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author | Chunseok Lee <chunseok.lee@samsung.com> | 2020-10-29 13:12:50 +0900 |
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committer | Chunseok Lee <chunseok.lee@samsung.com> | 2020-10-29 13:12:50 +0900 |
commit | d6b371e095d737922187a518b8faba1ef6f3a2b1 (patch) | |
tree | 9d90c09c887b5111389dbedf924f59206411cd5a /tests/nnapi/specs/skip/V1_2/box_with_nms_limit_linear.mod.py | |
parent | c55f8a6db48cda9d3a78048338b7f18c4cca62b8 (diff) | |
download | nnfw-d6b371e095d737922187a518b8faba1ef6f3a2b1.tar.gz nnfw-d6b371e095d737922187a518b8faba1ef6f3a2b1.tar.bz2 nnfw-d6b371e095d737922187a518b8faba1ef6f3a2b1.zip |
Imported Upstream version 0.4upstream/0.4
Diffstat (limited to 'tests/nnapi/specs/skip/V1_2/box_with_nms_limit_linear.mod.py')
-rw-r--r-- | tests/nnapi/specs/skip/V1_2/box_with_nms_limit_linear.mod.py | 201 |
1 files changed, 0 insertions, 201 deletions
diff --git a/tests/nnapi/specs/skip/V1_2/box_with_nms_limit_linear.mod.py b/tests/nnapi/specs/skip/V1_2/box_with_nms_limit_linear.mod.py deleted file mode 100644 index 4d3bc2001..000000000 --- a/tests/nnapi/specs/skip/V1_2/box_with_nms_limit_linear.mod.py +++ /dev/null @@ -1,201 +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: BOX_WITH_NMS_LIMIT, score_threshold = 0.3, nms_threshold = 0.4, max_detections = -1 -i1 = Input("scores", "TENSOR_FLOAT32", "{19, 3}") # scores -i2 = Input("roi", "TENSOR_FLOAT32", "{19, 12}") # roi -i3 = Input("batchSplit", "TENSOR_INT32", "{19}") # batchSplit - -o1 = Output("scoresOut", "TENSOR_FLOAT32", "{16}") # scores out -o2 = Output("roiOut", "TENSOR_FLOAT32", "{16, 4}") # roi out -o3 = Output("classesOut", "TENSOR_INT32", "{16}") # classes out -o4 = Output("batchSplitOut", "TENSOR_INT32", "{16}") # batch split out -model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, -1, 1, 0.4, 1.0, 0.3).To(o1, o2, o3, o4) - -quant8 = DataTypeConverter().Identify({ - i1: ("TENSOR_QUANT8_ASYMM", 0.01, 0), - i2: ("TENSOR_QUANT16_ASYMM", 0.125, 0), - o1: ("TENSOR_QUANT8_ASYMM", 0.01, 0), - o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0) -}) - -input0 = { - i1: [ # scores - 0.90, 0.95, 0.75, - 0.80, 0.70, 0.85, - 0.60, 0.90, 0.95, - 0.90, 0.65, 0.90, - 0.80, 0.85, 0.80, - 0.60, 0.60, 0.20, - 0.60, 0.80, 0.40, - 0.90, 0.55, 0.60, - 0.90, 0.75, 0.70, - 0.80, 0.70, 0.85, - 0.90, 0.95, 0.75, - 0.80, 0.85, 0.80, - 0.60, 0.90, 0.95, - 0.60, 0.60, 0.20, - 0.50, 0.90, 0.80, - 0.90, 0.75, 0.70, - 0.90, 0.65, 0.90, - 0.90, 0.55, 0.60, - 0.60, 0.80, 0.40 - ], - i2: [ # roi - 1, 1, 10, 10, 0, 0, 10, 10, 0, 0, 10, 10, - 2, 2, 11, 11, 1, 1, 11, 11, 1, 1, 11, 11, - 3, 3, 12, 12, 2, 2, 12, 12, 2, 2, 12, 12, - 4, 4, 13, 13, 3, 3, 13, 13, 3, 3, 13, 13, - 5, 5, 14, 14, 4, 4, 14, 14, 4, 4, 14, 14, - 6, 6, 15, 15, 5, 5, 15, 15, 5, 5, 15, 15, - 7, 7, 16, 16, 6, 6, 16, 16, 6, 6, 16, 16, - 8, 8, 17, 17, 7, 7, 17, 17, 7, 7, 17, 17, - 9, 9, 18, 18, 8, 8, 18, 18, 8, 8, 18, 18, - 2, 2, 11, 11, 2, 2, 12, 12, 2, 2, 12, 12, - 1, 1, 10, 10, 1, 1, 11, 11, 1, 1, 11, 11, - 5, 5, 14, 14, 5, 5, 15, 15, 5, 5, 15, 15, - 3, 3, 12, 12, 3, 3, 13, 13, 3, 3, 13, 13, - 6, 6, 15, 15, 6, 6, 16, 16, 6, 6, 16, 16, - 0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 2, 2, - 9, 9, 18, 18, 9, 9, 19, 19, 9, 9, 19, 19, - 4, 4, 13, 13, 4, 4, 14, 14, 4, 4, 14, 14, - 8, 8, 17, 17, 8, 8, 18, 18, 8, 8, 18, 18, - 7, 7, 16, 16, 7, 7, 17, 17, 7, 7, 17, 17 - ], - i3: [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] # batch