[Dy2Stat]Allow ifelse return buildin type in paddle cond (PaddlePaddl…

…e#37888)

* allow ifelse return `int` in paddle cond

* add test and refine code

* polish code, add test

* code format

python/paddle/fluid/dygraph/dygraph_to_static/convert_operators.py

@@ -248,20 +248,6 @@ def _remove_no_value_return_var(out):
 
 def _run_paddle_cond(pred, true_fn, false_fn, true_args, false_args,
                      return_vars):
-
-    return_var_ids = [id(var) for var in return_vars]
-    # NOTE 1: Returned vars of Paddle op `control_flow.cond` must be Paddle Tensors
-    # NOTE 2: Here uses id(var) not var, because `if var in return_var` use operator `==`,
-    #  which will call `fluid.layers.equal` and causes error when var in return_vars is not initialized.
-    true_args = [
-        to_static_variable(var) if id(var) in return_var_ids else var
-        for var in true_args
-    ]
-    false_args = [
-        to_static_variable(var) if id(var) in return_var_ids else var
-        for var in false_args
-    ]
-
     pred = cast_bool_if_necessary(pred)
     return control_flow.cond(pred, lambda: true_fn(*true_args),
                              lambda: false_fn(*false_args))

python/paddle/fluid/layers/control_flow.py

@@ -102,6 +102,41 @@ def select_input(inputs, mask):
     return out
 
 
+def select_input_with_buildin_type(inputs, mask):
+    from paddle.fluid.dygraph.dygraph_to_static.variable_trans_func import to_static_variable
+    support_ret_buildin_type = (bool, float, six.integer_types)
+    false_var, true_var = inputs
+
+    if isinstance(false_var, Variable) and isinstance(true_var, Variable):
+        return select_input(inputs, mask)
+
+    elif (isinstance(false_var, (support_ret_buildin_type)) and
+          isinstance(false_var, type(true_var))):
+        if false_var == true_var:
+            return false_var
+        else:
+            inputs = [
+                to_static_variable(false_var), to_static_variable(true_var)
+            ]
+    # Deal with the situations like this: false_var is int and true_var is Variable
+    elif ((isinstance(false_var, support_ret_buildin_type) and
+           isinstance(true_var, Variable)) or
+          (isinstance(true_var, support_ret_buildin_type) and
+           isinstance(false_var, Variable))):
+        inputs = [to_static_variable(false_var), to_static_variable(true_var)]
+        warnings.warn(
+            "Return results from different branches in cond are not same type: "
+            "false_var returned by fasle_fn is '{}' and true_var of true_fn is "
+            "'{}'".format(type(false_var), type(true_var)))
+    else:
+        raise TypeError(
+            "Unsupported return type of true_fn and false_fn in cond: false_var "
+            "returned by fasle_fn is '{}' and true_var of true_fn is '{}'".
+            format(type(false_var), type(true_var)))
+
+    return select_input(inputs, mask)
+
+
 def split_lod_tensor(input, mask, level=0):
     """
     This function takes in an input that contains the complete lod information,
@@ -2282,8 +2317,8 @@ def append_conditional_block_grad(self, parent_block, inside_block,
 
 
 def copy_var_to_parent_block(var, layer_helper):
-    if var is None:
-        return None
+    if not isinstance(var, Variable):
+        return var
     prog = layer_helper.main_program
     parent_idx = prog.current_block().parent_idx
     assert parent_idx >= 0, "Got wrong parent block index when assigning var to parent scope in control_flow"
@@ -2466,7 +2501,7 @@ def false_func():
             format(e))
 
     mask = cast(pred, dtype='int32')
-    merge_func = lambda false_var, true_var : select_input([false_var, true_var], mask)
+    merge_func = lambda false_var, true_var : select_input_with_buildin_type([false_var, true_var], mask)
     merged_output = map_structure(merge_func, false_output, true_output)
     return merged_output
 

python/paddle/fluid/tests/unittests/dygraph_to_static/ifelse_simple_func.py

@@ -341,3 +341,53 @@ def if_tensor_case(x):
         x += 1
 
     return x
+
+
+def dyfunc_ifelse_ret_int1(x):
+    index = 0
+    pred = paddle.to_tensor([1])
+    if pred:
+        y = x[index] + 1
+        index = index + 1
+        return y, index
+    else:
+        y = x[index] + 2
+        index = index + 1
+        return y, index
+
+
+def dyfunc_ifelse_ret_int2(x):
+    index = 0
+    pred = paddle.to_tensor([1])
+    if pred:
+        y = x[index] + 1
+        index = index + 1
+        return y, index
+    else:
+        y = x[index] + 2
+        index = index + 1
+        return y
+
+
+def dyfunc_ifelse_ret_int3(x):
+    index = 0
+    pred = paddle.to_tensor([1])
+    if pred:
+        y = x[index] + 1
+        index = index + 1
+        return index
+    else:
+        y = x[index] + 2
+        return y
+
+
+def dyfunc_ifelse_ret_int4(x):
+    index = 0
+    pred = paddle.to_tensor([1])
+    if pred:
+        y = x[index] + 1
+        index = index + 1
+        return 'unsupport ret'
+    else:
+        y = x[index] + 2
+        return y