tests/nnapi/specs/V1_2/cast.mod.py

   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 import itertools
  18 import collections
  19
  20 Operand = collections.namedtuple(
  21     "Operand", ["name", "as_input", "as_output", "data", "supports_relaxation"])
  22
  23 operands = [
  24     Operand(
  25         name="float16",
  26         as_input=Input("input0", "TENSOR_FLOAT16", "{2, 3}"),
  27         as_output=Output("output0", "TENSOR_FLOAT16", "{2, 3}"),
  28         data=[1, 2, 3, 4, 5, 6],
  29         supports_relaxation=False),
  30     Operand(
  31         name="float32",
  32         as_input=Input("input0", "TENSOR_FLOAT32", "{2, 3}"),
  33         as_output=Output("output0", "TENSOR_FLOAT32", "{2, 3}"),
  34         data=[1, 2, 3, 4, 5, 6],
  35         supports_relaxation=True),
  36     Operand(
  37         name="int32",
  38         as_input=Input("input0", "TENSOR_INT32", "{2, 3}"),
  39         as_output=Output("output0", "TENSOR_INT32", "{2, 3}"),
  40         data=[1, 2, 3, 4, 5, 6],
  41         supports_relaxation=False),
  42     Operand(
  43         name="quant8",
  44         as_input=Input("input0", "TENSOR_QUANT8_ASYMM", "{2, 3}, 4.0, 100"),
  45         as_output=Output("output0", "TENSOR_QUANT8_ASYMM", "{2, 3}, 4.0, 100"),
  46         data=[1, 2, 3, 4, 5, 6],
  47         supports_relaxation=False),
  48 ]
  49
  50 for operand1, operand2 in itertools.product(operands, operands):
  51   input0 = operand1.as_input
  52   output0 = operand2.as_output
  53
  54   model = Model().Operation("CAST", input0).To(output0)
  55
  56   example = Example({
  57       input0: operand1.data,
  58       output0: operand2.data,
  59   }, model=model, name='{}_to_{}'.format(operand1.name, operand2.name))
  60
  61   if operand1.supports_relaxation or operand2.supports_relaxation:
  62     example.AddRelaxed()
  63
  64
  65 # Test overflow and underflow.
  66 operands = [
  67     Operand(
  68         name="float16",
  69         as_input=Input("input0", "TENSOR_FLOAT16", "{2}"),
  70         as_output=None,
  71         data=[-1, 256],
  72         supports_relaxation=False),
  73     Operand(
  74         name="float32",
  75         as_input=Input("input0", "TENSOR_FLOAT32", "{2}"),
  76         as_output=None,
  77         data=[-1, 256],
  78         supports_relaxation=True),
  79     Operand(
  80         name="int32",
  81         as_input=Input("input0", "TENSOR_INT32", "{2}"),
  82         as_output=None,
  83         data=[-1, 256],
  84         supports_relaxation=False),
  85 ]
  86
  87 for operand1 in operands:
  88   input0 = operand1.as_input
  89   output0 = Output("output0", "TENSOR_QUANT8_ASYMM", "{2}, 4.0, 100")
  90
  91   model = Model().Operation("CAST", input0).To(output0)
  92
  93   example = Example({
  94       input0: operand1.data,
  95       output0: [0, 255],
  96   }, model=model, name='{}_to_quant8_overflow'.format(operand1.name))
  97
  98   if operand1.supports_relaxation:
  99     example.AddRelaxed()