INNER CODE UNIT · Python

output_shape

onnx/onnx-tensorrt · onnx_tensorrt/backend.py:205

    output_shape = [-99]      # Dummy value only
    graph_inputs = [onnx_helper.make_tensor_value_info(
        name, np2onnx_dtype(array.dtype), array.shape)
                    for name, array in zip(node.input, inputs)]
    graph_outputs = [onnx_helper.make_tensor_value_info(
        name, np2onnx_dtype(output_dtype), output_shape)
                     for name in node.output]
    if use_weights:
        # Add initializers for all inputs except the first
        initializers = [onnx_helper.make_tensor(
            name, np2onnx_dtype(array.dtype), array.shape, array.flatten().tolist())
                        for name, array in zip(node.input[1:], inputs[1:])]
    else:
        initializers = []
    graph = onnx_helper.make_graph(
           [node], "RunNodeGraph_" + node.op_type,
           graph_inputs, graph_outputs, initializer=initializers)
    model = onnx_helper.make_model(graph)

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