1#
2# Copyright (C) 2018 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
17# model
18model = Model()
19
20row = 212
21col1 = 60
22col2 = 30
23output_col = col1 + col2
24
25input1 = Input("input1", "TENSOR_FLOAT32", "{%d, %d}" % (row, col1)) # input tensor 1
26input2 = Input("input2", "TENSOR_FLOAT32", "{%d, %d}" % (row, col2)) # input tensor 2
27axis1 = Int32Scalar("axis1", 1)
28output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (row, output_col)) # output
29model = model.Operation("CONCATENATION", input1, input2, axis1).To(output)
30model = model.RelaxedExecution(True)
31
32# Example 1.
33input1_values = [x for x in range(row * col1)]
34input2_values = [-x for x in range(row * col2)]
35input0 = {input1: input1_values,
36          input2: input2_values}
37
38output_values = [x for x in range(row * output_col)]
39for r in range(row):
40  for c1 in range(col1):
41    output_values[r * output_col + c1] = input1_values[r * col1 + c1]
42  for c2 in range(col2):
43    output_values[r * output_col + col1 + c2] = input2_values[r * col2 + c2]
44
45output0 = {output: output_values}
46
47# Instantiate an example
48Example((input0, output0))
49