122 lines
3.2 KiB
Python
122 lines
3.2 KiB
Python
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#
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# Copyright (C) 2018 The Android Open Source Project
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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def test(input0, axis, indices, output0, input_data, output_data):
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model = Model().Operation("GATHER", input0, axis, indices).To(output0)
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quant8 = DataTypeConverter().Identify({
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input0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
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output0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
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})
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int32 = DataTypeConverter().Identify({
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input0: ["TENSOR_INT32"],
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output0: ["TENSOR_INT32"],
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})
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float16 = DataTypeConverter().Identify({
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input0: ["TENSOR_FLOAT16"],
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output0: ["TENSOR_FLOAT16"],
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})
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Example({
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input0: input_data,
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output0: output_data,
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}, model=model).AddVariations("relaxed", quant8, int32, float16)
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test(
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input0=Input("input0", "TENSOR_FLOAT32", "{2, 2}"),
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axis=0,
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indices=[1, 0],
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output0=Output("output0", "TENSOR_FLOAT32", "{2, 2}"),
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input_data=[-2.0, 0.2,
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0.7, 0.8],
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output_data=[0.7, 0.8,
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-2.0, 0.2],
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)
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test(
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input0=Input("input0", "TENSOR_FLOAT32", "{2, 2}"),
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axis=0,
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indices=[1], # Unlike TensorFlow, 0-D arguments and outputs are not supported.
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output0=Output("output0", "TENSOR_FLOAT32", "{1, 2}"),
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input_data=[-2.0, 0.2,
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0.7, 0.8],
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output_data=[0.7, 0.8],
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)
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test(
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input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
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axis=0,
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indices=[1],
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output0=Output("output0", "TENSOR_FLOAT32", "{1}"),
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input_data=[1, 2, 3],
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output_data=[2],
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)
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test(
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input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
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axis=0,
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indices=[1, 0],
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output0=Output("output0", "TENSOR_FLOAT32", "{2}"),
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input_data=[1, 2, 3],
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output_data=[2, 1],
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)
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test(
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input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 2}"),
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axis=0,
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indices=[0, 0],
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output0=Output("output0", "TENSOR_FLOAT32", "{2, 2, 2}"),
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input_data=[-2.0, 0.2,
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0.7, 0.8],
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output_data=[-2.0, 0.2,
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0.7, 0.8,
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-2.0, 0.2,
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0.7, 0.8],
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)
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test(
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input0=Input("input0", "TENSOR_FLOAT32", "{4, 1}"),
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axis=0,
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indices=[1, 3],
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output0=Output("output0", "TENSOR_FLOAT32", "{2, 1}"),
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input_data=[-2.0, 0.2, 0.7, 0.8],
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output_data=[0.2, 0.8],
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)
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test(
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input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 3}"),
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axis=1,
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indices=[1, 0],
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output0=Output("output0", "TENSOR_FLOAT32", "{1, 2, 3}"),
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input_data=[1, 2, 3,
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4, 5, 6],
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output_data=[4, 5, 6,
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1, 2, 3],
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)
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test(
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input0=Input("input0", "TENSOR_FLOAT32", "{1, 2, 3}"),
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axis=-1,
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indices=[2, 0],
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output0=Output("output0", "TENSOR_FLOAT32", "{1, 2, 2}"),
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input_data=[1, 2, 3,
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4, 5, 6],
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output_data=[3, 1,
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6, 4],
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)
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