100 lines
3.1 KiB
Python
100 lines
3.1 KiB
Python
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# Copyright (C) 2018 The Android Open Source Project
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import itertools
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import collections
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Operand = collections.namedtuple(
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"Operand", ["name", "as_input", "as_output", "data", "supports_relaxation"])
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operands = [
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Operand(
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name="float16",
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as_input=Input("input0", "TENSOR_FLOAT16", "{2, 3}"),
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as_output=Output("output0", "TENSOR_FLOAT16", "{2, 3}"),
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data=[1, 2, 3, 4, 5, 6],
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supports_relaxation=False),
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Operand(
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name="float32",
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as_input=Input("input0", "TENSOR_FLOAT32", "{2, 3}"),
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as_output=Output("output0", "TENSOR_FLOAT32", "{2, 3}"),
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data=[1, 2, 3, 4, 5, 6],
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supports_relaxation=True),
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Operand(
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name="int32",
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as_input=Input("input0", "TENSOR_INT32", "{2, 3}"),
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as_output=Output("output0", "TENSOR_INT32", "{2, 3}"),
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data=[1, 2, 3, 4, 5, 6],
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supports_relaxation=False),
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Operand(
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name="quant8",
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as_input=Input("input0", "TENSOR_QUANT8_ASYMM", "{2, 3}, 4.0, 100"),
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as_output=Output("output0", "TENSOR_QUANT8_ASYMM", "{2, 3}, 4.0, 100"),
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data=[1, 2, 3, 4, 5, 6],
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supports_relaxation=False),
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]
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for operand1, operand2 in itertools.product(operands, operands):
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input0 = operand1.as_input
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output0 = operand2.as_output
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model = Model().Operation("CAST", input0).To(output0)
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example = Example({
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input0: operand1.data,
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output0: operand2.data,
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}, model=model, name='{}_to_{}'.format(operand1.name, operand2.name))
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if operand1.supports_relaxation or operand2.supports_relaxation:
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example.AddRelaxed()
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# Test overflow and underflow.
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operands = [
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Operand(
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name="float16",
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as_input=Input("input0", "TENSOR_FLOAT16", "{2}"),
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as_output=None,
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data=[-1, 256],
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supports_relaxation=False),
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Operand(
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name="float32",
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as_input=Input("input0", "TENSOR_FLOAT32", "{2}"),
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as_output=None,
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data=[-1, 256],
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supports_relaxation=True),
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Operand(
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name="int32",
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as_input=Input("input0", "TENSOR_INT32", "{2}"),
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as_output=None,
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data=[-1, 256],
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supports_relaxation=False),
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]
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for operand1 in operands:
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input0 = operand1.as_input
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output0 = Output("output0", "TENSOR_QUANT8_ASYMM", "{2}, 4.0, 100")
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model = Model().Operation("CAST", input0).To(output0)
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example = Example({
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input0: operand1.data,
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output0: [0, 255],
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}, model=model, name='{}_to_quant8_overflow'.format(operand1.name))
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if operand1.supports_relaxation:
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example.AddRelaxed()
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