support more vjp code gen (#56890)

paddle/fluid/operators/generator/tests_utils.py

@@ -86,19 +86,18 @@ def is_tensor_list(s):
     return s == 'Tensor[]'
 
 
-def exist_mutable_attribute(attrs):
-    for attr in attrs:
+def exist_mutable_attribute(attributes):
+    for attribute in attributes:
         if (
-            attr['typename'] in ['Scalar', 'IntArray']
-            and attr['support_tensor'] is True
-        ):
+            is_scalar(attribute['typename'])
+            or is_intarray(attribute['typename'])
+        ) and attribute.get('support_tensor', False):
             return True
-        else:
-            return False
+    else:
+        return False
 
 
-def is_mutable_attribute(attr):
+def is_mutable_attribute(attribute):
     return (
-        attr['typename'] in ['Scalar', 'IntArray']
-        and attr['support_tensor'] is True
-    )
+        is_scalar(attribute['typename']) or is_intarray(attribute['typename'])
+    ) and attribute.get('support_tensor', False)

paddle/fluid/primitive/codegen/gen.py

@@ -45,6 +45,22 @@ VJPS = [
     'sum_grad',
     'concat_grad',
     'split_grad',
+    'gelu_grad',
+    'softmax_grad',
+    'silu_grad',
+    'multiply_grad',
+    'subtract_grad',
+    'erf_grad',
+    'expand_grad',
+    'exp_grad',
+    'elementwise_pow_grad',
+    'fused_softmax_mask_upper_triangle_grad',
+    'matmul_grad',
+    'pow_grad',
+    'reshape_grad',
+    'rsqrt_grad',
+    'slice_grad',
+    'transpose_grad',
 ]
 VJP_COMPS = ['divide_grad', 'sum_grad']
 BACKENDS = [
@@ -68,6 +84,49 @@ BACKENDS = [
     'sum_grad',
     'concat_grad',
     'split_grad',
+    'gelu_grad',
+    'softmax_grad',
+    'silu_grad',
+    'multiply_grad',
+    'subtract_grad',
+    'erf_grad',
+    'expand_grad',
+    'exp_grad',
+    'multiply',
+    'exp',
+    'erf',
+    'cast',
+    'elementwise_pow_grad',
+    'fused_softmax_mask_upper_triangle_grad',
+    'matmul_grad',
+    'pow_grad',
+    'reshape_grad',
+    'rsqrt_grad',
+    'slice_grad',
+    'transpose_grad',
+    'subtract',
+    'assign',
+    'equal',
+    'greater_equal',
+    'greater_than',
+    'less_equal',
+    'less_than',
+    'matmul',
+    'max',
+    'maximum',
+    'minimum',
+    'not_equal',
+    'abs',
+    'bitwise_and',
+    'bitwise_not',
+    'bitwise_or',
+    'bitwise_xor',
+    'floor',
+    'gather_nd',
+    'log',
+    'roll',
+    'scatter',
+    'scatter_nd_add',
 ]
 
 
@@ -157,21 +216,6 @@ def save(content: str, path: pathlib.Path):
             print(f"Generate source file {path}")
 
 
-def filter_compat_info(items):
-    for item in items:
-        item['op'] = item['op'].split('(')[0].strip()
-        if 'backward' in item:
-            item_backwards = item['backward'].split(',')
-            for idx, item_backward in enumerate(item_backwards):
-                item_backward = item_backward.split('(')[0].strip()
-                item_backwards[idx] = item_backward
-            item['backward'] = (
-                ','.join(item_backwards)
-                if len(item_backwards) > 0
-                else item_backwards[0]
-            )
-
-
 def to_compat_dict(items: List[Dict]) -> Dict[str, Dict]:
     compat_dict = {}
     for item in items:
@@ -201,11 +245,28 @@ def get_inplace_api(apis):
     return inplace_apis
 
