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/frameworks/ml/nn/runtime/test/specs/V1_2/
Dresize_nearest_neighbor.mod.py20 i1 = Input("in", "TENSOR_FLOAT32", "{1, 2, 2, 1}") # input 0 variable
22 model_shape = Model("shape").Operation("RESIZE_NEAREST_NEIGHBOR", i1, 1, 1, layout).To(o1)
23 model_scale = Model("scale").Operation("RESIZE_NEAREST_NEIGHBOR", i1, 0.5, 0.5, layout).To(o1)
27 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
32 i1: [1, 2, 3, 4],
36 Example(test1, model=model_shape).AddNchw(i1, o1, layout).AddVariations("relaxed", quant8, "float16…
37 Example(test1, model=model_scale).AddNchw(i1, o1, layout).AddVariations("relaxed", quant8, "float16…
41 i1 = Input("in", "TENSOR_FLOAT32", "{1, 2, 2, 1}") # input 0 variable
43 model_shape = Model("shape").Operation("RESIZE_NEAREST_NEIGHBOR", i1, 3, 3, layout).To(o1)
44 model_scale = Model("scale").Operation("RESIZE_NEAREST_NEIGHBOR", i1, 1.5, 1.5, layout).To(o1)
[all …]
Dresize_bilinear_v1_2.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable
22 model_shape = Model("shape").Operation("RESIZE_BILINEAR", i1, 3, 3, layout).To(o1)
23 model_scale = Model("scale").Operation("RESIZE_BILINEAR", i1, 1.5, 1.5, layout).To(o1)
27 i1: ("TENSOR_QUANT8_ASYMM", 0.01, 0),
32 i1: [1.0, 1.0, 2.0, 2.0],
39 Example(test1, model=model_shape).AddNchw(i1, o1, layout).AddVariations("relaxed", "float16", quant…
40 Example(test1, model=model_scale).AddNchw(i1, o1, layout).AddVariations("relaxed", "float16", quant…
103 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
105 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
116 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
[all …]
Ddetection_postprocess.mod.py18 i1 = Input("scores", "TENSOR_FLOAT32", "{1, 6, 3}") # scores variable
26 Model("regular").Operation("DETECTION_POSTPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, True, 3, 1…
29 i1: [ # class scores - two classes with background
69 i1 = Input("scores", "TENSOR_FLOAT32", "{1, 6, 3}") # scores variable
77 Model().Operation("DETECTION_POSTPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, False, 3, 1, 1, 0.0…
80 i1: [ # class scores - two classes with background
120 i1 = Input("scores", "TENSOR_FLOAT32", "{1, 6, 3}") # scores variable
128 Model().Operation("DETECTION_POSTPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, False, 3, 1, 1, 0.0…
131 i1: [ # class scores - two classes with background
171 i1 = Input("scores", "TENSOR_FLOAT32", "{1, 6, 3}") # scores variable
[all …]
Dgenerate_proposals.mod.py21 i1 = Input("scores", "TENSOR_FLOAT32", "{1, 2, 2, 2}") # scores variable
29 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3)
32 i1: ("TENSOR_QUANT8_ASYMM", 0.01, 100),
41 i1: [ # scores
66 Example((input0, output0)).AddNchw(i1, i2, layout).AddVariations("relaxed", quant8, "float16")
70 i1 = Input("scores", "TENSOR_FLOAT32", "{2, 4, 4, 4}") # scores variable
78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3)
81 i1: ("TENSOR_QUANT8_ASYMM", 0.005, 0),
90 i1: [ # scores
211 Example((input0, output0)).AddNchw(i1, i2, layout).AddVariations("relaxed", quant8, "float16")
Dl2_pool_v1_2.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable
22 Model().Operation("L2_POOL_2D", i1, 0, 0, 0, 0, 1, 1, 1, 1, 0, layout).To(o1)
26 i1: [1.0, 2.0, 3.0, 4.0],
28 }).AddNchw(i1, o1, layout).AddRelaxed().AddVariations("float16")
67 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
69 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
77 i1: [1],
81 }).AddNchw(i1, zero_sized, o3, layout).AddVariations("relaxed", "float16")
96 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
98 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
[all …]
Dmul_v1_2.mod.py19 i1 = Input("op1", "TENSOR_FLOAT16", "{3}") # a vector of 3 float16s variable
23 model = model.Operation("MUL", i1, i2, act).To(i3)
27 input0 = {i1: # input 0
41 i1 = Input("op1", "TENSOR_FLOAT16", "{1, 2}") variable
45 model = model.Operation("MUL", i1, i2, act).To(i3)
48 input0 = {i1: # input 0
73 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 2}") variable
75 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
87 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
95 i1: [1, 2],
Dadd_v1_2.mod.py19 i1 = Input("op1", "TENSOR_FLOAT16", "{3}") # a vector of 3 float16s variable
23 model = model.Operation("ADD", i1, i2, act).To(i3)
27 input0 = {i1: # input 0
41 i1 = Input("op1", "TENSOR_FLOAT16", "{1, 2}") variable
45 model = model.Operation("ADD", i1, i2, act).To(i3)
48 input0 = {i1: # input 0
