summaryrefslogtreecommitdiff
path: root/nn/runtime/test/specs/V1_3/while_fib.mod.py
blob: f8f0581332768ebbdd62394b26cecd679fae6ff5 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
#
# Copyright (C) 2020 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.
#

# Model: given n, produces [fib(n), fib(n + 1)].
#
# fib = [1, 1]
# i = 1
# while i < n:
#     fib = matmul(fib, [0 1;
#                        1 1])
#     i = i + 1

FibType = ["TENSOR_FLOAT32", [1, 2]]
CounterType = ["TENSOR_INT32", [1]]
BoolType = ["TENSOR_BOOL8", [1]]

def MakeConditionModel():
  fib = Input("fib", FibType)
  i = Input("i", CounterType)
  n = Input("n", CounterType)
  out = Output("out", BoolType)
  model = Model()
  model.IdentifyInputs(fib, i, n)
  model.IdentifyOutputs(out)
  model.Operation("LESS", i, n).To(out)
  return model

def MakeBodyModel():
  fib = Input("fib", FibType)
  i = Input("i", CounterType)
  n = Input("n", CounterType)
  fib_out = Output("fib_out", FibType)
  i_out = Output("i_out", CounterType)
  matrix = Parameter("matrix", ["TENSOR_FLOAT32", [2, 2]], [0, 1, 1, 1])
  zero_bias = Parameter("zero_bias", ["TENSOR_FLOAT32", [2, 1]], [0, 0])
  model = Model()
  model.IdentifyInputs(fib, i, n)
  model.IdentifyOutputs(fib_out, i_out)
  model.Operation("ADD", i, [1], 0).To(i_out)
  model.Operation("FULLY_CONNECTED", fib, matrix, zero_bias, 0).To(fib_out)
  return model

def Test(n, fib):
  n_ = Input("n", CounterType)
  fib_out = Output("fib_out", FibType)
  cond = MakeConditionModel()
  body = MakeBodyModel()
  fib_init = Parameter("fib_init", FibType, [1, 1])
  i_init = [1]
  model = Model().Operation("WHILE", cond, body, fib_init, i_init, n_).To(fib_out)
  example = Example({n_: [n], fib_out: fib}, name=str(n), model=model)
  example.AddVariations(AllOutputsAsInternalCoverter())

# Fibonacci numbers: 1 1 2 3 5 8
Test(n=1, fib=[1, 1])
Test(n=2, fib=[1, 2])
Test(n=3, fib=[2, 3])
Test(n=4, fib=[3, 5])
Test(n=5, fib=[5, 8])