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/frameworks/native/libs/input/tests/
DInputWindow_test.cpp35 InputWindowInfo i2 = InputWindowInfo::read(p); in TEST() local
36 ASSERT_TRUE(i2.token == nullptr); in TEST()
73 InputWindowInfo i2 = InputWindowInfo::read(p); in TEST() local
74 ASSERT_EQ(i.token, i2.token); in TEST()
75 ASSERT_EQ(i.id, i2.id); in TEST()
76 ASSERT_EQ(i.name, i2.name); in TEST()
77 ASSERT_EQ(i.layoutParamsFlags, i2.layoutParamsFlags); in TEST()
78 ASSERT_EQ(i.layoutParamsType, i2.layoutParamsType); in TEST()
79 ASSERT_EQ(i.dispatchingTimeout, i2.dispatchingTimeout); in TEST()
80 ASSERT_EQ(i.frameLeft, i2.frameLeft); in TEST()
[all …]
/frameworks/ml/nn/runtime/test/specs/V1_3/
Dbox_with_nms_limit_quant8_signed.mod.py19 i2 = Input("roi", "TENSOR_FLOAT32", "{19, 12}") # roi 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…
30 i2: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
57 i2: [ # roi
116 i2 = Input("roi", "TENSOR_FLOAT32", "{19, 12}") # roi 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…
127 i2: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
154 i2: [ # roi
205 i2 = Input("roi", "TENSOR_FLOAT32", "{19, 12}") # roi 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…
[all …]
Dgenerate_proposals_quant8_signed.mod.py21 i2 = Input("bboxDeltas", "TENSOR_FLOAT32", "{1, 2, 2, 8}") # bounding box deltas variable
28 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3)
32 i2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.05, 0),
44 i2: [ # bounding box deltas
65 Example((input0, output0)).AddNchw(i1, i2, layout).AddVariations(quant8_signed, includeDefault=Fals…
71 i2 = Input("bboxDeltas", "TENSOR_FLOAT32", "{2, 4, 4, 16}") # bounding box deltas variable
78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3)
82 i2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0),
124 i2: [ # bounding box deltas
211 Example((input0, output0)).AddNchw(i1, i2, layout).AddVariations(quant8_signed, includeDefault=Fals…
Dmul_quant8_signed.mod.py19 i2 = Input("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 2}, 1.0, -128") variable
22 model = model.Operation("MUL", i1, i2, act).To(i3)
27 i2: # input 1
40 i2 = Input("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 1.0, -128") variable
43 model = model.Operation("MUL", i1, i2, act).To(i3)
48 i2: # input 1
76 i2 = Parameter("op", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [1, 2, 3, 4]) # weights variable
78 model = model.Operation("MUL", zero_sized, i2, 0).To(o3)
87 i2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0),
Dadd_quant8_signed.mod.py19 i2 = Input("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{2}, 1.0, 0") variable
22 model = model.Operation("ADD", i1, i2, act).To(i3)
27 i2: # input 1
40 i2 = Input("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 2}, 1.0, 0") variable
43 model = model.Operation("ADD", i1, i2, act).To(i3)
48 i2: # input 1
76 i2 = Parameter("op", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [1, 2, 3, 4]) # weights variable
78 model = model.Operation("ADD", zero_sized, i2, 0).To(o3)
87 i2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0),
Ddepthwise_conv2d_quant8_signed.mod.py48 i2 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 4, 2}") variable
52 Model().Operation("DEPTHWISE_CONV_2D", i2, f2, b2, 0, 0, 0, 0, 1, 1, 2, 0, layout, 2, 2).To(o2)
56 i2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128),
64 i2: [0, 0, 0, 0, 0, 0, 0, 0,
72 }).AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False)
105 i2 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 4, 2}") variable
109 Model().Operation("DEPTHWISE_CONV_2D", i2, f2, b2, 2, 1, 1, 2, 0, layout, 2, 2).To(o2)
113 i2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128),
121 i2: [0, 0, 0, 0, 0, 0, 0, 0,
129 }, name="valid_padding").AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False)
[all …]
Dbatch_to_space_quant8_signed.mod.py54 i2 = Input("op1", "TENSOR_FLOAT32", "{4, 2, 2, 1}") variable
56 Model().Operation("BATCH_TO_SPACE_ND", i2, [2, 2], layout).To(o2)
60 i2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, 0),
66 i2: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16],
68 }).AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False)
Ddequantize_quant8_signed.mod.py19 i2 = Output("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable
20 model = model.Operation("DEQUANTIZE", i1).To(i2)
26 output0 = {i2: # output 0
63 i2 = Output("op2", "TENSOR_FLOAT16", "{1, 2, 2, 1}") variable
64 model = model.Operation("DEQUANTIZE", i1).To(i2)
70 output0 = {i2: # output 0
/frameworks/ml/nn/runtime/test/specs/V1_2/
Ddepthwise_conv2d_dilation.mod.py47 i2 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 4, 2}") variable
51 Model().Operation("DEPTHWISE_CONV_2D", i2, f2, b2, 0, 0, 0, 0, 1, 1, 2, 0, layout, 2, 2).To(o2)
55 i2: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
63 i2: [0, 0, 0, 0, 0, 0, 0, 0,
71 }).AddNchw(i2, o2, layout)
102 i2 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 4, 2}") variable
106 Model().Operation("DEPTHWISE_CONV_2D", i2, f2, b2, 2, 1, 1, 2, 0, layout, 2, 2).To(o2)
110 i2: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
118 i2: [0, 0, 0, 0, 0, 0, 0, 0,
126 }, name="valid_padding").AddNchw(i2, o2, layout)
[all …]
Ddetection_postprocess.mod.py19 i2 = Input("roi", "TENSOR_FLOAT32", "{1, 6, 4}") # roi variable
26 Model("regular").Operation("DETECTION_POSTPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, True, 3, 1…
37 i2: [ # six boxes in center-size encoding
70 i2 = Input("roi", "TENSOR_FLOAT32", "{1, 6, 4}") # roi variable
77 Model().Operation("DETECTION_POSTPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, False, 3, 1, 1, 0.0…
88 i2: [ # six boxes in center-size encoding
121 i2 = Input("roi", "TENSOR_FLOAT32", "{1, 6, 7}") # roi variable
128 Model().Operation("DETECTION_POSTPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, False, 3, 1, 1, 0.0…
139 i2: [ # six boxes in center-size encoding
172 i2 = Input("roi", "TENSOR_FLOAT32", "{1, 6, 7}") # roi variable
[all …]
Dgenerate_proposals.mod.py22 i2 = Input("bboxDeltas", "TENSOR_FLOAT32", "{1, 2, 2, 8}") # bounding box deltas variable
29 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3)
33 i2: ("TENSOR_QUANT8_ASYMM", 0.05, 128),
45 i2: [ # bounding box deltas
66 Example((input0, output0)).AddNchw(i1, i2, layout).AddVariations("relaxed", quant8, "float16")
71 i2 = Input("bboxDeltas", "TENSOR_FLOAT32", "{2, 4, 4, 16}") # bounding box deltas variable
78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3)
82 i2: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
124 i2: [ # bounding box deltas
211 Example((input0, output0)).AddNchw(i1, i2, layout).AddVariations("relaxed", quant8, "float16")
Dadd_v1_2.mod.py20 i2 = Input("op2", "TENSOR_FLOAT16", "{3}") # another vector of 3 float16s variable
23 model = model.Operation("ADD", i1, i2, act).To(i3)
29 i2: # input 1
42 i2 = Input("op2", "TENSOR_FLOAT16", "{2, 2}") variable
45 model = model.Operation("ADD", i1, i2, act).To(i3)
50 i2: # input 1
78 i2 = Parameter("op", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [1, 2, 3, 4]) # weights variable
80 model = model.Operation("ADD", zero_sized, i2, 0).To(o3)
89 i2: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
Dmul_v1_2.mod.py20 i2 = Input("op2", "TENSOR_FLOAT16", "{3}") # another vector of 3 float16s variable
23 model = model.Operation("MUL", i1, i2, act).To(i3)
29 i2: # input 1
42 i2 = Input("op2", "TENSOR_FLOAT16", "{2, 2}") variable
45 model = model.Operation("MUL", i1, i2, act).To(i3)
50 i2: # input 1
78 i2 = Parameter("op", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [1, 2, 3, 4]) # weights variable
80 model = model.Operation("MUL", zero_sized, i2, 0).To(o3)
89 i2: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
Dbox_with_nms_limit_gaussian.mod.py19 i2 = Input("roi", "TENSOR_FLOAT32", "{19, 12}") # roi 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…
30 i2: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
57 i2: [ # roi
115 i2 = Input("roi", "TENSOR_FLOAT32", "{19, 12}") # roi 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…
126 i2: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
153 i2: [ # roi
Dbox_with_nms_limit_linear.mod.py19 i2 = Input("roi", "TENSOR_FLOAT32", "{19, 12}") # roi 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…
30 i2: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
57 i2: [ # roi
113 i2 = Input("roi", "TENSOR_FLOAT32", "{19, 12}") # roi 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…
124 i2: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
151 i2: [ # roi
Dbox_with_nms_limit_hard.mod.py19 i2 = Input("roi", "TENSOR_FLOAT32", "{19, 12}") # roi 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…