73 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 2}") variable
75 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
87 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
95 i1: [1, 2],
Ddiv_v1_2.mod.py19 i1 = Input("op1", "TENSOR_FLOAT16", "{3}") # a vector of 3 float16s variable
23 model = model.Operation("DIV", i1, i2, act).To(i3)
27 input0 = {i1: # input 0
41 i1 = Input("op1", "TENSOR_FLOAT16", "{2, 2}") variable
45 model = model.Operation("DIV", i1, i2, act).To(i3)
48 input0 = {i1: # input 0
73 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 2}") variable
75 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
84 i1: [1, 2],
Dprelu.mod.py18 i1 = Input("input", "TENSOR_FLOAT32", "{1, 2, 2, 3}") variable
21 Model().Operation("PRELU", i1, a1).To(o1)
25 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
32 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
39 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
46 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
53 i1: [ 0, 0, 0,
Dtranspose_v1_2.mod.py19 i1 = Input("input", "TENSOR_FLOAT32", "{2, 2}") variable
23 model = model.Operation("TRANSPOSE", i1, perms).To(output)
27 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
33 i1: [1.0, 2.0,
57 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
59 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
70 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
77 i1: [1],
Dbox_with_nms_limit_linear.mod.py18 i1 = Input("scores", "TENSOR_FLOAT32", "{19, 3}") # scores 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…
29 i1: ("TENSOR_QUANT8_ASYMM", 0.01, 0),
36 i1: [ # scores
112 i1 = Input("scores", "TENSOR_FLOAT32", "{19, 3}") # scores 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…
123 i1: ("TENSOR_QUANT8_ASYMM", 0.01, 128),
130 i1: [ # scores
Dbox_with_nms_limit_hard.mod.py18 i1 = Input("scores", "TENSOR_FLOAT32", "{19, 3}") # scores 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…
29 i1: ("TENSOR_QUANT8_ASYMM", 0.01, 0),
36 i1: [ # scores
105 i1 = Input("scores", "TENSOR_FLOAT32", "{19, 3}") # scores 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…
116 i1: ("TENSOR_QUANT8_ASYMM", 0.01, 128),
123 i1: [ # scores
Dbox_with_nms_limit_gaussian.mod.py18 i1 = Input("scores", "TENSOR_FLOAT32", "{19, 3}") # scores 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…
29 i1: ("TENSOR_QUANT8_ASYMM", 0.01, 0),
36 i1: [ # scores
114 i1 = Input("scores", "TENSOR_FLOAT32", "{19, 3}") # scores 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…
125 i1: ("TENSOR_QUANT8_ASYMM", 0.01, 128),
132 i1: [ # scores
Dmax_pool_v1_2.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable
22 Model().Operation("MAX_POOL_2D", i1, 0, 0, 0, 0, 1, 1, 1, 1, 0, layout).To(o1)
26 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
32 i1: [1.0, 2.0, 3.0, 4.0],
34 }).AddNchw(i1, o1, layout).AddVariations("relaxed", quant8, "float16")
123 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
125 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
136 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
143 i1: [1],
147 }).AddNchw(i1, zero_sized, o3, layout).AddVariations("relaxed", quant8, "float16")
[all …]
Ddepthwise_conv2d_dilation.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 2}") variable
24 Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 2, 0, layout, 1, 1).To(o1)
28 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
36 i1: [10, 21, 10, 22, 10, 23,
43 }).AddNchw(i1, o1, layout).AddInput(f1, b1).AddVariations("relaxed", "float16", quant8)
75 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 2}") variable
79 Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 2, 1, 1, 2, 0, layout, 1, 1).To(o1)
83 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
91 i1: [10, 21, 10, 22, 10, 23,
98 }, name="valid_padding").AddNchw(i1, o1, layout).AddInput(f1, b1).AddVariations("relaxed", "float16…
Dtranspose_conv2d.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") # input 0 variable
26 Model().Operation("TRANSPOSE_CONV_2D", i1, w1, b1, s1, 2, 2, 2, act, layout).To(o1)
30 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
37 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 100),
45 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 100),
52 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 100),
59 i1: [1, 2, 3, 4],
65 }).AddNchw(i1, o1, s1, layout).AddAllActivations(o1, act).AddVariations("relaxed", quant8, quant8_m…
190 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
192 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
