float16")
/frameworks/av/media/libstagefright/codecs/amrnb/enc/src/
Ds10_8pf.cpp568 Word16 i0, i1, i2, i3, i4, i5, i6, i7, i9; in search_10and8i40() local
638 for (i3 = ipos[3]; i3 < L_CODE; i3 += step) in search_10and8i40()
640 p_temp2 = &rr[i3][0]; in search_10and8i40()
641 s = (Word32) * (p_temp2 + i3) >> 1; in search_10and8i40()
644 *(p_temp1++) = ps0 + dn[i3]; in search_10and8i40()
672 for (i3 = ipos[3]; i3 < L_CODE; i3 += step) in search_10and8i40()
679 alp2 = (alp1 + p_temp2[i3]) >> 2; in search_10and8i40()
687 ib = i3; in search_10and8i40()
693 i3 = ib; in search_10and8i40()
711 s += (Word32) * (p_temp2 + i3); in search_10and8i40()
[all …]
/frameworks/rs/
DrsCppUtils.h174 static inline uint16_t rsBoxFilter565(uint16_t i1, uint16_t i2, uint16_t i3, uint16_t i4) { in rsBoxFilter565() argument
175 uint32_t r = ((i1 & 0x1f) + (i2 & 0x1f) + (i3 & 0x1f) + (i4 & 0x1f)); in rsBoxFilter565()
176 uint32_t g = ((i1 >> 5) & 0x3f) + ((i2 >> 5) & 0x3f) + ((i3 >> 5) & 0x3f) + ((i4 >> 5) & 0x3f); in rsBoxFilter565()
177 uint32_t b = ((i1 >> 11) + (i2 >> 11) + (i3 >> 11) + (i4 >> 11)); in rsBoxFilter565()
181 static inline uint32_t rsBoxFilter8888(uint32_t i1, uint32_t i2, uint32_t i3, uint32_t i4) { in rsBoxFilter8888() argument
182 uint32_t r = (i1 & 0xff) + (i2 & 0xff) + (i3 & 0xff) + (i4 & 0xff); in rsBoxFilter8888()
183 … uint32_t g = ((i1 >> 8) & 0xff) + ((i2 >> 8) & 0xff) + ((i3 >> 8) & 0xff) + ((i4 >> 8) & 0xff); in rsBoxFilter8888()
184 …uint32_t b = ((i1 >> 16) & 0xff) + ((i2 >> 16) & 0xff) + ((i3 >> 16) & 0xff) + ((i4 >> 16) & 0xff); in rsBoxFilter8888()
185 …uint32_t a = ((i1 >> 24) & 0xff) + ((i2 >> 24) & 0xff) + ((i3 >> 24) & 0xff) + ((i4 >> 24) & 0xff); in rsBoxFilter8888()
/frameworks/av/media/libstagefright/codecs/amrwbenc/src/asm/ARMV5E/
Dresidu_asm_opt.s82 SMULTB r11, r5, r10 @i3(0) --- r11 = x[2] * a0
86 SMLABT r11, r5, r2, r11 @i3(1) --- r11 += x[1] * a0
89 SMLATB r11, r6, r2, r11 @i3(2) --- r11 += x[0] * a2
97 SMLABT r11, r6, r2, r11 @i3(3) --- r11 += x[-1] * a3
102 SMLATB r11,r7, r2, r11 @ i3 (4)
108 SMLABT r11,r7, r2, r11 @ i3 (5)
112 SMLATB r11,r8, r2, r11 @ i3 (6)
118 SMLABT r11,r8, r2, r11 @ i3 (7)
122 SMLATB r11,r9, r2, r11 @ i3 (8)
129 SMLABT r11,r9, r2, r11 @ i3 (9)
[all …]
/frameworks/ml/nn/runtime/test/specs/V1_0/
Dconv_3_h3_w2_SAME.mod.py7 i3 = Output("op3", "TENSOR_FLOAT32", "{1, 8, 8, 3}") # output 0 variable
10 model = model.Operation("CONV_2D", i2, i0, i1, i4, i5, i6, i7).To(i3)
14 output0 = {i3: [-1.27853, 1.74987, -0.876718, 0.989692, 0.298548, 0.522103, -0.536896, -0.179382, -…
18 output1 = {i3: [0.78574, 0.0700466, -0.110245, 0.0141003, -0.621007, -0.979104, 1.24104, 0.580398, …
Dconv_1_h3_w2_VALID.mod.py7 i3 = Output("op3", "TENSOR_FLOAT32", "{1, 6, 7, 1}") # output 0 variable
10 model = model.Operation("CONV_2D", i2, i0, i1, i4, i5, i6, i7).To(i3)
14 output0 = {i3: [1.72003, 1.55816, 0.667546, 2.23663, 0.0661516, 0.290254, 0.770222, -1.58197, -0.85…
18 output1 = {i3: [1.28735, 1.91315, 2.51734, 0.375841, 0.637563, 2.653, 2.72959, 1.17389, -2.12119, 2…
Dconv_3_h3_w2_VALID.mod.py7 i3 = Output("op3", "TENSOR_FLOAT32", "{1, 6, 7, 3}") # output 0 variable
10 model = model.Operation("CONV_2D", i2, i0, i1, i4, i5, i6, i7).To(i3)
14 output0 = {i3: [-0.186842, -1.87308, 1.21135, -0.385009, 1.72032, -1.56036, -1.23059, 1.23694, 0.00…
18 output1 = {i3: [1.06709, -1.16534, 1.52694, -0.797245, 0.802736, -0.997109, 2.2661, -1.45548, 2.155…
Dconv_1_h3_w2_SAME.mod.py7 i3 = Output("op3", "TENSOR_FLOAT32", "{1, 8, 8, 1}") # output 0 variable
10 model = model.Operation("CONV_2D", i2, i0, i1, i4, i5, i6, i7).To(i3)
14 output0 = {i3: [1.85284, -0.0393656, -0.127353, 1.43115, -0.302294, -1.0402, 0.655023, -0.587614, 1…
18 output1 = {i3: [-0.000614278, -1.21221, 0.443861, 0.102117, -2.52714, 1.47489, 0.173474, -0.237577,…
Ddepthwise_conv.mod.py8 i3 = Output("op3", "TENSOR_FLOAT32", "{1, 8, 8, 3}") # output 0 variable
11 model = model.Operation("DEPTHWISE_CONV_2D", i2, i0, i1, i4, i5, i6, i7, i8).To(i3)
15 output0 = {i3: [0.840539, -0.301347, 0.754947, -0.14848, -0.40603, 0.294432, 0.130372, 0.11573, -0.…
19 output1 = {i3: [0.285357, 0.00181194, 0.453967, -0.160473, 0.133146, 0.125066, 0.695562, 0.406415, …

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