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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.
#
# This test is for testing the input requirements of Fully Connected Op:
# the input's first dimension doesn't have to be the batch size, the
# input is reshaped as needed.
model = Model()
in0 = Input("op1", "TENSOR_FLOAT32", "{4, 1, 5, 1}")
weights = Parameter("op2", "TENSOR_FLOAT32", "{3, 10}", [
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, # u = 0
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, # u = 1
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, # u = 1
])
bias = Parameter("b0", "TENSOR_FLOAT32", "{3}", [1, 2, 3])
out0 = Output("op3", "TENSOR_FLOAT32", "{2, 3}")
act = Int32Scalar("act", 0)
model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
model = model.RelaxedExecution(True)
# Example 1. Input in operand 0,
input0 = {in0: # input 0
[1, 2, 3, 4, 5, 6, 7, 8, -9, -10,
1, 2, 3, 4, 5, 6, 7, -8, 9, -10]}
output0 = {out0: # output 0
[24, 25, 26,
58, 59, 60]}
# Instantiate an example
Example((input0, output0))
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