serialization: version mismatch info, added pytest

Author: liamsemeria

serialization_temp_example.py

@@ -7,6 +7,7 @@
 from .graph import XTCGraph
 from .context import XTCGraphContext
 from .expr import XTCTensorExpr
+from .operators import XTCOperator
 from . import op_factory
 from yaml import safe_load
 
@@ -52,8 +53,14 @@ def tuplify(obj: Any) -> Any:
             if "name" in node:
                 args.append(node["name"])
             if not hasattr(op_factory, expr["op"]["name"]):
+                version_mismatch = (
+                    "version mismatch detected, "
+                    if XTCOperator.version_string() != graph_dict["ops_version"]
+                    else ""
+                )
                 raise ValueError(
-                    f"serialized op {expr['op']['name']} is not implemented!"
+                    version_mismatch
+                    + f"serialized op {expr['op']['name']} is not implemented."
                 )
             op_func = getattr(op_factory, expr["op"]["name"])
             expr_uid_map[node["uid"]] = op_func(*args, **tuplify(expr["op"]["attrs"]))

src/xtc/graphs/xtc/builder.py

@@ -0,0 +1,66 @@
+import tempfile
+import xtc.graphs.xtc.op as O
+
+def test_matmul_relu_to_from_dict():
+    I, J, K, dtype = 4, 32, 512, "float32"
+    a = O.tensor((I, K), dtype, name="A")
+    b = O.tensor((K, J), dtype, name="B")
+
+    with O.graph(name="matmul_relu") as gb:
+        m = O.matmul(a, b, name="matmul")
+        O.relu(m, name="relu")
+
+    graph_dict = gb.graph.to_dict()
+    with O.graph() as gb2:
+        gb2.from_dict(graph_dict)
+    assert graph_dict != {}
+    assert graph_dict == gb2.graph.to_dict()
+        
+
+def test_conv2d_pad_sdump_sload():
+    N, H, W, F, R, S, C, SH, SW, dtype = 1, 8, 8, 16, 5, 5, 3, 2, 2, "float32"
+    a = O.tensor((N, H, W, C), dtype, name="I")
+    b = O.tensor((R, S, C, F), dtype, name="W")
+
+    with O.graph(name="pad_conv2d_nhwc_mini") as gb:
+        p = O.pad(a, padding={1: (2), 2: (2, 2)}, name="pad")
+        O.conv2d(p, b, stride=(SH, SW), name="conv")
+
+    graph_str = gb.graph.dumps()
+    with O.graph(name="matmul_relu") as gb2:
+        gb2.loads(graph_str)
+    assert graph_str != ""
+    assert graph_str == gb2.graph.dumps()
+
+    with tempfile.NamedTemporaryFile(mode="w+", delete=True) as f:
+        gb.graph.dump(f.name)
+        with O.graph() as gb3:
+            gb3.load(f.name)
+        assert gb.graph.to_dict() == gb3.graph.to_dict()
+
+def test_mlp_fc_custom_output():
+    img = O.tensor()
+    w1 = O.tensor()
+    w2 = O.tensor()
+    w3 = O.tensor()
+    w4 = O.tensor()
+    fc = lambda i, w, nout: O.matmul(O.reshape(i, shape=(1, -1)), O.reshape(w, shape=(-1, nout)))
+    # Multi Layer Perceptron with 3 relu(fc) + 1 fc
+    with O.graph(name="mlp4") as gb:
+        with O.graph(name="l1"):
+            l1 = O.relu(fc(img, w1, 512))
+        with O.graph(name="l2"):
+            l2 = O.relu(fc(l1, w2, 256))
+        with O.graph(name="l3"):
+            l3 = O.relu(fc(l2, w3, 128))
+        with O.graph(name="l4"):
+            l4 = fc(l3, w4, 10)
+        O.reshape(l4, shape=(-1,))
+        O.outputs(l1)
+   
+    graph_dict = gb.graph.to_dict()
+    with O.graph() as gb2:
+        gb2.from_dict(graph_dict)
+    assert graph_dict != {}
+    assert graph_dict == gb2.graph.to_dict()
+