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# Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
import onnx
from onnx import helper, TensorProto
QUERY_TENSOR = helper.make_tensor_value_info('query_tensor', TensorProto.FLOAT, ['batch', 4])
ATTRIBUTE_TENSOR = helper.make_tensor_value_info('attribute_tensor', TensorProto.FLOAT, [4, 1])
BIAS_TENSOR = helper.make_tensor_value_info('bias_tensor', TensorProto.FLOAT, ['batch', -1])
OUTPUT = helper.make_tensor_value_info('output', TensorProto.FLOAT, ['batch', 1])
nodes = [
helper.make_node(
'MatMul',
['query_tensor', 'attribute_tensor'],
['matmul'],
),
helper.make_node(
'ReduceSum',
['bias_tensor'],
['reduce'],
axes=[1]
),
helper.make_node(
'Add',
['matmul', 'reduce'],
['output'],
),
]
graph_def = helper.make_graph(
nodes,
'dynamic_scoring',
[
QUERY_TENSOR,
ATTRIBUTE_TENSOR,
BIAS_TENSOR,
],
[OUTPUT],
)
model_def = helper.make_model(graph_def, producer_name='dynamic.py', opset_imports=[onnx.OperatorSetIdProto(version=12)])
onnx.save(model_def, 'dynamic.onnx')
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