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/frameworks/ml/nn/runtime/test/specs/V1_3/
Dbox_with_nms_limit_quant8_signed.mod.py24 o3 = Output("classesOut", "TENSOR_INT32", "{18}") # classes out variable
26 …= Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 2, 0.4, 0.5, 0.3).To(o1, o2, o3, o4)
106 o3: [1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2],
121 o3 = Output("classesOut", "TENSOR_INT32", "{10}") # classes 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…
195 o3: [1, 1, 1, 2, 2, 1, 1, 1, 2, 2],
210 o3 = Output("classesOut", "TENSOR_INT32", "{12}") # classes out variable
212 …= Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, o2, o3, o4)
283 o3: [1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 2],
298 o3 = Output("classesOut", "TENSOR_INT32", "{10}") # classes out variable
[all …]
Dresize_quant8_signed.mod.py69 o3 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}") variable
70 model_shape = Model("shape").Operation("RESIZE_BILINEAR", i3, 3, 3).To(o3)
71 model_scale = Model("scale").Operation("RESIZE_BILINEAR", i3, 1.8, 1.8).To(o3)
76 o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, -128)
81 o3: [1.0, 1.0, 1.0,
108 o3 = Output("out", "TENSOR_FLOAT32", "{0, 3, 3, 1}") # out variable
109 model = model.Operation("RESIZE_BILINEAR", zero_sized, 3, 3, layout).To(o3)
118 o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0)
125 o3: [],
126 }).AddNchw(i1, zero_sized, o3, layout).AddVariations(quant8_signed, includeDefault=False)
[all …]
Dtranspose_quant8_signed.mod.py141 o3 = Output("op4", "TENSOR_FLOAT32", "{1, 4, 4, 1}") # output variable
142 Model().Operation("TRANSPOSE_CONV_2D", i3, w3, b3, s3, 1, 1, 1, 0, layout).To(o3)
149 o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 16.0, -128)
155 o3: [184, 412, 568, 528,
159 }).AddNchw(i3, o3, s3, layout).AddVariations(quant8_signed, includeDefault=False)
234 o3 = Output("out", "TENSOR_FLOAT32", "{0, 5, 5, 2}") # out variable
235 model = model.Operation("TRANSPOSE_CONV_2D", zero_sized, w, b, s, 2, 2, 2, 0, layout).To(o3)
246 o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0)
253 o3: [],
254 }).AddNchw(i1, zero_sized, o3, s, layout).AddVariations(quant8_signed, includeDefault=False)
[all …]
Dtranspose_conv2d_quant8_signed.mod.py140 o3 = Output("op4", "TENSOR_FLOAT32", "{1, 4, 4, 1}") # output variable
141 Model().Operation("TRANSPOSE_CONV_2D", i3, w3, b3, s3, 1, 1, 1, 0, layout).To(o3)
148 o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 16.0, -128)
154 o3: [184, 412, 568, 528,
158 }).AddNchw(i3, o3, s3, layout).AddVariations(quant8_signed, includeDefault=False)
233 o3 = Output("out", "TENSOR_FLOAT32", "{0, 5, 5, 2}") # out variable
234 model = model.Operation("TRANSPOSE_CONV_2D", zero_sized, w, b, s, 2, 2, 2, 0, layout).To(o3)
245 o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0)
252 o3: [],
253 }).AddNchw(i1, zero_sized, o3, s, layout).AddVariations(quant8_signed, includeDefault=False)
[all …]
Dconv2d_quant8_signed.mod.py126 o3 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}") variable
127 Model().Operation("CONV_2D", i3, f3, b3, 1, 2, 2, 0, layout, 3, 3).To(o3)
134 o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, -128)
145 o3: [16, 0, 9, 0, 0, 0, 4, 0, 1]
146 }).AddNchw(i3, o3, layout).AddVariations(quant8_signed, includeDefault=False)
197 o3 = Output("out", "TENSOR_QUANT8_ASYMM_SIGNED", "{0, 2, 2, 3}, 1.f, 0") # out variable
198 model = model.Operation("CONV_2D", zero_sized, w, b, 0, 0, 0, 0, 1, 1, 0, layout).To(o3)
204 o3: [],
