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test_tipc/supplementary/slim/slim_fpgm.py

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+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