From f29a92fce5408094abc9d36fc207eb1a17eb1c11 Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <yamanu@xilinx.com>
Date: Wed, 30 Oct 2019 11:42:40 +0000
Subject: [PATCH] [Test] add test_move_scalar_add_past_matmul
---
...mul.py => test_move_scalar_past_matmul.py} | 33 +++++++++++++++++++
1 file changed, 33 insertions(+)
rename tests/{test_move_scalar_mul_past_matmul.py => test_move_scalar_past_matmul.py} (53%)
diff --git a/tests/test_move_scalar_mul_past_matmul.py b/tests/test_move_scalar_past_matmul.py
similarity index 53%
rename from tests/test_move_scalar_mul_past_matmul.py
rename to tests/test_move_scalar_past_matmul.py
index 55a7d8cbe..a9cd35d42 100644
--- a/tests/test_move_scalar_mul_past_matmul.py
+++ b/tests/test_move_scalar_past_matmul.py
@@ -39,3 +39,36 @@ def test_move_scalar_mul_past_matmul():
assert new_model.graph.node[0].op_type == "MatMul"
assert new_model.graph.node[1].op_type == "Mul"
assert new_model.graph.node[0].output[0] == new_model.graph.node[1].input[0]
+
+
+def test_move_scalar_add_past_matmul():
+ top_in = oh.make_tensor_value_info("top_in", TensorProto.FLOAT, [1, 2])
+ add_param = oh.make_tensor_value_info("add_param", TensorProto.FLOAT, [1, 1])
+ matmul_param = oh.make_tensor_value_info("matmul_param", TensorProto.FLOAT, [2, 2])
+ top_out = oh.make_tensor_value_info("top_out", TensorProto.FLOAT, [1, 2])
+ modelproto = oh.make_model(
+ oh.make_graph(
+ name="test",
+ inputs=[top_in],
+ outputs=[top_out],
+ value_info=[add_param, matmul_param],
+ nodes=[
+ oh.make_node("Add", ["top_in", "add_param"], ["middle"]),
+ oh.make_node("MatMul", ["middle", "matmul_param"], ["top_out"]),
+ ],
+ )
+ )
+ model = ModelWrapper(modelproto)
+ model = model.transform_single(si.infer_shapes)
+ model.set_initializer("add_param", np.asarray([[3]], dtype=np.float32))
+ model.set_initializer(
+ "matmul_param", np.asarray([[2, 4], [-1, 1]], dtype=np.float32)
+ )
+ new_model = model.transform_repeated(tx.move_scalar_add_past_matmul)
+ inp_dict = {"top_in": np.asarray([[-1.0, 1.0]], dtype=np.float32)}
+ out_orig = ox.execute_onnx(model, inp_dict)["top_out"]
+ out_transformed = ox.execute_onnx(new_model, inp_dict)["top_out"]
+ assert np.isclose(out_orig, out_transformed).all()
+ assert new_model.graph.node[0].op_type == "MatMul"
+ assert new_model.graph.node[1].op_type == "Add"
+ assert new_model.graph.node[0].output[0] == new_model.graph.node[1].input[0]
--
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