diff options
Diffstat (limited to 'tests/nnapi/specs/V1_2/transpose_v1_2.mod.py')
-rwxr-xr-x | tests/nnapi/specs/V1_2/transpose_v1_2.mod.py | 81 |
1 files changed, 81 insertions, 0 deletions
diff --git a/tests/nnapi/specs/V1_2/transpose_v1_2.mod.py b/tests/nnapi/specs/V1_2/transpose_v1_2.mod.py new file mode 100755 index 000000000..9d0108e8f --- /dev/null +++ b/tests/nnapi/specs/V1_2/transpose_v1_2.mod.py @@ -0,0 +1,81 @@ +# +# Copyright (C) 2018 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. +# + +# model +model = Model() +i1 = Input("input", "TENSOR_FLOAT32", "{2, 2}") +perms = Input("perms", "TENSOR_INT32", "{0}") +output = Output("output", "TENSOR_FLOAT32", "{2, 2}") + +model = model.Operation("TRANSPOSE", i1, perms).To(output) + +# Additional data type +quant8 = DataTypeConverter().Identify({ + i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0), + output: ("TENSOR_QUANT8_ASYMM", 0.5, 0) +}) + +# Instantiate an example +Example({ + i1: [1.0, 2.0, + 3.0, 4.0], + perms: [], + output: [1.0, 3.0, + 2.0, 4.0] +}).AddVariations("relaxed", quant8) + +# TRANSPOSE of data type TENSOR_FLOAT32 and TENSOR_QUANT8_ASYMM is introduced in V1_1. +Example.SetVersion("V1_1", "transpose_v1_2", "transpose_v1_2_quant8") + + +# zero-sized input + +# Use BOX_WITH_NMS_LIMIT op to generate a zero-sized internal tensor for box cooridnates. +p1 = Parameter("scores", "TENSOR_FLOAT32", "{1, 2}", [0.90, 0.10]) # scores +p2 = Parameter("roi", "TENSOR_FLOAT32", "{1, 8}", [1, 1, 10, 10, 0, 0, 10, 10]) # roi +o1 = Output("scoresOut", "TENSOR_FLOAT32", "{0}") # scores out +o2 = Output("classesOut", "TENSOR_INT32", "{0}") # classes out +tmp1 = Internal("roiOut", "TENSOR_FLOAT32", "{0, 4}") # roi out +tmp2 = Internal("batchSplitOut", "TENSOR_INT32", "{0}") # batch split out +model = Model("zero_sized").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3, -1, 0, 0.4, 1.0, 0.3).To(o1, tmp1, o2, tmp2) + +# Use ROI_ALIGN op to convert into zero-sized feature map. +layout = BoolScalar("layout", False) # NHWC +i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}") +zero_sized = Internal("featureMap", "TENSOR_FLOAT32", "{0, 2, 2, 1}") +model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4, layout).To(zero_sized) + +# TRANSPOSE op with numBatches = 0. +o3 = Output("out", "TENSOR_FLOAT32", "{0, 1, 2, 2}") # out +model = model.Operation("TRANSPOSE", zero_sized, [0, 3, 1, 2]).To(o3) + +quant8 = DataTypeConverter().Identify({ + p1: ("TENSOR_QUANT8_ASYMM", 0.1, 128), + p2: ("TENSOR_QUANT16_ASYMM", 0.125, 0), + o1: ("TENSOR_QUANT8_ASYMM", 0.1, 128), + tmp1: ("TENSOR_QUANT16_ASYMM", 0.125, 0), + i1: ("TENSOR_QUANT8_ASYMM", 0.1, 128), + zero_sized: ("TENSOR_QUANT8_ASYMM", 0.1, 128), + o3: ("TENSOR_QUANT8_ASYMM", 0.1, 128) +}) + +# Create test case with dummy values. +Example({ + i1: [1], + o1: [0], + o2: [0], + o3: [0], +}).AddVariations("relaxed", quant8, "float16") |