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/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/
Dbox_with_nms_limit_quant8_signed.mod.py23 o2 = Output("roiOut", "TENSOR_FLOAT32", "{18, 4}") # roi out 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…
32 o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0)
86 o2: [
120 o2 = Output("roiOut", "TENSOR_FLOAT32", "{10, 4}") # roi out 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…
129 o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0)
183 o2: [
209 o2 = Output("roiOut", "TENSOR_FLOAT32", "{12, 4}") # roi out 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 …]
Ddepthwise_conv2d_quant8_signed.mod.py51 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable
52 Model().Operation("DEPTHWISE_CONV_2D", i2, f2, b2, 0, 0, 0, 0, 1, 1, 2, 0, layout, 2, 2).To(o2)
59 o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, -128)
68 o2: [13, 14, 0, 0,
72 }).AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False)
108 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable
109 Model().Operation("DEPTHWISE_CONV_2D", i2, f2, b2, 2, 1, 1, 2, 0, layout, 2, 2).To(o2)
116 o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -128)
125 o2: [13, 14, 0, 0,
129 }, name="valid_padding").AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False)
[all …]
Dconv2d_quant8_signed.mod.py45 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}") variable
46 Model().Operation("CONV_2D", i2, f2, b2, 0, 0, 0, 0, 1, 1, 0, layout, 3, 3).To(o2)
53 o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, -128)
67 o2: [5, 5, 5, 5, 5, 5, 5, 5, 5]
68 }).AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False)
96 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}") variable
97 Model().Operation("CONV_2D", i2, f2, b2, 2, 1, 1, 0, layout, 3, 3).To(o2)
104 o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, -128)
118 o2: [5, 5, 5, 5, 5, 5, 5, 5, 5]
119 }, name="valid_padding").AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False)
[all …]
Dresize_quant8_signed.mod.py45 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 2}") variable
46 model_shape = Model("shape").Operation("RESIZE_BILINEAR", i2, 3, 3, layout).To(o2)
47 model_scale = Model("scale").Operation("RESIZE_BILINEAR", i2, 1.6, 1.6, layout).To(o2)
52 o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -128)
57 o2: [3, 4, 5, 8, 6, 10,
63 Example(test2, model=model_shape).AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefau…
64 Example(test2, model=model_scale).AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefau…
97 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
100 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
124 o2: [],
[all …]
Dtranspose_quant8_signed.mod.py108 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 4, 1}") # output variable
109 Model().Operation("TRANSPOSE_CONV_2D", i2, w2, b2, s2, 1, 3, 3, 1, layout).To(o2)
116 o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 20.0, -78)
124 o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 20.0, -78)
129 o2: [500., 800., 3500., 1500.,
132 }).AddNchw(i2, o2, s2, layout).AddVariations(quant8_signed, channelQuant8_signed, includeDefault=Fa…
220 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
223 …ed").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
252 o2: [],
263 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
[all …]
Dgenerate_proposals_quant8_signed.mod.py25 o2 = Output("roiOut", "TENSOR_FLOAT32", "{4, 4}") # roi out variable
28 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3)
36 o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0)
56 o2: [ # roi out
75 o2 = Output("roiOut", "TENSOR_FLOAT32", "{30, 4}") # roi out variable
78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3)
86 o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0)
173 o2: [ # roi out
Dtranspose_conv2d_quant8_signed.mod.py108 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 4, 1}") # output variable
109 Model().Operation("TRANSPOSE_CONV_2D", i2, w2, b2, s2, 1, 3, 3, 1, layout).To(o2)
116 o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 20.0, -78)
124 o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 20.0, -78)
129 o2: [500., 800., 3500., 1500.,
132 }).AddNchw(i2, o2, s2, layout).AddVariations(quant8_signed, channelQuant8_signed, includeDefault=Fa…
219 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
222 …ed").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
251 o2: [],
262 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
[all …]
Droi_align_quant8_signed.mod.py57 o2 = Output("out", "TENSOR_FLOAT32", "{4, 2, 3, 2}") variable
58 Model().Operation("ROI_ALIGN", i2, roi2, [0, 0, 3, 3], 2, 3, 4.0, 4.0, 4, 4, layout).To(o2)
63 o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.03125, -118)
104 o2: [
118 }).AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False)
