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#
# Copyright (C) 2018 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.
#
import itertools
import collections
Operand = collections.namedtuple(
"Operand", ["name", "as_input", "as_output", "data", "supports_relaxation"])
operands = [
Operand(
name="float16",
as_input=Input("input0", "TENSOR_FLOAT16", "{2, 3}"),
as_output=Output("output0", "TENSOR_FLOAT16", "{2, 3}"),
data=[1, 2, 3, 4, 5, 6],
supports_relaxation=False),
Operand(
name="float32",
as_input=Input("input0", "TENSOR_FLOAT32", "{2, 3}"),
as_output=Output("output0", "TENSOR_FLOAT32", "{2, 3}"),
data=[1, 2, 3, 4, 5, 6],
supports_relaxation=True),
Operand(
name="int32",
as_input=Input("input0", "TENSOR_INT32", "{2, 3}"),
as_output=Output("output0", "TENSOR_INT32", "{2, 3}"),
data=[1, 2, 3, 4, 5, 6],
supports_relaxation=False),
Operand(
name="quant8",
as_input=Input("input0", "TENSOR_QUANT8_ASYMM", "{2, 3}, 4.0, 100"),
as_output=Output("output0", "TENSOR_QUANT8_ASYMM", "{2, 3}, 4.0, 100"),
data=[1, 2, 3, 4, 5, 6],
supports_relaxation=False),
]
for operand1, operand2 in itertools.product(operands, operands):
input0 = operand1.as_input
output0 = operand2.as_output
model = Model().Operation("CAST", input0).To(output0)
example = Example({
input0: operand1.data,
output0: operand2.data,
}, model=model, name='{}_to_{}'.format(operand1.name, operand2.name))
if operand1.supports_relaxation or operand2.supports_relaxation:
example.AddRelaxed()
# Test overflow and underflow.
operands = [
Operand(
name="float16",
as_input=Input("input0", "TENSOR_FLOAT16", "{2}"),
as_output=None,
data=[-1, 256],
supports_relaxation=False),
Operand(
name="float32",
as_input=Input("input0", "TENSOR_FLOAT32", "{2}"),
as_output=None,
data=[-1, 256],
supports_relaxation=True),
Operand(
name="int32",
as_input=Input("input0", "TENSOR_INT32", "{2}"),
as_output=None,
data=[-1, 256],
supports_relaxation=False),
]
for operand1 in operands:
input0 = operand1.as_input
output0 = Output("output0", "TENSOR_QUANT8_ASYMM", "{2}, 4.0, 100")
model = Model().Operation("CAST", input0).To(output0)
example = Example({
input0: operand1.data,
output0: [0, 255],
}, model=model, name='{}_to_quant8_overflow'.format(operand1.name))
if operand1.supports_relaxation:
example.AddRelaxed()
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