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# Copyright Vespa.ai. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
import onnx
from onnx import helper, TensorProto
input = helper.make_tensor_value_info('input', TensorProto.FLOAT, [3])
output = helper.make_tensor_value_info('output', TensorProto.FLOAT, [3])
initializers = [
helper.make_tensor(
name='epsilon', # small constant: no dimensions
data_type=TensorProto.FLOAT,
dims=(),
vals=[1e-6]
)
]
nodes = [
onnx.helper.make_node(
'Exp',
inputs=['input'],
outputs=['exp_output']
),
onnx.helper.make_node(
'ReduceSum',
inputs=['exp_output'],
outputs=['sum_exp_output'],
axes=[0]
),
onnx.helper.make_node(
'Add',
inputs=['sum_exp_output', 'epsilon'],
outputs=['add_output']
),
onnx.helper.make_node(
'Div',
inputs=['exp_output', 'add_output'],
outputs=['output']
)
]
graph_def = onnx.helper.make_graph(
nodes = nodes,
name = 'test',
inputs = [input],
outputs = [output],
initializer = initializers
)
model_def = helper.make_model(graph_def, producer_name='small_constants_and_functions.py')
onnx.checker.check_model(model_def)
onnx.save(model_def, 'small_constants_and_functions.onnx')
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