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-rw-r--r--tests/nnapi/specs/skip/V1_2/detection_postprocess.mod.py219
1 files changed, 0 insertions, 219 deletions
diff --git a/tests/nnapi/specs/skip/V1_2/detection_postprocess.mod.py b/tests/nnapi/specs/skip/V1_2/detection_postprocess.mod.py
deleted file mode 100644
index b37989134..000000000
--- a/tests/nnapi/specs/skip/V1_2/detection_postprocess.mod.py
+++ /dev/null
@@ -1,219 +0,0 @@
-#
-# Copyright (C) 2019 The Android Open Source Project
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-#
-
-# TEST 1: DETECTION_POSTPROCESSING
-i1 = Input("scores", "TENSOR_FLOAT32", "{1, 6, 3}") # scores
-i2 = Input("roi", "TENSOR_FLOAT32", "{1, 6, 4}") # roi
-i3 = Input("anchors", "TENSOR_FLOAT32", "{6, 4}") # anchors
-
-o1 = Output("scoresOut", "TENSOR_FLOAT32", "{1, 3}") # scores out
-o2 = Output("roiOut", "TENSOR_FLOAT32", "{1, 3, 4}") # roi out
-o3 = Output("classesOut", "TENSOR_INT32", "{1, 3}") # classes out
-o4 = Output("detectionOut", "TENSOR_INT32", "{1}") # num detections out
-Model("regular").Operation("DETECTION_POSTPROCESSING", 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)
-
-input0 = {
- i1: [ # class scores - two classes with background
- 0., .9, .8,
- 0., .75, .72,
- 0., .6, .5,
- 0., .93, .95,
- 0., .5, .4,
- 0., .3, .2
- ],
- i2: [ # six boxes in center-size encoding
- 0.0, 0.0, 0.0, 0.0, # box #1
- 0.0, 1.0, 0.0, 0.0, # box #2
- 0.0, -1.0, 0.0, 0.0, # box #3
- 0.0, 0.0, 0.0, 0.0, # box #4
- 0.0, 1.0, 0.0, 0.0, # box #5
- 0.0, 0.0, 0.0, 0.0 # box #6
- ],
- i3: [ # six anchors in center-size encoding
- 0.5, 0.5, 1.0, 1.0, # anchor #1
- 0.5, 0.5, 1.0, 1.0, # anchor #2
- 0.5, 0.5, 1.0, 1.0, # anchor #3
- 0.5, 10.5, 1.0, 1.0, # anchor #4
- 0.5, 10.5, 1.0, 1.0, # anchor #5
- 0.5, 100.5, 1.0, 1.0 # anchor #6
- ]
-}
-
-output0 = {
- o1: [0.95, 0.93, 0.0],
- o2: [
- 0.0, 10.0, 1.0, 11.0,
- 0.0, 10.0, 1.0, 11.0,
- 0.0, 0.0, 0.0, 0.0
- ],
- o3: [1, 0, 0],
- o4: [2],
-}
-
-Example((input0, output0)).AddVariations("relaxed", "float16")
-
-# TEST 2: DETECTION_POSTPROCESSING
-i1 = Input("scores", "TENSOR_FLOAT32", "{1, 6, 3}") # scores
-i2 = Input("roi", "TENSOR_FLOAT32", "{1, 6, 4}") # roi
-i3 = Input("anchors", "TENSOR_FLOAT32", "{6, 4}") # anchors
-
-o1 = Output("scoresOut", "TENSOR_FLOAT32", "{1, 3}") # scores out
-o2 = Output("roiOut", "TENSOR_FLOAT32", "{1, 3, 4}") # roi out
-o3 = Output("classesOut", "TENSOR_INT32", "{1, 3}") # classes out
-o4 = Output("detectionOut", "TENSOR_INT32", "{1}") # num detections out
-Model().Operation("DETECTION_POSTPROCESSING", 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)
-
-input0 = {
- i1: [ # class scores - two classes with background
- 0., .9, .8,
- 0., .75, .72,
- 0., .6, .5,
- 0., .93, .95,
- 0., .5, .4,
- 0., .3, .2
- ],
- i2: [ # six boxes in center-size encoding
- 0.0, 0.0, 0.0, 0.0, # box #1
- 0.0, 1.0, 0.0, 0.0, # box #2
- 0.0, -1.0, 0.0, 0.0, # box #3
- 0.0, 0.0, 0.0, 0.0, # box #4
- 0.0, 1.0, 0.0, 0.0, # box #5
- 0.0, 0.0, 0.0, 0.0 # box #6
- ],
- i3: [ # six anchors in center-size encoding
- 0.5, 0.5, 1.0, 1.0, # anchor #1
- 0.5, 0.5, 1.0, 1.0, # anchor #2
- 0.5, 0.5, 1.0, 1.0, # anchor #3
- 0.5, 10.5, 1.0, 1.0, # anchor #4
- 0.5, 10.5, 1.0, 1.0, # anchor #5
- 0.5, 100.5, 1.0, 1.0 # anchor #6
- ]
-}
-
-output0 = {
- o1: [0.95, 0.9, 0.3],
- o2: [
- 0.0, 10.0, 1.0, 11.0,
- 0.0, 0.0, 1.0, 1.0,
- 0.0, 100.0, 1.0, 101.0
- ],
- o3: [1, 0, 0],
