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
17model = Model()
18i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 2}")
19f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0, .2, 0, .25, 0, 0, .3, .25, 0, 0, 0, .25, .1, 0, 0])
20b1 = Parameter("op3", "TENSOR_FLOAT32", "{4}", [1, 2, 3, 4])
21pad0 = Int32Scalar("pad0", 0)
22act = Int32Scalar("act", 0)
23stride = Int32Scalar("stride", 1)
24cm = Int32Scalar("channelMultiplier", 2)
25output = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}")
26
27model = model.Operation("DEPTHWISE_CONV_2D",
28                        i1, f1, b1,
29                        pad0, pad0, pad0, pad0,
30                        stride, stride,
31                        cm, act).To(output)
32
33# Example 1. Input in operand 0,
34input0 = {i1: # input 0
35          [10, 21, 10, 22, 10, 23,
36           10, 24, 10, 25, 10, 26,
37           10, 27, 10, 28, 10, 29]}
38# (i1 (conv) f1) + b1
39# filter usage:
40#   in_ch1 * f_1  --> output_d1
41#   in_ch1 * f_2  --> output_d2
42#   in_ch2 * f_3  --> output_d3
43#   in_ch3 * f_4  --> output_d4
44output0 = {output: # output 0
45           [11, 3, 7.2, 10.6,
46            11, 3, 7.4, 10.9,
47            11, 3, 7.8, 11.5,
48            11, 3, 8.0, 11.8]}
49
50# Instantiate an example
51Example((input0, output0))
52