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def setup_binding_shapes( | |
engine: trt.ICudaEngine, | |
context: trt.IExecutionContext, | |
host_inputs: List[np.ndarray], | |
input_binding_idxs: List[int], | |
output_binding_idxs: List[int], | |
): | |
# Explicitly set the dynamic input shapes, so the dynamic output | |
# shapes can be computed internally | |
for host_input, binding_index in zip(host_inputs, input_binding_idxs): | |
context.set_binding_shape(binding_index, host_input.shape) | |
assert context.all_binding_shapes_specified | |
host_outputs = [] | |
device_outputs = [] | |
for binding_index in output_binding_idxs: | |
output_shape = context.get_binding_shape(binding_index) | |
# Allocate buffers to hold output results after copying back to host | |
buffer = np.empty(output_shape, dtype=np.float32) | |
host_outputs.append(buffer) | |
# Allocate output buffers on device | |
device_outputs.append(cuda.mem_alloc(buffer.nbytes)) | |
return host_outputs, device_outputs |
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