1#
2# Copyright (C) 2017 The Android Open Source Project
3#
4# Licensed under the Apache License, Version 2.0 (the "License");
5# you may not use this file except in compliance with the License.
6# You may obtain a copy of the License at
7#
8#      http://www.apache.org/licenses/LICENSE-2.0
9#
10# Unless required by applicable law or agreed to in writing, software
11# distributed under the License is distributed on an "AS IS" BASIS,
12# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13# See the License for the specific language governing permissions and
14# limitations under the License.
15
16# conv_quant8.mod.py with biases and filter being constants
17
18model = Model()
19i1 = Input("op1", "TENSOR_QUANT8_ASYMM", "{1, 3, 3, 1}, 0.5f, 0")
20f1 = Parameter("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 1}, 0.5f, 0",
21               [2, 2, 2, 2])
22b1 = Parameter("op3", "TENSOR_INT32", "{1}, 0.25f, 0", [4])
23pad0 = Int32Scalar("pad0", 0)
24act = Int32Scalar("act", 0)
25stride = Int32Scalar("stride", 1)
26# output dimension:
27#     (i1.height - f1.height + 1) x (i1.width - f1.width + 1)
28output = Output("op4", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 1}, 1.f, 0")
29
30model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride,
31                        stride, act).To(output)
32
33# Example 1. Input in operand 0,
34input0 = {
35    i1:  # input 0
36        [8, 8, 8, 8, 4, 8, 8, 8, 8]
37}
38# (i1 (conv) f1) + b1
39output0 = {
40    output:  # output 0
41        [15, 15, 15, 15]
42}
43
44# Instantiate an example
45Example((input0, output0))
46