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/frameworks/ml/nn/runtime/test/specs/V1_3/
Dbox_with_nms_limit_quant8_signed.mod.py25 o4 = Output("batchSplitOut", "TENSOR_INT32", "{18}") # batch split 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)
107 o4: [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
122 o4 = Output("batchSplitOut", "TENSOR_INT32", "{10}") # batch split out variable
123 … = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, 5, 2, 0.4, 0.5, 0.3).To(o1, o2, o3, o4)
196 o4: [1, 1, 1, 1, 1, 3, 3, 3, 3, 3],
211 o4 = Output("batchSplitOut", "TENSOR_INT32", "{12}") # batch split 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)
284 o4: [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1],
299 o4 = Output("batchSplitOut", "TENSOR_INT32", "{10}") # batch split out variable
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Droi_align_quant8_signed.mod.py177 o4 = Output("out", "TENSOR_FLOAT32", "{5, 2, 2, 1}") variable
178 Model().Operation("ROI_ALIGN", i4, roi4, [2, 2, 2, 2, 2], 2, 2, 2.0, 1.0, 0, 4, layout).To(o4)
183 o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.0625, 0)
204 o4: [
211 }).AddNchw(i4, o4, layout).AddVariations(quant8_signed, includeDefault=False)
250 o4 = Output("out", "TENSOR_FLOAT32", "{1, 128, 4, 1}") variable
251 Model().Operation("ROI_ALIGN", i4, roi4, [0], 128, 4, 1.0, 64.0, 10, 10, layout).To(o4)
256 o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.0625, 0)
263 o4: [0] * (128 * 4)
264 }).AddNchw(i4, o4, layout).AddVariations(quant8_signed, includeDefault=False)
Dspace_to_batch_quant8_signed.mod.py197 o4 = Output("op4", "TENSOR_FLOAT32", "{6, 2, 4, 1}") variable
198 Model().Operation("SPACE_TO_BATCH_ND", i4, [3, 2], pad4, layout).To(o4)
203 o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, 0)
209 o4: [0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0,
212 }).AddNchw(i4, o4, layout).AddVariations(quant8_signed, includeDefault=False)
Dtranspose_conv2d_quant8_signed.mod.py166 o4 = Output("op4", "TENSOR_FLOAT32", "{1, 6, 6, 1}") # output variable
167 Model().Operation("TRANSPOSE_CONV_2D", i4, w4, b4, s4, 2, 1, 1, 0, layout).To(o4)
174 o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 32.0, -48)
180 o4: [5, 22, 59, 101, 114, 83,
186 }).AddNchw(i4, o4, s4, layout).AddVariations(quant8_signed, includeDefault=False)
Ddepthwise_conv2d_quant8_signed.mod.py475 o4 = Output("op4", "TENSOR_FLOAT32", "{1, 1, 1, 4}") variable
476 Model("large").Operation("DEPTHWISE_CONV_2D", i4, f4, b4, 0, 0, 0, 0, 1, 1, 1, 0, layout).To(o4)
483 o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 50.0, -128)
489 o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 50.0, -128)
498 o4: [6010, 7046, 11000, 9000]
499 }).AddNchw(i4, o4, layout).AddVariations(quant8_signed, includeDefault=False)
Dtranspose_quant8_signed.mod.py167 o4 = Output("op4", "TENSOR_FLOAT32", "{1, 6, 6, 1}") # output variable
168 Model().Operation("TRANSPOSE_CONV_2D", i4, w4, b4, s4, 2, 1, 1, 0, layout).To(o4)
175 o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 32.0, -48)
181 o4: [5, 22, 59, 101, 114, 83,
187 }).AddNchw(i4, o4, s4, layout).AddVariations(quant8_signed, includeDefault=False)
Dmax_pool_quant8_signed.mod.py211 o4 = Output("op4", "TENSOR_FLOAT32", "{1, 1, 2, 1}") variable
212 Model().Operation("MAX_POOL_2D", i4, 1, 2, 2, 2, 2, 0, layout).To(o4)
217 o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -128)
