diff options
Diffstat (limited to 'tests/nnapi/specs/skip/V1_2/minimum.mod.py')
-rw-r--r-- | tests/nnapi/specs/skip/V1_2/minimum.mod.py | 64 |
1 files changed, 64 insertions, 0 deletions
diff --git a/tests/nnapi/specs/skip/V1_2/minimum.mod.py b/tests/nnapi/specs/skip/V1_2/minimum.mod.py new file mode 100644 index 000000000..76b058612 --- /dev/null +++ b/tests/nnapi/specs/skip/V1_2/minimum.mod.py @@ -0,0 +1,64 @@ +# +# 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. +# + +def test(name, input0, input1, output0, input0_data, input1_data, output_data): + model = Model().Operation("MINIMUM", input0, input1).To(output0) + + quant8 = DataTypeConverter().Identify({ + input0: ["TENSOR_QUANT8_ASYMM", 0.5, 127], + input1: ["TENSOR_QUANT8_ASYMM", 1.0, 100], + output0: ["TENSOR_QUANT8_ASYMM", 2.0, 80], + }) + + Example({ + input0: input0_data, + input1: input1_data, + output0: output_data, + }, model=model, name=name).AddVariations("relaxed", "float16", "int32", quant8) + + +test( + name="simple", + input0=Input("input0", "TENSOR_FLOAT32", "{3, 1, 2}"), + input1=Input("input1", "TENSOR_FLOAT32", "{3, 1, 2}"), + output0=Output("output0", "TENSOR_FLOAT32", "{3, 1, 2}"), + input0_data=[1.0, 0.0, -1.0, 11.0, -2.0, -1.44], + input1_data=[-1.0, 0.0, 1.0, 12.0, -3.0, -1.43], + output_data=[-1.0, 0.0, -1.0, 11.0, -3.0, -1.44], +) + +test( + name="broadcast", + input0=Input("input0", "TENSOR_FLOAT32", "{3, 1, 2}"), + input1=Input("input1", "TENSOR_FLOAT32", "{2}"), + output0=Output("output0", "TENSOR_FLOAT32", "{3, 1, 2}"), + input0_data=[1.0, 0.0, -1.0, -2.0, -1.44, 11.0], + input1_data=[0.5, 2.0], + output_data=[0.5, 0.0, -1.0, -2.0, -1.44, 2.0], +) + + +# Test overflow and underflow. +input0 = Input("input0", "TENSOR_QUANT8_ASYMM", "{2}, 1.0f, 128") +input1 = Input("input1", "TENSOR_QUANT8_ASYMM", "{2}, 1.0f, 128") +output0 = Output("output0", "TENSOR_QUANT8_ASYMM", "{2}, 0.5f, 128") +model = Model().Operation("MINIMUM", input0, input1).To(output0) + +Example({ + input0: [60, 128], + input1: [128, 200], + output0: [0, 128], +}, model=model, name="overflow") |