Add support for sharing params of operators in tensorflow frontend (#5042)

python/tvm/relay/frontend/tensorflow.py

@@ -81,7 +81,7 @@ def _dimension_constraint():
 def _get_param(params, input_node):
     if isinstance(input_node, _expr.Constant):
         return np.atleast_1d(input_node.data.asnumpy())
-    return params.pop(input_node.name_hint).asnumpy()
+    return params[input_node.name_hint].asnumpy()
 
 def _get_num_param(params, input_node):
     return _get_param(params, input_node).item()

tests/python/frontend/tensorflow/test_forward.py

@@ -3058,6 +3058,21 @@ def test_forward_add_n():
     _test_forward_add_n(in4)
     _test_forward_add_n(in5)
 
+#######################################################################
+# Sharing params case
+# ----------------------
+
+
+def test_sharing_node():
+    """Test the sharing params case."""
+    np_data = np.random.uniform(size=(2,2,2)).astype('float32')
+    with tf.Graph().as_default():
+        in_data = tf.placeholder(tf.float32, shape=(2, 2, 2), name='in_data')
+        axis = tf.constant([-1], dtype=tf.int32, name='axis')
+        mean0 = tf.reduce_mean(in_data, axis=axis, keepdims=False, name='mean0')
+        mean1 = tf.reduce_mean(in_data, axis=axis, keepdims=False, name='mean1')
+        out = tf.add(mean0, mean1, name='out')
+        compare_tf_with_tvm([np_data], ['in_data:0'], 'out:0')
 
 #######################################################################
 # Unravel Index
@@ -3311,3 +3326,6 @@ if __name__ == '__main__':
 
     # Internal misc. ops
     test_read_variable_op()
+
+    # Sharing params case using Mean ops
+    test_sharing_node()