- o4: [3],
-}
-
-Example((input0, output0)).AddVariations("relaxed", "float16")
-
-# TEST 3: DETECTION_POSTPROCESSING
-i1 = Input("scores", "TENSOR_FLOAT32", "{1, 6, 3}") # scores
-i2 = Input("roi", "TENSOR_FLOAT32", "{1, 6, 7}") # roi
-i3 = Input("anchors", "TENSOR_FLOAT32", "{6, 4}") # anchors
-
-o1 = Output("scoresOut", "TENSOR_FLOAT32", "{1, 3}") # scores out
-o2 = Output("roiOut", "TENSOR_FLOAT32", "{1, 3, 4}") # roi out
-o3 = Output("classesOut", "TENSOR_INT32", "{1, 3}") # classes out
-o4 = Output("detectionOut", "TENSOR_INT32", "{1}") # num detections out
-Model().Operation("DETECTION_POSTPROCESSING", 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)
-
-input0 = {
- i1: [ # class scores - two classes with background
- 0., .9, .8,
- 0., .75, .72,
- 0., .6, .5,
- 0., .93, .95,
- 0., .5, .4,
- 0., .3, .2
- ],
- i2: [ # six boxes in center-size encoding
- 0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, # box #1
- 0.0, 1.0, 0.0, 0.0, 1.0, 2.0, 3.0, # box #2
- 0.0, -1.0, 0.0, 0.0, 1.0, 2.0, 3.0, # box #3
- 0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, # box #4
- 0.0, 1.0, 0.0, 0.0, 1.0, 2.0, 3.0, # box #5
- 0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0 # box #6
- ],
- i3: [ # six anchors in center-size encoding
- 0.5, 0.5, 1.0, 1.0, # anchor #1
- 0.5, 0.5, 1.0, 1.0, # anchor #2
- 0.5, 0.5, 1.0, 1.0, # anchor #3
- 0.5, 10.5, 1.0, 1.0, # anchor #4
- 0.5, 10.5, 1.0, 1.0, # anchor #5
- 0.5, 100.5, 1.0, 1.0 # anchor #6
- ]
-}
-
-output0 = {
- o1: [0.95, 0.9, 0.3],
- o2: [
- 0.0, 10.0, 1.0, 11.0,
- 0.0, 0.0, 1.0, 1.0,
- 0.0, 100.0, 1.0, 101.0
- ],
- o3: [1, 0, 0],
- o4: [3],
-}
-
-Example((input0, output0)).AddVariations("relaxed", "float16")
-
-# TEST 4: DETECTION_POSTPROCESSING
-i1 = Input("scores", "TENSOR_FLOAT32", "{1, 6, 3}") # scores
-i2 = Input("roi", "TENSOR_FLOAT32", "{1, 6, 7}") # roi
-i3 = Input("anchors", "TENSOR_FLOAT32", "{6, 4}") # anchors
-
-o1 = Output("scoresOut", "TENSOR_FLOAT32", "{1, 3}") # scores out
-o2 = Output("roiOut", "TENSOR_FLOAT32", "{1, 3, 4}") # roi out
-o3 = Output("classesOut", "TENSOR_INT32", "{1, 3}") # classes out
-o4 = Output("detectionOut", "TENSOR_INT32", "{1}") # num detections out
-Model().Operation("DETECTION_POSTPROCESSING", i1, i2, i3, 10.0, 10.0, 5.0, 5.0, False, 3, 1, 1, 0.0, 0.5, True).To(o1, o2, o3, o4)
-
-input0 = {
- i1: [ # class scores - two classes with background
- 0., .9, .8,
- 0., .75, .72,
- 0., .6, .5,
- 0., .93, .95,
- 0., .5, .4,
- 0., .3, .2
- ],
- i2: [ # six boxes in center-size encoding
- 0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, # box #1
- 0.0, 1.0, 0.0, 0.0, 1.0, 2.0, 3.0, # box #2
- 0.0, -1.0, 0.0, 0.0, 1.0, 2.0, 3.0, # box #3
- 0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, # box #4
- 0.0, 1.0, 0.0, 0.0, 1.0, 2.0, 3.0, # box #5
- 0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0 # box #6
- ],
- i3: [ # six anchors in center-size encoding
- 0.5, 0.5, 1.0, 1.0, # anchor #1
- 0.5, 0.5, 1.0, 1.0, # anchor #2
- 0.5, 0.5, 1.0, 1.0, # anchor #3
- 0.5, 10.5, 1.0, 1.0, # anchor #4
- 0.5, 10.5, 1.0, 1.0, # anchor #5
- 0.5, 100.5, 1.0, 1.0 # anchor #6
- ]
-}
-
-output0 = {
- o1: [0.95, 0.9, 0.3],
- o2: [
- 0.0, 10.0, 1.0, 11.0,
- 0.0, 0.0, 1.0, 1.0,
- 0.0, 100.0, 1.0, 101.0
- ],
- o3: [2, 1, 1],
- o4: [3],
-}
-
-Example((input0, output0)).AddVariations("relaxed", "float16")
generated by cgit v1.2.3 (git 2.25.1) at 2024-07-04 18:11:32 +0000