223 o4: [6, 10]
224 }).AddNchw(i4, o4, layout).AddVariations(quant8_signed, includeDefault=False)
Dconv2d_quant8_signed.mod.py297 o4 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 3, 3}") variable
298 Model("large").Operation("CONV_2D", i4, f4, b4, 0, 0, 0, 0, 1, 1, 0, layout).To(o4)
305 o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 2.0, -128)
311 o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 2.0, -128)
317 o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 1.0, -1)
324 o4: [30., 36., 42.,
330 }).AddNchw(i4, o4, layout).AddVariations(quant8_signed, channelquant8_signed, channelQuant8_mult_gt…
Davg_pool_quant8_signed.mod.py239 o4 = Output("op4", ("TENSOR_FLOAT32", [bat, output_row, output_col, chn])) variable
240 Model().Operation("AVERAGE_POOL_2D", i4, pad, pad, pad, pad, std, std, flt, flt, 3, layout).To(o4)
245 o4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, -128)
251 o4: [6 for _ in range(bat * output_row * output_col * chn)]
252 }).AddNchw(i4, o4, layout).AddVariations(quant8_signed, includeDefault=False)
/frameworks/ml/nn/runtime/test/specs/V1_2/
Ddetection_postprocess.mod.py25 o4 = Output("detectionOut", "TENSOR_INT32", "{1}") # num detections 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)
63 o4: [2],
76 o4 = Output("detectionOut", "TENSOR_INT32", "{1}") # num detections 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)
114 o4: [3],
127 o4 = Output("detectionOut", "TENSOR_INT32", "{1}") # num detections 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)
165 o4: [3],
178 o4 = Output("detectionOut", "TENSOR_INT32", "{1}") # num detections out variable
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Droi_align.mod.py177 o4 = Output("out", "TENSOR_FLOAT32", "{5, 2, 2, 1}") variable
178 Model().Operation("ROI_ALIGN", i4, roi4, [2, 2, 2, 2, 2], 2, 2, 2.0, 1.0, 0, 4, layout).To(o4)
183 o4: ("TENSOR_QUANT8_ASYMM", 0.0625, 128)
204 o4: [
211 }).AddNchw(i4, o4, layout).AddVariations("relaxed", quant8, "float16")
250 o4 = Output("out", "TENSOR_FLOAT32", "{1, 128, 4, 1}") variable
251 Model().Operation("ROI_ALIGN", i4, roi4, [0], 128, 4, 1.0, 64.0, 10, 10, layout).To(o4)
256 o4: ("TENSOR_QUANT8_ASYMM", 0.0625, 128)
263 o4: [0] * (128 * 4)
264 }).AddNchw(i4, o4, layout).AddVariations("relaxed", quant8, "float16")
Dbox_with_nms_limit_gaussian.mod.py25 o4 = Output("batchSplitOut", "TENSOR_INT32", "{18}") # batch split 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)
107 o4: [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
121 o4 = Output("batchSplitOut", "TENSOR_INT32", "{10}") # batch split out variable
122 … = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, 5, 2, 0.4, 0.5, 0.3).To(o1, o2, o3, o4)
195 o4: [1, 1, 1, 1, 1, 3, 3, 3, 3, 3],
Dbox_with_nms_limit_linear.mod.py25 o4 = Output("batchSplitOut", "TENSOR_INT32", "{16}") # batch split 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)
105 o4: [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1],
119 o4 = Output("batchSplitOut", "TENSOR_INT32", "{15}") # batch split out variable
120 … = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, 8, 1, 0.4, 0.5, 0.3).To(o1, o2, o3, o4)
198 o4: [1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3],
Dbox_with_nms_limit_hard.mod.py25 o4 = Output("batchSplitOut", "TENSOR_INT32", "{12}") # batch split 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)
