PaddleOCR MCP Server

import paddleslim import paddle import numpy as np from paddleslim.dygraph import FPGMFilterPruner def prune_model(model, input_shape, prune_ratio=0.1): flops = paddle.flops(model, input_shape) pruner = FPGMFilterPruner(model, input_shape) params_sensitive = {} for param in model.parameters(): if "transpose" not in param.name and "linear" not in param.name: # set prune ratio as 10%. The larger the value, the more convolution weights will be cropped params_sensitive[param.name] = prune_ratio plan = pruner.prune_vars(params_sensitive, [0]) flops = paddle.flops(model, input_shape) return model