[all …]
Dconv2d_dilation.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 1}") variable
24 Model().Operation("CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 0, layout, 1, 1).To(o1)
28 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
36 i1: [1.0, 1.0, 1.0, 1.0, 0.5, 1.0, 1.0, 1.0, 1.0],
38 }).AddNchw(i1, o1, layout).AddInput(f1, b1).AddVariations("relaxed", quant8, "float16")
71 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 1}") variable
75 Model().Operation("CONV_2D", i1, f1, b1, 2, 1, 1, 0, layout, 1, 1).To(o1)
79 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
87 i1: [1.0, 1.0, 1.0, 1.0, 0.5, 1.0, 1.0, 1.0, 1.0],
89 }, name="valid_padding").AddNchw(i1, o1, layout).AddInput(f1, b1).AddVariations("relaxed", quant8, …
Davg_pool_v1_2.mod.py20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable
22 Model().Operation("AVERAGE_POOL_2D", i1, 0, 0, 0, 0, 1, 1, 1, 1, 0, layout).To(o1)
26 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
32 i1: [1.0, 2.0, 3.0, 4.0],
34 }).AddNchw(i1, o1, layout).AddVariations("relaxed", "float16", quant8)
151 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
153 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
164 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
171 i1: [1],
175 }).AddNchw(i1, zero_sized, o3, layout).AddVariations("relaxed", quant8, "float16")
[all …]
Dconcat_zero_sized.mod.py30 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
32 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
43 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
50 i1: [1],
70 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
72 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
84 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
92 i1: [1],
Droi_align.mod.py20 i1 = Input("in", "TENSOR_FLOAT32", "{1, 4, 4, 1}") variable
23 Model().Operation("ROI_ALIGN", i1, roi1, [0, 0, 0, 0], 2, 2, 2.0, 2.0, 4, 4, layout).To(o1)
26 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
33 i1: [
51 }).AddNchw(i1, o1, layout).AddVariations("relaxed", quant8, "float16")
226 i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") variable
228 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
235 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128),
241 i1: [0],
245 }).AddNchw(i1, zero_sized, layout).AddVariations("relaxed", quant8, "float16")
Dchannel_shuffle.mod.py17 i1 = Input("op1", "TENSOR_FLOAT32", "{2, 2, 3, 12}") # input 0 variable
20 Model().Operation("CHANNEL_SHUFFLE", i1, 3, axis).To(o1)
24 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
29 i1: list(range(2*2*3*12)),
42 }).AddVariations("relaxed", quant8, "float16").AddAllDimsAndAxis(i1, o1, axis)
Dl2_normalization_axis.mod.py17 i1 = Input("op1", "TENSOR_FLOAT32", "{2, 2, 2, 3}") # input 0 variable
22 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 32),
27 i1: [ 0, 3, 4,
46 Model().Operation("L2_NORMALIZATION", i1, axis).To(o1)
47 Example(example0).AddRelaxed().AddAllDimsAndAxis(i1, o1, axis).AddVariations("relaxed", "float16", …
Dl2_normalization_v1_2.mod.py17 i1 = Input("op1", "TENSOR_FLOAT32", "{2, 2, 2, 3}") # input 0 variable
22 i1: ("TENSOR_QUANT8_ASYMM", 0.1, 32),
27 i1: [ 0, 3, 4,
46 Model().Operation("L2_NORMALIZATION", i1).To(o1)
47 Example(example0).AddRelaxed().AddAllDims(i1, o1).AddVariations("relaxed", "float16", quant8)
Dconv2d_per_channel.mod.py17 i1 = Input("op1", "TENSOR_QUANT8_ASYMM", "{1, 3, 1, 2}, 0.5f, 128") variable
22 Model().Operation("CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 0).To(o1)
26 i1: [138, 138, 138, 138, 138, 138],
57 i1 = Input("in", "TENSOR_QUANT8_ASYMM", "{1, 1, 1, 2}, 0.5f, 128") variable
59 model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized)
70 i1: [130, 130],
74 }).AddNchw(i1, zero_sized, o3, layout)
/frameworks/base/core/java/android/os/
DWorkSource.java558 int i1 = 0, i2 = 0; in removeUids() local
560 while (i1 < N1 && i2 < N2) { in removeUids()
561 if (DEBUG) Log.d(TAG, "Step: target @ " + i1 + " of " + N1 + ", other @ " + i2 in removeUids()
563 if (uids2[i2] == uids1[i1]) { in removeUids()
564 if (DEBUG) Log.d(TAG, "i1=" + i1 + " i2=" + i2 + " N1=" + N1 in removeUids()
565 + ": remove " + uids1[i1]); in removeUids()
568 if (i1 < N1) System.arraycopy(uids1, i1+1, uids1, i1, N1-i1); in removeUids()
570 } else if (uids2[i2] > uids1[i1]) { in removeUids()
571 if (DEBUG) Log.d(TAG, "i1=" + i1 + " i2=" + i2 + " N1=" + N1 + ": skip i1"); in removeUids()
572 i1++; in removeUids()
[all …]

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