 
+def filter_compat_info(items):
+    for item in items:
+        item['op'] = item['op'].split('(')[0].strip()
+        if 'backward' in item:
+            item_backwards = item['backward'].split(',')
+            for idx, item_backward in enumerate(item_backwards):
+                item_backward = item_backward.split('(')[0].strip()
+                item_backwards[idx] = item_backward
+            item['backward'] = (
+                ','.join(item_backwards)
+                if len(item_backwards) > 0
+                else item_backwards[0]
+            )
+
+
 def extend_compat_info(apis, compats):
     for api in apis:
         attrs = api["attrs"]
         for attr in attrs:
-            if attr['typename'] in ["Scalar", "IntArray"]:
+            if op_gen_tests.is_scalar(
+                attr['typename']
+            ) or op_gen_tests.is_intarray(attr['typename']):
                 attr["support_tensor"] = False
     apis_dict = to_apis_dict(apis)
     for compat_item in compats:

test/prim/new_ir_prim/test_vjp_prim.py

@@ -21,7 +21,7 @@ from paddle.fluid.core import call_vjp
 paddle.enable_static()
 
 
-def get_ir_program_0():
+def get_ir_divide_program():
     main_program, start_program = (
         paddle.static.Program(),
         paddle.static.Program(),
@@ -42,7 +42,7 @@ def get_ir_program_0():
     return newir_program
 
 
-def get_ir_program_1():
+def get_ir_sum_program():
     main_program, start_program = (
         paddle.static.Program(),
         paddle.static.Program(),
@@ -61,8 +61,8 @@ def get_ir_program_1():
 
 class TestVjpPrim(unittest.TestCase):
     def test_divide_grad_prim_case1(self):
-        newir_program = get_ir_program_0()
-        paddle.fluid.core._set_prim_backward_enabled(True)
+        newir_program = get_ir_divide_program()
+        paddle.framework.core._set_prim_backward_enabled(True)
         dout = newir_program.block().ops[-2].result(0)
         out_grads = [[dout]]
         stop_gradients = [[False], [False]]
@@ -100,10 +100,11 @@ class TestVjpPrim(unittest.TestCase):
         ]
         for idx, op in enumerate(newir_program.block().ops):
             self.assertEqual(op.name(), all_op_names[idx])
+        paddle.framework.core._set_prim_backward_enabled(False)
 
     def test_divide_grad_no_prim(self):
-        newir_program = get_ir_program_0()
-        paddle.fluid.core._set_prim_backward_enabled(False)
+        newir_program = get_ir_divide_program()
+        paddle.framework.core._set_prim_backward_enabled(False)
         dout = newir_program.block().ops[-2].result(0)
         out_grads = [[dout]]
         stop_gradients = [[False], [False]]
@@ -120,8 +121,8 @@ class TestVjpPrim(unittest.TestCase):
         self.assertEqual(len(newir_program.block().ops), 5)
 
     def test_sum_grad_prim(self):
-        newir_program = get_ir_program_1()
-        paddle.fluid.core._set_prim_backward_enabled(True)
+        newir_program = get_ir_sum_program()
+        paddle.framework.core._set_prim_backward_enabled(True)
         dout = newir_program.block().ops[-3].result(0)
         out_grads = [[dout]]
         stop_gradients = [[False], [True]]
@@ -145,10 +146,11 @@ class TestVjpPrim(unittest.TestCase):
         ]
         for idx, op in enumerate(newir_program.block().ops):
             self.assertEqual(op.name(), all_op_names[idx])
+        paddle.framework.core._set_prim_backward_enabled(False)
 
     def test_sum_grad_no_prim(self):
-        newir_program = get_ir_program_1()
-        paddle.fluid.core._set_prim_backward_enabled(False)
+        newir_program = get_ir_sum_program()
+        paddle.framework.core._set_prim_backward_enabled(False)
         dout = newir_program.block().ops[-2].result(0)
         out_grads = [[dout]]
         stop_gradients = [[False], [True]]