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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.
#
import itertools
def dequantize(x, scale, offset):
return (x - offset) * scale
def quantize(x, scale, offset):
return max(0, min(255, int(round(x / scale)) + offset))
def create_test(input0_scale, input0_offset,
input1_scale, input1_offset,
output_scale, output_offset):
def sub_quantized(a, b):
a_dequantized = dequantize(a, input0_scale, input0_offset)
b_dequantized = dequantize(b, input1_scale, input1_offset)
return quantize(a_dequantized - b_dequantized, output_scale, output_offset)
values = [0, 1, 2, 3, 4, 5, 250, 251, 252, 253, 254, 255]
inputs = list(itertools.product(values, values))
input0_values, input1_values = zip(*inputs)
output_values = [sub_quantized(a, b) for a, b in inputs]
size = len(output_values)
input0 = Input("input0", "TENSOR_QUANT8_ASYMM",
"{%d}, %g, %d" % (size, input0_scale, input0_offset))
input1 = Input("input1", "TENSOR_QUANT8_ASYMM",
"{%d}, %g, %d" % (size, input1_scale, input1_offset))
activation = 0
output0 = Output("output0", "TENSOR_QUANT8_ASYMM",
"{%d}, %g, %d" % (size, output_scale, output_offset))
model = Model().Operation("SUB", input0, input1, activation).To(output0)
Example({
input0: input0_values,
input1: input1_values,
output0: output_values,
})
scales_and_offsets = [(1.0, 0),
(1.0, 1),
(0.01, 120),
(10.0, 120)]
for params in itertools.product(scales_and_offsets,
scales_and_offsets,
scales_and_offsets):
input0_params, input1_params, output_params = params
create_test(*input0_params, *input1_params, *output_params)
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