30 i2: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
57 i2: [ # roi
106 i2 = Input("roi", "TENSOR_FLOAT32", "{19, 12}") # roi 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…
117 i2: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
144 i2: [ # roi
Dconv2d_dilation.mod.py42 i2 = Input("op1", "TENSOR_FLOAT32", "{1, 9, 9, 1}") variable
46 Model().Operation("CONV_2D", i2, f2, b2, 0, 0, 0, 0, 1, 1, 0, layout, 3, 3).To(o2)
50 i2: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
58 i2: [0, 0, 0, 0, 0, 0, 0, 0, 0,
68 }).AddNchw(i2, o2, layout).AddVariations("relaxed", quant8, "float16")
93 i2 = Input("op1", "TENSOR_FLOAT32", "{1, 9, 9, 1}") variable
97 Model().Operation("CONV_2D", i2, f2, b2, 2, 1, 1, 0, layout, 3, 3).To(o2)
101 i2: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
109 i2: [0, 0, 0, 0, 0, 0, 0, 0, 0,
119 }, name="valid_padding").AddNchw(i2, o2, layout).AddVariations("relaxed", quant8, "float16")
Ddiv_v1_2.mod.py20 i2 = Input("op2", "TENSOR_FLOAT16", "{3}") # another vector of 3 float16s variable
23 model = model.Operation("DIV", i1, i2, act).To(i3)
29 i2: # input 1
42 i2 = Input("op2", "TENSOR_FLOAT16", "{1, 2}") variable
45 model = model.Operation("DIV", i1, i2, act).To(i3)
50 i2: # input 1
78 i2 = Parameter("op", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [1, 2, 3, 4]) # weights variable
80 model = model.Operation("DIV", zero_sized, i2, 0).To(o3)
Dbatch_to_space_v1_2.mod.py38 i2 = Input("op1", "TENSOR_FLOAT32", "{4, 2, 2, 1}") variable
40 Model().Operation("BATCH_TO_SPACE_ND", i2, [2, 2], layout).To(o2)
44 i2: ("TENSOR_QUANT8_ASYMM", 0.5, 128),
50 i2: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16],
52 }).AddNchw(i2, o2, layout).AddVariations("relaxed", "float16", quant8)
Ddepth_to_space_v1_2.mod.py38 i2 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable
40 Model().Operation("DEPTH_TO_SPACE", i2, 2, layout).To(o2)
44 i2: ("TENSOR_QUANT8_ASYMM", 0.5, 128),
50 i2: [1., 2., 5., 6., 3., 4., 7., 8., 9., 10., 13., 14., 11., 12., 15., 16.],
52 }).AddNchw(i2, o2, layout).AddVariations("relaxed", "float16", quant8)
Dspace_to_depth_v1_2.mod.py38 i2 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 4, 1}") variable
40 Model().Operation("SPACE_TO_DEPTH", i2, 2, layout).To(o2)
44 i2: ("TENSOR_QUANT8_ASYMM", 0.5, 128),
50 i2: [1., 2., 5., 6., 3., 4., 7., 8., 9., 10., 13., 14., 11., 12., 15., 16.],
52 }).AddNchw(i2, o2, layout).AddVariations("relaxed", "float16", quant8)
/frameworks/base/core/java/android/os/
DWorkSource.java629 int i1 = 0, i2 = 0; in removeUids() local
631 while (i1 < N1 && i2 < N2) { in removeUids()
632 if (DEBUG) Log.d(TAG, "Step: target @ " + i1 + " of " + N1 + ", other @ " + i2 in removeUids()
634 if (uids2[i2] == uids1[i1]) { in removeUids()
635 if (DEBUG) Log.d(TAG, "i1=" + i1 + " i2=" + i2 + " N1=" + N1 in removeUids()
640 i2++; in removeUids()
641 } else if (uids2[i2] > uids1[i1]) { in removeUids()
642 if (DEBUG) Log.d(TAG, "i1=" + i1 + " i2=" + i2 + " N1=" + N1 + ": skip i1"); in removeUids()
645 if (DEBUG) Log.d(TAG, "i1=" + i1 + " i2=" + i2 + " N1=" + N1 + ": skip i2"); in removeUids()
646 i2++; in removeUids()
[all …]
/frameworks/layoutlib/create/tests/src/com/android/tools/layoutlib/create/
DDelegateClassAdapterTest.java105 Object i2 = clazz2.newInstance(); in testNoOp()
106 assertNotNull(i2); in testNoOp()
107 assertEquals(42, callAdd(i2, 20, 22)); in testNoOp()
110 callCallNativeInstance(i2, 10, 3.1415, new Object[0]); in testNoOp()
160 Object i2 = clazz2.newInstance(); in testConstructorAfterDelegate()
161 assertNotNull(i2); in testConstructorAfterDelegate()
162 assertEquals(123, clazz2.getField("mId").getInt(i2)); in testConstructorAfterDelegate()
195 Object i2 = clazz2.getConstructor(outerClazz2).newInstance(o2); in testInnerConstructorAfterDelegate()
196 assertNotNull(i2); in testInnerConstructorAfterDelegate()
197 assertEquals(98, clazz2.getField("mInnerId").getInt(i2)); in testInnerConstructorAfterDelegate()
[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/ml/nn/runtime/test/specs/V1_0/
Drelu6_quant8_1.mod.py20 i2 = Output("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 1}, 0.5f, 0") # output 0 variable
21 model = model.Operation("RELU6", i1).To(i2)
26 output0 = {i2: # output 0
34 output1 = {i2: # output 0

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