98 o4: [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1],
112 o4 = Output("batchSplitOut", "TENSOR_INT32", "{10}") # batch split out variable
113 … = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, 5, 0, 0.4, 0.5, 0.3).To(o1, o2, o3, o4)
183 o4: [1, 1, 1, 1, 1, 3, 3, 3, 3, 3],
Dspace_to_batch_v1_2.mod.py79 o4 = Output("op4", "TENSOR_FLOAT32", "{6, 2, 4, 1}") variable
80 Model().Operation("SPACE_TO_BATCH_ND", i4, [3, 2], pad4, layout).To(o4)
85 o4: ("TENSOR_QUANT8_ASYMM", 0.25, 128)
91 o4: [0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0,
94 }).AddNchw(i4, o4, layout).AddVariations("relaxed", "float16", quant8)
Ddepthwise_conv2d_v1_2.mod.py118 o4 = Output("op4", "TENSOR_FLOAT32", "{1, 1, 1, 4}") variable
119 Model("large").Operation("DEPTHWISE_CONV_2D", i4, f4, b4, 0, 0, 0, 0, 1, 1, 1, 0, layout).To(o4)
126 o4: ("TENSOR_QUANT8_ASYMM", 50.0, 0)
132 o4: ("TENSOR_QUANT8_ASYMM", 50.0, 0)
141 o4: [6010, 7046, 11000, 9000]
142 }).AddNchw(i4, o4, layout).AddVariations("relaxed", "float16", quant8, channelQuant8)
Dconv2d_v1_2.mod.py107 o4 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 3, 3}") variable
108 Model("large").Operation("CONV_2D", i4, f4, b4, 0, 0, 0, 0, 1, 1, 0, layout).To(o4)
115 o4: ("TENSOR_QUANT8_ASYMM", 2.0, 0)
121 o4: ("TENSOR_QUANT8_ASYMM", 2.0, 0)
127 o4: ("TENSOR_QUANT8_ASYMM", 1.0, 127)
134 o4: [30., 36., 42.,
140 }).AddNchw(i4, o4, layout).AddVariations("relaxed", quant8, channelQuant8, channelQuant8_mult_gt_1,…
Dmax_pool_v1_2.mod.py95 o4 = Output("op4", "TENSOR_FLOAT32", "{1, 1, 2, 1}") variable
96 Model().Operation("MAX_POOL_2D", i4, 1, 2, 2, 2, 2, 0, layout).To(o4)
101 o4: ("TENSOR_QUANT8_ASYMM", 0.25, 0)
107 o4: [6, 10]
108 }).AddNchw(i4, o4, layout).AddVariations("relaxed", quant8, "float16")
Davg_pool_v1_2.mod.py107 o4 = Output("op4", ("TENSOR_FLOAT32", [bat, output_row, output_col, chn])) variable
108 Model().Operation("AVERAGE_POOL_2D", i4, pad, pad, pad, pad, std, std, flt, flt, 3, layout).To(o4)
113 o4: ("TENSOR_QUANT8_ASYMM", 0.5, 0)
119 o4: [6 for _ in range(bat * output_row * output_col * chn)]
120 }).AddNchw(i4, o4, layout).AddVariations("relaxed", "float16", quant8)
Dtranspose_conv2d.mod.py131 o4 = Output("op4", "TENSOR_FLOAT32", "{1, 6, 6, 1}") # output variable
132 Model().Operation("TRANSPOSE_CONV_2D", i4, w4, b4, s4, 2, 1, 1, 0, layout).To(o4)
139 o4: ("TENSOR_QUANT8_ASYMM", 32.0, 80)
145 o4: [5, 22, 59, 101, 114, 83,
151 }).AddNchw(i4, o4, s4, layout).AddVariations("relaxed", quant8, "float16")
/frameworks/compile/slang/tests/F_one_definition_rule4/
Ddef1.rscript10 DifferentDefinition4 o4;
Ddef2.rscript10 DifferentDefinition4 o4;
/frameworks/rs/cpu_ref/
DrsCpuIntrinsics_x86.cpp152 __m128i i4, o4; in rsdIntrinsicColorMatrix4x4_K() local
187 o4 = _mm_packus_epi16(x2, z2); in rsdIntrinsicColorMatrix4x4_K()
189 o4 = _mm_shuffle_epi8(o4, T4x4); in rsdIntrinsicColorMatrix4x4_K()
190 _mm_storeu_si128((__m128i *)dst, o4); in rsdIntrinsicColorMatrix4x4_K()
208 __m128i i4, o4; in rsdIntrinsicColorMatrix3x3_K() local
241 o4 = _mm_packus_epi16(x2, z2); in rsdIntrinsicColorMatrix3x3_K()
243 o4 = _mm_shuffle_epi8(o4, T4x4); in rsdIntrinsicColorMatrix3x3_K()
244 _mm_storeu_si128((__m128i *)dst, o4); in rsdIntrinsicColorMatrix3x3_K()
260 __m128i i4, o4; in rsdIntrinsicColorMatrixDot_K() local
293 o4 = _mm_packus_epi16(x2, z2); in rsdIntrinsicColorMatrixDot_K()
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