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