xref: /frameworks/ml/nn/runtime/test/specs/V1_0/fully_connected_quant8_large_weights_as_inputs.mod.py

#
# Copyright (C) 2017 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.
#

model = Model()
in0 = Input("op1", "TENSOR_QUANT8_ASYMM", "{1, 5}, 0.2, 0") # batch = 1, input_size = 5
weights = Input("op2", "TENSOR_QUANT8_ASYMM", "{1, 5}, 0.2, 0") # num_units = 1, input_size = 5
bias = Input("b0", "TENSOR_INT32", "{1}, 0.04, 0")
out0 = Output("op3", "TENSOR_QUANT8_ASYMM", "{1, 1}, 1.f, 0") # batch = 1, number_units = 1
act = Int32Scalar("act", 0)
model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)

# Example 1. Input in operand 0,
input0 = {in0: # input 0
          [10, 10, 10, 10, 10],
          weights:
          [10, 20, 20, 20, 10],
          bias:
          [10]}
output0 = {out0: # output 0
           [32]}

# Instantiate an example
Example((input0, output0))