220 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
223 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
242 o2: [],
Dmax_pool_quant8_signed.mod.py163 o2 = Output("op4", ("TENSOR_FLOAT32", [bat, output_row, output_col, chn])) variable
164 Model().Operation("MAX_POOL_2D", i2, pad, pad, pad, pad, std, std, flt, flt, 0, layout).To(o2)
169 o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128)
175 o2: [std for _ in range(bat * output_row * output_col * chn)]
176 }).AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False)
233 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
236 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
260 o2: [],
272 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
275 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
[all …]
Davg_pool_quant8_signed.mod.py181 o2 = Output("op4", ("TENSOR_FLOAT32", [bat, output_row, output_col, chn])) variable
182 Model().Operation("AVERAGE_POOL_2D", i2, pad, pad, pad, pad, std, std, flt, flt, 0, layout).To(o2)
187 o2: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128)
193 o2: [1. for _ in range(bat * output_row * output_col * chn)]
194 }).AddNchw(i2, o2, layout).AddVariations(quant8_signed, includeDefault=False)
281 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
284 …ed").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
308 o2: [],
320 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
323 …ed").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
[all …]
/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/
Ddepthwise_conv2d_dilation.mod.py50 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable
51 Model().Operation("DEPTHWISE_CONV_2D", i2, f2, b2, 0, 0, 0, 0, 1, 1, 2, 0, layout, 2, 2).To(o2)
58 o2: ("TENSOR_QUANT8_ASYMM", 0.1, 0)
67 o2: [13, 14, 0, 0,
71 }).AddNchw(i2, o2, layout)
105 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable
106 Model().Operation("DEPTHWISE_CONV_2D", i2, f2, b2, 2, 1, 1, 2, 0, layout, 2, 2).To(o2)
113 o2: ("TENSOR_QUANT8_ASYMM", 0.1, 0)
122 o2: [13, 14, 0, 0,
126 }, name="valid_padding").AddNchw(i2, o2, layout)
[all …]
Ddetection_postprocess.mod.py23 o2 = Output("roiOut", "TENSOR_FLOAT32", "{1, 3, 4}") # roi out variable
26 …STPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, True, 3, 1, 1, 0.0, 0.5, False).To(o1, o2, o3, o4)
57 o2: [
74 o2 = Output("roiOut", "TENSOR_FLOAT32", "{1, 3, 4}") # roi out variable
77 …TPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, False, 3, 1, 1, 0.0, 0.5, False).To(o1, o2, o3, o4)
108 o2: [
125 o2 = Output("roiOut", "TENSOR_FLOAT32", "{1, 3, 4}") # roi out variable
128 …TPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, False, 3, 1, 1, 0.0, 0.5, False).To(o1, o2, o3, o4)
159 o2: [
176 o2 = Output("roiOut", "TENSOR_FLOAT32", "{1, 3, 4}") # roi out variable
[all …]
Dresize_bilinear_v1_2.mod.py45 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 2}") variable
46 model_shape = Model("shape").Operation("RESIZE_BILINEAR", i2, 3, 3, layout).To(o2)
47 model_scale = Model("scale").Operation("RESIZE_BILINEAR", i2, 1.6, 1.6, layout).To(o2)
52 o2: ("TENSOR_QUANT8_ASYMM", 0.25, 0)
57 o2: [3, 4, 5, 8, 6, 10,
63 Example(test2, model=model_shape).AddNchw(i2, o2, layout).AddVariations("relaxed", "float16", quant…
64 Example(test2, model=model_scale).AddNchw(i2, o2, layout).AddVariations("relaxed", "float16", quant…
97 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
100 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
124 o2: [],
[all …]
Dl2_pool_v1_2.mod.py33 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 1, 2, 1}") variable
34 Model().Operation("L2_POOL_2D", i2, 1, 2, 2, 2, 2, 0, layout).To(o2)
39 o2: [3.5, 6.5]
40 }).AddNchw(i2, o2, layout).AddVariations("relaxed", "float16")
61 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
64 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
78 o2: [],
89 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
92 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
106 o2: [],
Dconv2d_dilation.mod.py45 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}") variable
46 Model().Operation("CONV_2D", i2, f2, b2, 0, 0, 0, 0, 1, 1, 0, layout, 3, 3).To(o2)
53 o2: ("TENSOR_QUANT8_ASYMM", 0.125, 0)
67 o2: [5, 5, 5, 5, 5, 5, 5, 5, 5]
68 }).AddNchw(i2, o2, layout).AddVariations("relaxed", quant8, "float16")
96 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}") variable
97 Model().Operation("CONV_2D", i2, f2, b2, 2, 1, 1, 0, layout, 3, 3).To(o2)
104 o2: ("TENSOR_QUANT8_ASYMM", 0.125, 0)
118 o2: [5, 5, 5, 5, 5, 5, 5, 5, 5]
119 }, name="valid_padding").AddNchw(i2, o2, layout).AddVariations("relaxed", quant8, "float16")
Dmax_pool_v1_2.mod.py49 o2 = Output("op4", ("TENSOR_FLOAT32", [bat, output_row, output_col, chn])) variable
50 Model().Operation("MAX_POOL_2D", i2, pad, pad, pad, pad, std, std, flt, flt, 0, layout).To(o2)
