#
# Copyright (C) 2017 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 math

# model
model = Model()

d0 = 1 #2
d1 = 16 #256
d2 = 16 #256
d3 = 1 #2

i0 = Input("input", "TENSOR_QUANT8_ASYMM", "{%d, %d, %d, %d}, .5f, 0" % (d0, d1, d2, d3))

output = Output("output", "TENSOR_QUANT8_ASYMM", "{%d, %d, %d, %d}, 0.00390625f, 0" % (d0, d1, d2, d3))

model = model.Operation("LOGISTIC", i0).To(output)

# Example 1. Input in operand 0,
rng = d0 * d1 * d2 * d3
input_values = (lambda r = rng: [x % 256 for x in range(r)])()
input0 = {i0: input_values}
output_values = [
    255 if 1. / (1. + math.exp(-x * .5)) * 256 > 255
        else int(round(1. / (1. + math.exp(-x * .5)) * 256))
    for x in input_values]
output0 = {output: output_values}

# Instantiate an example
Example((input0, output0))