205 }).AddNchw(i1, zero_sized, o3, layout)
269 o3 = Output("op4", "TENSOR_FLOAT32", "{1, 1, 1, 3}") variable
[all …]
Dgenerate_proposals_quant8_signed.mod.py26 o3 = Output("batchSplit", "TENSOR_INT32", "{4}") # batch split out variable
28 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3)
62 o3: [0, 0, 0, 0]
76 o3 = Output("batchSplit", "TENSOR_INT32", "{30}") # batch split out variable
78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3)
205 o3: [
Dmax_pool_quant8_signed.mod.py192 o3 = Output("op4", ("TENSOR_FLOAT32", [bat, output_row, output_col, chn])) variable
193 Model().Operation("MAX_POOL_2D", i3, pad, pad, pad, pad, std, std, flt, flt, 3, layout).To(o3)
198 o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -128)
204 o3: [6 for _ in range(bat * output_row * output_col * chn)]
205 }).AddNchw(i3, o3, layout).AddVariations(quant8_signed, includeDefault=False)
244 o3 = Output("out", "TENSOR_FLOAT32", "{0, 1, 1, 1}") # out variable
245 model = model.Operation("MAX_POOL_2D", zero_sized, 0, 0, 0, 0, 1, 1, 2, 2, 0, layout).To(o3)
254 o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0)
261 o3: [],
262 }).AddNchw(i1, zero_sized, o3, layout).AddVariations(quant8_signed, includeDefault=False)
[all …]
Davg_pool_quant8_signed.mod.py210 o3 = Output("op4", ("TENSOR_FLOAT32", [bat, output_row, output_col, chn])) variable
211 Model().Operation("AVERAGE_POOL_2D", i3, pad, pad, pad, pad, std, std, flt, flt, 0, layout).To(o3)
216 o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -128)
222 o3: [.5 for _ in range(bat * output_row * output_col * chn)]
223 }).AddNchw(i3, o3, layout).AddVariations(quant8_signed, includeDefault=False)
292 o3 = Output("out", "TENSOR_FLOAT32", "{0, 1, 1, 1}") # out variable
293 model = model.Operation("AVERAGE_POOL_2D", zero_sized, 0, 0, 0, 0, 1, 1, 2, 2, 0, layout).To(o3)
302 o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0)
309 o3: [],
310 }).AddNchw(i1, zero_sized, o3, layout).AddVariations(quant8_signed, includeDefault=False)
[all …]
Droi_pooling_quant8_signed.mod.py118 o3 = Output("out", "TENSOR_FLOAT32", "{5, 2, 2, 1}") variable
119 Model().Operation("ROI_POOLING", i3, roi3, [2, 2, 2, 2, 2], 2, 2, 2.0, 1.0, layout).To(o3)
124 o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, 0)
145 o3: [
152 }).AddNchw(i3, o3, layout).AddVariations(quant8_signed, includeDefault=False)
/frameworks/ml/nn/runtime/test/specs/V1_2/
Ddetection_postprocess.mod.py24 o3 = Output("classesOut", "TENSOR_INT32", "{1, 3}") # classes 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)
62 o3: [1, 0, 0],
75 o3 = Output("classesOut", "TENSOR_INT32", "{1, 3}") # classes 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)
113 o3: [1, 0, 0],
126 o3 = Output("classesOut", "TENSOR_INT32", "{1, 3}") # classes 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)
164 o3: [1, 0, 0],
177 o3 = Output("classesOut", "TENSOR_INT32", "{1, 3}") # classes out variable
[all …]
Dl2_pool_v1_2.mod.py45 o3 = Output("op4", "TENSOR_FLOAT32", "{1, 1, 1, 3}") variable
46 Model("large").Operation("L2_POOL_2D", i3, 0, 0, 0, 0, 1, 1, 2, 2, 0, layout).To(o3)
51 o3: [6.442049503326416, 7.3143692016601562, 8.2158384323120117]
52 }).AddNchw(i3, o3, layout).AddVariations("relaxed", "float16")
72 o3 = Output("out", "TENSOR_FLOAT32", "{0, 1, 1, 1}") # out variable
73 model = model.Operation("L2_POOL_2D", zero_sized, 0, 0, 0, 0, 1, 1, 2, 2, 0, layout).To(o3)
79 o3: [],
80 }).AddNchw(i1, zero_sized, o3, layout).AddVariations("relaxed", "float16")
