A fix for seed attribute in the keras random normal generator (#2126)

* A fix for seed field in the tf.keras random normal generator. The seed field was not passing to the converted onnx model due to that it exists in seed2 attribute instead of seed and its type is Integer and not float.

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Signed-off-by: inonbe <inonb@waves.com>
Co-authored-by: Jay Zhang <36183870+fatcat-z@users.noreply.github.com>

Author: inonbe

tf2onnx/onnx_opset/generator.py

@@ -60,8 +60,8 @@ def version_1(cls, ctx, node, **kwargs):
         # in the rewriter does not trigger. grappler will send the random uniform
         # with shape as input so we need to pickup the input here and if the shape is
         # const we make it an attribute.
-        seed = node.get_attr("seed")
-        node.set_attr("seed", float(seed.f))
+        seed = node.get_attr("seed2")
+        node.set_attr("seed", float(seed.i))
         utils.make_sure(node.inputs[0].is_const(), "%s node with non-const shape requires opset >= 9", node.type)
         shape = node.inputs[0].get_tensor_value()
         ctx.remove_input(node, node.input[0], 0)
@@ -88,8 +88,8 @@ def version_9(cls, ctx, node, **kwargs):
         if node.inputs[0].is_const():
             cls.version_1(ctx, node, **kwargs)
         else:
-            seed = node.get_attr("seed")
-            node.set_attr("seed", float(seed.f))
+            seed = node.get_attr("seed2")
+            node.set_attr("seed", float(seed.i))
             cast_node = ctx.make_node("Cast", [node.input[0]], attr={'to': onnx_pb.TensorProto.INT64})
             const_node = ctx.make_node("ConstantOfShape", cast_node.output)
             inputs = node.input.copy()