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
20row1 = 52
21row2 = 40
22col = 230
23output_row = row1 + row2
24
25input1 = Input("input1", "TENSOR_FLOAT32", "{%d, %d}" % (row1, col)) # input tensor 1
26input2 = Input("input2", "TENSOR_FLOAT32", "{%d, %d}" % (row2, col)) # input tensor 2
27axis0 = Int32Scalar("axis0", 0)
28output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (output_row, col)) # output
29model = model.Operation("CONCATENATION", input1, input2, axis0).To(output)
30model = model.RelaxedExecution(True)
31
32# Example 1.
33input1_values = [x for x in range(row1 * col)]
34input2_values = (lambda s1 = row1 * col, s2 = row2 * col:
35                 [x + s1 for x in range(s2)])()
36input0 = {input1: input1_values,
37          input2: input2_values}
38output_values = [x for x in range(output_row * col)]
39output0 = {output: output_values}
40
41# Instantiate an example
42Example((input0, output0))
43