100 o3 = Output("out", "TENSOR_FLOAT32", "{0, 2, 2, 1}") # out variable
101 model = model.Operation("L2_POOL_2D", zero_sized, 1, 1, 1, 2, 2, 0, layout).To(o3)
[all …]
Dresize_bilinear_v1_2.mod.py69 o3 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}") variable
70 model_shape = Model("shape").Operation("RESIZE_BILINEAR", i3, 3, 3).To(o3)
71 model_scale = Model("scale").Operation("RESIZE_BILINEAR", i3, 1.8, 1.8).To(o3)
76 o3: ("TENSOR_QUANT8_ASYMM", 0.01, 0)
81 o3: [1.0, 1.0, 1.0,
108 o3 = Output("out", "TENSOR_FLOAT32", "{0, 3, 3, 1}") # out variable
109 model = model.Operation("RESIZE_BILINEAR", zero_sized, 3, 3, layout).To(o3)
118 o3: ("TENSOR_QUANT8_ASYMM", 0.1, 128)
125 o3: [],
126 }).AddNchw(i1, zero_sized, o3, layout).AddVariations("relaxed", quant8, "float16")
[all …]
Dmax_pool_v1_2.mod.py77 o3 = Output("op4", ("TENSOR_FLOAT32", [bat, output_row, output_col, chn])) variable
78 Model().Operation("MAX_POOL_2D", i3, pad, pad, pad, pad, std, std, flt, flt, 3, layout).To(o3)
83 o3: ("TENSOR_QUANT8_ASYMM", 0.25, 0)
89 o3: [6 for _ in range(bat * output_row * output_col * chn)]
90 }).AddNchw(i3, o3, layout).AddVariations("relaxed", quant8, "float16")
128 o3 = Output("out", "TENSOR_FLOAT32", "{0, 1, 1, 1}") # out variable
129 model = model.Operation("MAX_POOL_2D", zero_sized, 0, 0, 0, 0, 1, 1, 2, 2, 0, layout).To(o3)
138 o3: ("TENSOR_QUANT8_ASYMM", 0.1, 128)
145 o3: [],
146 }).AddNchw(i1, zero_sized, o3, layout).AddVariations("relaxed", quant8, "float16")
[all …]
Davg_pool_v1_2.mod.py79 o3 = Output("op4", ("TENSOR_FLOAT32", [bat, output_row, output_col, chn])) variable
80 Model().Operation("AVERAGE_POOL_2D", i3, pad, pad, pad, pad, std, std, flt, flt, 0, layout).To(o3)
85 o3: ("TENSOR_QUANT8_ASYMM", 0.25, 0)
91 o3: [.5 for _ in range(bat * output_row * output_col * chn)]
92 }).AddNchw(i3, o3, layout).AddVariations("relaxed", "float16", quant8)
158 o3 = Output("out", "TENSOR_FLOAT32", "{0, 1, 1, 1}") # out variable
159 model = model.Operation("AVERAGE_POOL_2D", zero_sized, 0, 0, 0, 0, 1, 1, 2, 2, 0, layout).To(o3)
168 o3: ("TENSOR_QUANT8_ASYMM", 0.1, 128)
175 o3: [],
176 }).AddNchw(i1, zero_sized, o3, layout).AddVariations("relaxed", quant8, "float16")
[all …]
Dtranspose_conv2d.mod.py105 o3 = Output("op4", "TENSOR_FLOAT32", "{1, 4, 4, 1}") # output variable
106 Model().Operation("TRANSPOSE_CONV_2D", i3, w3, b3, s3, 1, 1, 1, 0, layout).To(o3)
113 o3: ("TENSOR_QUANT8_ASYMM", 16.0, 0)
119 o3: [184, 412, 568, 528,
123 }).AddNchw(i3, o3, s3, layout).AddVariations("relaxed", quant8, "float16")
198 o3 = Output("out", "TENSOR_FLOAT32", "{0, 5, 5, 2}") # out variable
199 model = model.Operation("TRANSPOSE_CONV_2D", zero_sized, w, b, s, 2, 2, 2, 0, layout).To(o3)
210 o3: ("TENSOR_QUANT8_ASYMM", 0.1, 128)
217 o3: [],
218 }).AddNchw(i1, zero_sized, o3, s, layout).AddVariations("relaxed", quant8, "float16")
[all …]
Dconcat_zero_sized.mod.py35 o3 = Output("out", "TENSOR_FLOAT32", "{0, 2, 2, 2}") # out variable
36 model = model.Operation("CONCATENATION", zero_sized, zero_sized, 3).To(o3)
45 o3: ("TENSOR_QUANT8_ASYMM", 0.1, 128)
52 o3: [],
75 o3 = Output("out", "TENSOR_FLOAT32", "{1, 2, 2, 1}") # out variable
76 model = model.Operation("CONCATENATION", zero_sized, i2, 0).To(o3)
86 o3: ("TENSOR_QUANT8_ASYMM", 0.1, 128)
94 o3: [1, 2, 3, 4],
Dconv2d_v1_2.mod.py79 o3 = Output("op4", "TENSOR_FLOAT32", "{1, 1, 1, 3}") variable
80 Model("channel").Operation("CONV_2D", i3, f3, b3, 0, 0, 0, 0, 1, 1, 0, layout).To(o3)
87 o3: ("TENSOR_QUANT8_ASYMM", 0.5, 0)
93 o3: ("TENSOR_QUANT8_ASYMM", 0.5, 0)
99 o3: [15., 37.5, 60.]
