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# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import onnx
from onnx import TensorProto, helper
from onnx.helper import make_opsetid
input_info = helper.make_tensor_value_info("input", TensorProto.FLOAT16, [1, 5])
output_info = helper.make_tensor_value_info("output", TensorProto.FLOAT16, [1, 5])
# Create a node (NodeProto) - This is based on Pad-11
node_def = helper.make_node(
"Slice", # node name
["input"], # inputs
["output"], # outputs
axes=[0, 1], # attributes
ends=[1, 5],
starts=[0, 0],
)
graph_def = helper.make_graph(nodes=[node_def], name="test_input_FLOAT16", inputs=[input_info], outputs=[output_info])
model_def = helper.make_model(graph_def, producer_name="AIInfra", opset_imports=[make_opsetid("", 7)])
onnx.checker.check_model(model_def)
onnx.helper.strip_doc_string(model_def)
final_model = onnx.shape_inference.infer_shapes(model_def)
onnx.checker.check_model(final_model)
onnx.save(final_model, "test_types_FLOAT16.onnx")
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