55 o2: ("TENSOR_QUANT8_ASYMM", 0.5, 0)
61 o2: [std for _ in range(bat * output_row * output_col * chn)]
62 }).AddNchw(i2, o2, layout).AddVariations("relaxed", quant8, "float16")
117 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
120 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
144 o2: [],
155 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
158 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
[all …]
Dbox_with_nms_limit_hard.mod.py23 o2 = Output("roiOut", "TENSOR_FLOAT32", "{12, 4}") # roi out 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…
32 o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0)
83 o2: [
110 o2 = Output("roiOut", "TENSOR_FLOAT32", "{10, 4}") # roi out 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…
119 o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0)
170 o2: [
Dbox_with_nms_limit_linear.mod.py23 o2 = Output("roiOut", "TENSOR_FLOAT32", "{16, 4}") # roi out 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…
32 o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0)
86 o2: [
117 o2 = Output("roiOut", "TENSOR_FLOAT32", "{15, 4}") # roi out 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…
126 o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0)
180 o2: [
Dbox_with_nms_limit_gaussian.mod.py23 o2 = Output("roiOut", "TENSOR_FLOAT32", "{18, 4}") # roi out 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…
32 o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0)
86 o2: [
119 o2 = Output("roiOut", "TENSOR_FLOAT32", "{10, 4}") # roi out 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…
128 o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0)
182 o2: [
Dtranspose_conv2d.mod.py73 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 4, 1}") # output variable
74 Model().Operation("TRANSPOSE_CONV_2D", i2, w2, b2, s2, 1, 3, 3, 1, layout).To(o2)
81 o2: ("TENSOR_QUANT8_ASYMM", 20.0, 50)
89 o2: ("TENSOR_QUANT8_ASYMM", 20.0, 50)
94 o2: [500., 800., 3500., 1500.,
97 }).AddNchw(i2, o2, s2, layout).AddVariations("relaxed", quant8, channelQuant8, "float16")
184 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
187 …ed").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
216 o2: [],
227 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
[all …]
Dgenerate_proposals.mod.py26 o2 = Output("roiOut", "TENSOR_FLOAT32", "{4, 4}") # roi out variable
29 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3)
37 o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0)
57 o2: [ # roi out
75 o2 = Output("roiOut", "TENSOR_FLOAT32", "{30, 4}") # roi out variable
78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3)
86 o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0)
173 o2: [ # roi out
Davg_pool_v1_2.mod.py51 o2 = Output("op4", ("TENSOR_FLOAT32", [bat, output_row, output_col, chn])) variable
52 Model().Operation("AVERAGE_POOL_2D", i2, pad, pad, pad, pad, std, std, flt, flt, 0, layout).To(o2)
57 o2: ("TENSOR_QUANT8_ASYMM", 0.5, 0)
63 o2: [1. for _ in range(bat * output_row * output_col * chn)]
64 }).AddNchw(i2, o2, layout).AddVariations("relaxed", "float16", quant8)
147 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
150 …ed").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
174 o2: [],
185 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
188 …ed").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
[all …]
Dconv2d_v1_2.mod.py51 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 4, 1}") variable
52 Model().Operation("CONV_2D", i2, f2, b2, 1, 1, 1, 1, layout).To(o2)
59 o2: ("TENSOR_QUANT8_ASYMM", 1.0, 50)
65 o2: ("TENSOR_QUANT8_ASYMM", 1.0, 50)
71 o2: [0, 0, 0, 0, 35, 112, 157, 0, 0, 34, 61, 0]
72 }).AddNchw(i2, o2, layout).AddVariations("relaxed", quant8, channelQuant8, "float16")
220 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
223 …ed").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
251 o2: [],
262 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
[all …]
Droi_align.mod.py57 o2 = Output("out", "TENSOR_FLOAT32", "{4, 2, 3, 2}") variable
58 Model().Operation("ROI_ALIGN", i2, roi2, [0, 0, 3, 3], 2, 3, 4.0, 4.0, 4, 4, layout).To(o2)
63 o2: ("TENSOR_QUANT8_ASYMM", 0.03125, 10)
104 o2: [
118 }).AddNchw(i2, o2, layout).AddVariations("relaxed", quant8, "float16")
220 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
223 …d").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
242 o2: [],
Dconv2d_per_channel.mod.py36 o2 = Output("op4", "TENSOR_QUANT8_ASYMM", "{1, 3, 1, 3}, 1.f, 128") variable
37 Model("layouts").Operation("CONV_2D", i2, f2, b2, 0, 0, 0, 0, 1, 1, 0, layout).To(o2)
42 o2: [121, 118, 115, 121, 118, 115, 121, 118, 115]
43 }).AddNchw(i2, o2, layout)
51 o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out variable
54 …ed").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2)
71 o2: [],

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