INNER CODE UNIT · Python

run

onnx/onnx-tensorrt · onnx_tensorrt/backend.py:148

    def run(self, inputs, **kwargs):
        """Execute the prepared engine and return the outputs as a named tuple.
        inputs -- Input tensor(s) as a Numpy array or list of Numpy arrays.
        """
        if isinstance(inputs, np.ndarray):
            inputs = [inputs]

        if self.dynamic:
            self._build_engine(inputs)

        outputs = self.engine.run(inputs)
        output_names = [output.name for output in self.engine.outputs]

        for i, (name, array) in enumerate(zip(output_names, outputs)):
            output_shape = self._output_shapes[name]
            # HACK WAR for unknown output shape in run_node
            if output_shape == (-99,):
                # WAR for TRT requiring at least 2 dims (NC)

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