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rpitonak/graph_inputs.py

Last active July 12, 2022 07:42
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graph_inputs.py
model_input_name = "X"
X = onnx.helper.make_tensor_value_info(
model_input_name,
onnx.TensorProto.FLOAT,
[None, None, None, 3]) # notice that we are leaving just channels dimension fixed, Batch size, width and heigh is not known in advance
model_output_name = "Y"
Y = onnx.helper.make_tensor_value_info(
model_output_name,
onnx.TensorProto.FLOAT,
[None, 3, 224, 224]) # output is resized but also transposed to be ready as an input to Squeezenet model
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