100 }).AddNchw(i3, o3, layout).AddVariations("relaxed", quant8, channelQuant8, "float16")
233 o3 = Output("out", "TENSOR_FLOAT32", "{0, 2, 2, 2}") # out variable
234 model = model.Operation("CONV_2D", zero_sized, w, b, 0, 0, 0, 0, 1, 1, 0, layout).To(o3)
245 o3: ("TENSOR_QUANT8_ASYMM", 0.1, 128)
252 o3: [],
[all …]
Dbox_with_nms_limit_gaussian.mod.py24 o3 = Output("classesOut", "TENSOR_INT32", "{18}") # classes out variable
26 …= Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 2, 0.4, 0.5, 0.3).To(o1, o2, o3, o4)
106 o3: [1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2],
120 o3 = Output("classesOut", "TENSOR_INT32", "{10}") # classes 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…
194 o3: [1, 1, 1, 2, 2, 1, 1, 1, 2, 2],
Dbox_with_nms_limit_linear.mod.py24 o3 = Output("classesOut", "TENSOR_INT32", "{16}") # classes out variable
26 …= Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 1, 0.4, 1.0, 0.3).To(o1, o2, o3, o4)
104 o3: [1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2],
118 o3 = Output("classesOut", "TENSOR_INT32", "{15}") # classes 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…
197 o3: [1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2],
Dbox_with_nms_limit_hard.mod.py24 o3 = Output("classesOut", "TENSOR_INT32", "{12}") # classes out variable
26 …= Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, o2, o3, o4)
97 o3: [1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 2],
111 o3 = Output("classesOut", "TENSOR_INT32", "{10}") # classes 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…
182 o3: [1, 1, 1, 2, 2, 1, 1, 1, 2, 2],
Dgenerate_proposals.mod.py27 o3 = Output("batchSplit", "TENSOR_INT32", "{4}") # batch split out variable
29 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3)
63 o3: [0, 0, 0, 0]
76 o3 = Output("batchSplit", "TENSOR_INT32", "{30}") # batch split out variable
78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3)
205 o3: [
Dspace_to_depth_v1_2.mod.py57 o3 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 8}") variable
58 Model().Operation("SPACE_TO_DEPTH", i3, 2, layout).To(o3)
63 o3: ("TENSOR_QUANT8_ASYMM", 1.0, 0)
72 o3: [10, 20, 11, 21, 14, 24, 15, 25,
76 }).AddNchw(i3, o3, layout).AddVariations("relaxed", "float16", quant8)
Ddepth_to_space_v1_2.mod.py57 o3 = Output("op4", "TENSOR_FLOAT32", "{1, 4, 4, 2}") variable
58 Model().Operation("DEPTH_TO_SPACE", i3, 2, layout).To(o3)
63 o3: ("TENSOR_QUANT8_ASYMM", 1.0, 0)
72 o3: [10, 20, 11, 21, 12, 22, 13, 23,
76 }).AddNchw(i3, o3, layout).AddVariations("relaxed", "float16", quant8)
Droi_pooling.mod.py118 o3 = Output("out", "TENSOR_FLOAT32", "{5, 2, 2, 1}") variable
119 Model().Operation("ROI_POOLING", i3, roi3, [2, 2, 2, 2, 2], 2, 2, 2.0, 1.0, layout).To(o3)
124 o3: ("TENSOR_QUANT8_ASYMM", 0.25, 128)
145 o3: [
152 }).AddNchw(i3, o3, layout).AddVariations("relaxed", quant8, "float16")
Dgrouped_conv2d.mod.py108 o3 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 6}") # output 0 variable
109 Model("channel").Operation("GROUPED_CONV_2D", i3, w3, b3, 1, 1, 1, 3, 0, layout).To(o3)
116 o3: ("TENSOR_QUANT8_ASYMM", 2.0, 60)
123 o3: ("TENSOR_QUANT8_ASYMM", 2.0, 60)
131 o3: [24, -16, 215, 338, 98, -51,
135 }).AddNchw(i3, o3, layout).AddVariations("relaxed", quant8, channelQuant8, "float16")

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