100 lines
3.3 KiB
Python
100 lines
3.3 KiB
Python
#
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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(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True):
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model = Model().Operation("GREATER", input0, input1).To(output0)
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example = Example({
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input0: input0_data,
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input1: input1_data,
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output0: output_data,
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}, model=model, name=name)
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if do_variations:
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example.AddVariations("int32", "float16", "relaxed")
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test(
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name="simple",
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input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
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input1=Input("input1", "TENSOR_FLOAT32", "{3}"),
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output0=Output("output0", "TENSOR_BOOL8", "{3}"),
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input0_data=[5, 7, 10],
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input1_data=[10, 7, 5],
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output_data=[False, False, True],
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)
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test(
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name="broadcast",
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input0=Input("input0", "TENSOR_FLOAT32", "{2, 1}"),
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input1=Input("input1", "TENSOR_FLOAT32", "{2}"),
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output0=Output("output0", "TENSOR_BOOL8", "{2, 2}"),
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input0_data=[5, 10],
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input1_data=[10, 5],
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output_data=[False, False, False, True],
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)
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test(
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name="quantized_different_scale",
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input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
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input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 2.0, 128)),
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output0=Output("output0", "TENSOR_BOOL8", "{3}"),
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input0_data=[129, 130, 131], # effectively 1, 2, 3
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input1_data=[129], # effectively 2
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output_data=[False, False, True],
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do_variations=False,
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)
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test(
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name="quantized_different_zero_point",
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input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
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input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.0, 129)),
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output0=Output("output0", "TENSOR_BOOL8", "{3}"),
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input0_data=[129, 130, 131], # effectively 1, 2, 3
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input1_data=[131], # effectively 2
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output_data=[False, False, True],
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do_variations=False,
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)
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test(
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name="quantized_overflow_second_input_if_requantized",
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input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
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input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
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output0=Output("output0", "TENSOR_BOOL8", "{1}"),
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input0_data=[0],
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input1_data=[200],
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output_data=[True],
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do_variations=False,
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)
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test(
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name="quantized_overflow_first_input_if_requantized",
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input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
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input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
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output0=Output("output0", "TENSOR_BOOL8", "{1}"),
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input0_data=[200],
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input1_data=[0],
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output_data=[False],
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do_variations=False,
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)
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test(
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name="boolean",
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input0=Input("input0", "TENSOR_BOOL8", "{4}"),
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input1=Input("input1", "TENSOR_BOOL8", "{4}"),
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output0=Output("output0", "TENSOR_BOOL8", "{4}"),
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input0_data=[False, True, False, True],
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input1_data=[False, False, True, True],
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output_data=[False, True, False, False],
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do_variations=False,
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)
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