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Diffstat (limited to 'tests/nnapi/specs/V1_2/gather.mod.py')
-rw-r--r-- | tests/nnapi/specs/V1_2/gather.mod.py | 121 |
1 files changed, 121 insertions, 0 deletions
diff --git a/tests/nnapi/specs/V1_2/gather.mod.py b/tests/nnapi/specs/V1_2/gather.mod.py new file mode 100644 index 000000000..d5e1ef73d --- /dev/null +++ b/tests/nnapi/specs/V1_2/gather.mod.py @@ -0,0 +1,121 @@ +# +# 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(input0, axis, indices, output0, input_data, output_data): + model = Model().Operation("GATHER", input0, axis, indices).To(output0) + + quant8 = DataTypeConverter().Identify({ + input0: ["TENSOR_QUANT8_ASYMM", 0.5, 127], + output0: ["TENSOR_QUANT8_ASYMM", 0.5, 127], + }) + + int32 = DataTypeConverter().Identify({ + input0: ["TENSOR_INT32"], + output0: ["TENSOR_INT32"], + }) + + float16 = DataTypeConverter().Identify({ + input0: ["TENSOR_FLOAT16"], + output0: ["TENSOR_FLOAT16"], + }) + + Example({ + input0: input_data, + output0: output_data, + }, model=model).AddVariations("relaxed", quant8, int32, float16) + +test( + input0=Input("input0", "TENSOR_FLOAT32", "{2, 2}"), + axis=0, + indices=[1, 0], + output0=Output("output0", "TENSOR_FLOAT32", "{2, 2}"), + input_data=[-2.0, 0.2, + 0.7, 0.8], + output_data=[0.7, 0.8, + -2.0, 0.2], +) + +test( + input0=Input("input0", "TENSOR_FLOAT32", "{2, 2}"), + axis=0, + indices=[1], # Unlike TensorFlow, 0-D arguments and outputs are not supported. + output0=Output("output0", "TENSOR_FLOAT32", "{1, 2}"), + input_data=[-2.0, 0.2, + 0.7, 0.8], + output_data=[0.7, 0.8], +) + +test( + input0=Input("input0", "TENSOR_FLOAT32", "{3}"), + axis=0, + indices=[1], + output0=Output("output0", "TENSOR_FLOAT32", "{1}"), + input_data=[1, 2, 3], + output_data=[2], +) + +test( + input0=Input("input0", "TENSOR_FLOAT32", "{3}"), + axis=0, + indices=[1, 0], + output0=Output("output0", "TENSOR_FLOAT32", "{2}"), + input_data=[1, 2, 3], + output_data=[2, 1], +) + +test( + input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 2}"), + axis=0, + indices=[0, 0], + output0=Output("output0", "TENSOR_FLOAT32", "{2, 2, 2}"), + input_data=[-2.0, 0.2, + 0.7, 0.8], + output_data=[-2.0, 0.2, + 0.7, 0.8, + -2.0, 0.2, + 0.7, 0.8], +) + +test( + input0=Input("input0", "TENSOR_FLOAT32", "{4, 1}"), + axis=0, + indices=[1, 3], + output0=Output("output0", "TENSOR_FLOAT32", "{2, 1}"), + input_data=[-2.0, 0.2, 0.7, 0.8], + output_data=[0.2, 0.8], +) + +test( + input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 3}"), + axis=1, + indices=[1, 0], + output0=Output("output0", "TENSOR_FLOAT32", "{1, 2, 3}"), + input_data=[1, 2, 3, + 4, 5, 6], + output_data=[4, 5, 6, + 1, 2, 3], +) + +test( + input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 3}"), + axis=-1, + indices=[2, 0], + output0=Output("output0", "TENSOR_FLOAT32", "{1, 2, 2}"), + input_data=[1, 2, 3, + 4, 5, 6], + output_data=[3, 1, + 6, 4], +) |