From e6506dfb152530ced61d1d92667503af74e2b61e Mon Sep 17 00:00:00 2001
From: auphelia <jakobapk@web.de>
Date: Thu, 18 Jun 2020 17:41:55 +0100
Subject: [PATCH] [Test] Add test for trafo to remove identity ops
---
.../test_remove_identity_ops.py | 81 +++++++++++++++++++
1 file changed, 81 insertions(+)
create mode 100644 tests/transformation/test_remove_identity_ops.py
diff --git a/tests/transformation/test_remove_identity_ops.py b/tests/transformation/test_remove_identity_ops.py
new file mode 100644
index 000000000..536c1ab0b
--- /dev/null
+++ b/tests/transformation/test_remove_identity_ops.py
@@ -0,0 +1,81 @@
+import pytest
+
+import numpy as np
+from onnx import helper, TensorProto
+import finn.core.onnx_exec as oxe
+from finn.core.datatype import DataType
+from finn.core.modelwrapper import ModelWrapper
+from finn.transformation.infer_datatypes import InferDataTypes
+from finn.transformation.infer_shapes import InferShapes
+from finn.transformation.streamline.remove import RemoveIdentityOps
+from finn.util.basic import gen_finn_dt_tensor
+
+
+def insert_identity_op(model, op):
+ if op in ["Add", "Sub"]:
+ val = np.asarray([0.0], dtype=np.float32)
+ elif op in ["Mul", "Div"]:
+ val = np.asarray([1.0], dtype=np.float32)
+ else:
+ return
+
+ identity_node = helper.make_node(op, ["div_out", "value"], ["ident_out"])
+ graph = model.graph
+ graph.node.insert(3, identity_node)
+ graph.node[-1].input[0] = "ident_out"
+ model.set_initializer("value", val)
+
+ return model
+
+
+# identity operations to be inserted
+@pytest.mark.parametrize("op", ["Add", "Sub", "Mul", "Div"])
+def test_remove_identity_ops(op):
+
+ # set up onnx model
+ inp = helper.make_tensor_value_info("inp", TensorProto.FLOAT, [1, 4, 1, 1])
+ mul = helper.make_tensor_value_info("mul", TensorProto.FLOAT, [])
+ shape = helper.make_tensor_value_info("shape", TensorProto.FLOAT, [2])
+ div = helper.make_tensor_value_info("div", TensorProto.FLOAT, [])
+ matmul = helper.make_tensor_value_info("matmul", TensorProto.FLOAT, [4, 2])
+ outp = helper.make_tensor_value_info("outp", TensorProto.FLOAT, [1, 2])
+
+ mul_node = helper.make_node("Mul", ["inp", "mul"], ["mul_out"])
+ reshape_node = helper.make_node("Reshape", ["mul_out", "shape"], ["reshape_out"])
+ div_node = helper.make_node("Div", ["reshape_out", "div"], ["div_out"])
+ matmul_node = helper.make_node("MatMul", ["div_out", "matmul"], ["outp"])
+
+ graph = helper.make_graph(
+ nodes=[mul_node, reshape_node, div_node, matmul_node],
+ name="identity-graph",
+ inputs=[inp],
+ outputs=[outp],
+ value_info=[mul, shape, div, matmul],
+ )
+
+ model = helper.make_model(graph, producer_name="mulpastconv-model")
+ model = ModelWrapper(model)
+ inp_values = gen_finn_dt_tensor(DataType.INT2, [1, 4, 1, 1])
+ mul_values = np.random.uniform(low=0.1, high=0.99, size=(1)).astype(np.float32)
+ shape_values = np.asarray([1, -1], dtype=np.int64)
+ div_values = np.random.uniform(low=0.1, high=0.99, size=(1)).astype(np.float32)
+ matmul_values = gen_finn_dt_tensor(DataType.INT2, [4, 2])
+ model.set_initializer("mul", mul_values)
+ model.set_initializer("shape", shape_values)
+ model.set_initializer("div", div_values)
+ model.set_initializer("matmul", matmul_values)
+ insert_identity_op(model, op)
+ model = model.transform(InferShapes())
+ model = model.transform(InferDataTypes())
+ idict = {"inp": inp_values}
+ odict = oxe.execute_onnx(model, idict)
+ out_before = odict["outp"]
+ num_of_nodes_before = len(model.graph.node)
+
+ model = model.transform(RemoveIdentityOps())
+ num_of_nodes_after = len(model.graph.node)
+ assert num_of_nodes_before - 1 == num_of_nodes_after
+
+ odict = oxe.execute_onnx(model, idict)
+ out_after = odict["outp"]
+ assert (out_before == out_after).all()
--
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