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#
# Copyright (C) 2019 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.
#
i1 = Input("op1", "TENSOR_FLOAT32", "{2, 2, 2, 3}") # input 0
o1 = Output("op2", "TENSOR_FLOAT32", "{2, 2, 2, 3}") # output 0
axis = Int32Scalar("axis", -1) # last axis
quant8_signed = DataTypeConverter().Identify({
i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -96),
o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 1.0 / 128, 0)
})
example0 = {
i1: [ 0, 3, 4,
3, 0, 4,
8, 6, 0,
12, 0, 9,
9, 12, 20,
12, 15, 16,
20, 9, 12,
16, 15, 12],
o1: [0.00, 0.60, 0.80,
0.60, 0.00, 0.80,
0.80, 0.60, 0.00,
0.80, 0.00, 0.60,
0.36, 0.48, 0.80,
0.48, 0.60, 0.64,
0.80, 0.36, 0.48,
0.64, 0.60, 0.48]
}
# All dimensions, with all possible axis parameter
Model().Operation("L2_NORMALIZATION", i1, axis).To(o1)
Example(example0).AddAllDimsAndAxis(i1, o1, axis).AddVariations(quant8_signed, includeDefault=False)
#######################################################
i1 = Input("op1", "TENSOR_FLOAT32", "{2, 2, 2, 3}") # input 0
o1 = Output("op2", "TENSOR_FLOAT32", "{2, 2, 2, 3}") # output 0
axis = Int32Scalar("axis", -1) # last axis
quant8_signed = DataTypeConverter().Identify({
i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, -96),
o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 1.0 / 128, 0)
})
example0 = {
i1: [ 0, 3, 4,
3, 0, 4,
8, 6, 0,
12, 0, 9,
9, 12, 20,
12, 15, 16,
20, 9, 12,
16, 15, 12],
o1: [0.00, 0.60, 0.80,
0.60, 0.00, 0.80,
0.80, 0.60, 0.00,
0.80, 0.00, 0.60,
0.36, 0.48, 0.80,
0.48, 0.60, 0.64,
0.80, 0.36, 0.48,
0.64, 0.60, 0.48]
}
# All dimensions other than 4, without axis parameter
Model().Operation("L2_NORMALIZATION", i1).To(o1)
Example(example0).AddAllDims(i1, o1).AddVariations(quant8_signed, includeDefault=False)
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