split -} - -output0 = { - o1: [ - 0.95, 0.85, 0.75, 0.95, 0.7, 0.42352945, 0.39705884, - 0.95, 0.9, 0.85, 0.75, 0.95, 0.8, 0.7, 0.42352945, 0.39705884 - ], - o2: [ - 0, 0, 10, 10, - 4, 4, 14, 14, - 8, 8, 18, 18, - 2, 2, 12, 12, - 8, 8, 18, 18, - 4, 4, 14, 14, - 0, 0, 10, 10, - 1, 1, 11, 11, - 0, 0, 2, 2, - 5, 5, 15, 15, - 9, 9, 19, 19, - 3, 3, 13, 13, - 0, 0, 2, 2, - 9, 9, 19, 19, - 5, 5, 15, 15, - 1, 1, 11, 11 - ], - o3: [1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2], - o4: [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1], -} - -Example((input0, output0)).AddVariations("relaxed", "float16", quant8) - - -# TEST 2: BOX_WITH_NMS_LIMIT, score_threshold = 0.3, nms_threshold = 0.4, max_detections = 5 -i1 = Input("scores", "TENSOR_FLOAT32", "{19, 3}") # scores -i2 = Input("roi", "TENSOR_FLOAT32", "{19, 12}") # roi -i3 = Input("batchSplit", "TENSOR_INT32", "{19}") # batchSplit - -o1 = Output("scoresOut", "TENSOR_FLOAT32", "{15}") # scores out -o2 = Output("roiOut", "TENSOR_FLOAT32", "{15, 4}") # roi out -o3 = Output("classesOut", "TENSOR_INT32", "{15}") # classes out -o4 = Output("batchSplitOut", "TENSOR_INT32", "{15}") # batch split out -model = Model().Operation("BOX_WITH_NMS_LIMIT", i1, i2, i3, 0.3, 8, 1, 0.4, 0.5, 0.3).To(o1, o2, o3, o4) - -quant8 = DataTypeConverter().Identify({ - i1: ("TENSOR_QUANT8_ASYMM", 0.01, 128), - i2: ("TENSOR_QUANT16_ASYMM", 0.125, 0), - o1: ("TENSOR_QUANT8_ASYMM", 0.01, 128), - o2: ("TENSOR_QUANT16_ASYMM", 0.125, 0) -}) - -input0 = { - i1: [ # scores - 0.90, 0.95, 0.75, - 0.80, 0.70, 0.85, - 0.60, 0.90, 0.95, - 0.90, 0.65, 0.90, - 0.80, 0.85, 0.80, - 0.60, 0.60, 0.20, - 0.60, 0.80, 0.40, - 0.90, 0.55, 0.60, - 0.90, 0.75, 0.70, - 0.80, 0.70, 0.85, - 0.90, 0.95, 0.75, - 0.80, 0.85, 0.80, - 0.60, 0.90, 0.95, - 0.60, 0.60, 0.20, - 0.50, 0.90, 0.80, - 0.90, 0.75, 0.70, - 0.90, 0.65, 0.90, - 0.90, 0.55, 0.60, - 0.60, 0.80, 0.40 - ], - i2: [ # roi - 1, 1, 10, 10, 0, 0, 10, 10, 0, 0, 10, 10, - 2, 2, 11, 11, 1, 1, 11, 11, 1, 1, 11, 11, - 3, 3, 12, 12, 2, 2, 12, 12, 2, 2, 12, 12, - 4, 4, 13, 13, 3, 3, 13, 13, 3, 3, 13, 13, - 5, 5, 14, 14, 4, 4, 14, 14, 4, 4, 14, 14, - 6, 6, 15, 15, 5, 5, 15, 15, 5, 5, 15, 15, - 7, 7, 16, 16, 6, 6, 16, 16, 6, 6, 16, 16, - 8, 8, 17, 17, 7, 7, 17, 17, 7, 7, 17, 17, - 9, 9, 18, 18, 8, 8, 18, 18, 8, 8, 18, 18, - 2, 2, 11, 11, 2, 2, 12, 12, 2, 2, 12, 12, - 1, 1, 10, 10, 1, 1, 11, 11, 1, 1, 11, 11, - 5, 5, 14, 14, 5, 5, 15, 15, 5, 5, 15, 15, - 3, 3, 12, 12, 3, 3, 13, 13, 3, 3, 13, 13, - 6, 6, 15, 15, 6, 6, 16, 16, 6, 6, 16, 16, - 0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 2, 2, - 9, 9, 18, 18, 9, 9, 19, 19, 9, 9, 19, 19, - 4, 4, 13, 13, 4, 4, 14, 14, 4, 4, 14, 14, - 8, 8, 17, 17, 8, 8, 18, 18, 8, 8, 18, 18, - 7, 7, 16, 16, 7, 7, 17, 17, 7, 7, 17, 17 - ], - i3: [1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3] # batch split -} - -output0 = { - o1: [ - 0.95, 0.85, 0.75, 0.95, 0.7, 0.42352945, 0.39705884, - 0.95, 0.9, 0.85, 0.75, 0.95, 0.8, 0.7, 0.42352945 - ], - o2: [ - 0, 0, 10, 10, - 4, 4, 14, 14, - 8, 8, 18, 18, - 2, 2, 12, 12, - 8, 8, 18, 18, - 4, 4, 14, 14, - 0, 0, 10, 10, - 1, 1, 11, 11, - 0, 0, 2, 2, - 5, 5, 15, 15, - 9, 9, 19, 19, - 3, 3, 13, 13, - 0, 0, 2, 2, - 9, 9, 19, 19, - 5, 5, 15, 15 - ], - o3: [1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2], - o4: [1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3], -} - -Example((input0, output0)).AddVariations("relaxed", "float16", quant8) |