simplify GRE and LRE

Author: RandySheriffH

tests/test_backend.py

@@ -3153,7 +3153,16 @@ def test_einsum(self):
         def func(x, y):
             ret = tf.einsum("i,j->ij", x, y)
             return tf.identity(ret, name=_TFOUTPUT)
-        self._run_test_case(func, [_OUTPUT],  {_INPUT: x_val, _INPUT1: y_val})
+        self._run_test_case(func, [_OUTPUT], {_INPUT: x_val, _INPUT1: y_val})
+
+    @check_opset_min_version(12)
+    def test_compare(self):
+        x_val = np.random.random([10, 20]).astype(np.float32)
+        y_val = np.random.random([10, 20]).astype(np.float32)
+        def func(x, y):
+            return tf.math.less_equal(x, y, name=_TFOUTPUT), \
+                   tf.math.greater_equal(x, y, name=_TFOUTPUT1)
+        self._run_test_case(func, [_OUTPUT, _OUTPUT1], {_INPUT: x_val, _INPUT1: y_val})
 
 
 if __name__ == '__main__':

tf2onnx/onnx_opset/logical.py

@@ -121,3 +121,17 @@ def version_7(cls, ctx, node, **kwargs):
         new_node = ctx.insert_new_node_on_output("Not", output_name, name=utils.make_name(node.name))
         ctx.copy_shape(output_name, new_node.output[0])
         ctx.set_dtype(new_node.output[0], ctx.get_dtype(output_name))
+
+
+@tf_op("GreaterEqual", onnx_op="GreaterOrEqual")
+class GreaterEqual:
+    @classmethod
+    def version_12(cls, ctx, node, **kwargs):
+        pass
+
+
+@tf_op("LessEqual", onnx_op="LessOrEqual")
+class LessEqual:
+    @classmethod
+    def version_12(cls, ctx, node, **kwargs):')
+        pass

tf2onnx/onnx_opset/math.py

@@ -561,6 +561,7 @@ class SquaredDistance:
     def version_12(cls, ctx, node, **kwargs):
         node.attr["reduction"] = "none"
 
+
 @tf_op("Einsum")
 class Einsum:
     @classmethod
@@ -570,3 +571,4 @@ def version_12(cls, ctx, node, **kwargs):
 
 
 
+