Check -1 shape for input_spec and program when prim or cinn enabled (#…

…50473)

* Check -1 shape for input_spec and program when prim or cinn enabled

* Polish neg shape check

* Polish code

* Fix UT

* Fix UT in static

python/paddle/fluid/tests/unittests/test_input_spec.py

@@ -20,6 +20,7 @@
 
 import paddle
 import paddle.fluid as fluid
+from paddle.fluid import core
 from paddle.fluid.framework import convert_np_dtype_to_dtype_
 from paddle.jit.dy2static.utils import _compatible_non_tensor_spec
 from paddle.static import InputSpec
@@ -331,5 +332,32 @@ def test_case(self):
         )
 
 
+class NegSpecNet(paddle.nn.Layer):
+    def __init__(self):
+        super().__init__()
+        self.linear = paddle.nn.Linear(10, 5)
+
+    def forward(self, x):
+        return self.linear(x)
+
+
+class TestNegSpecWithPrim(unittest.TestCase):
+    def setUp(self):
+        paddle.disable_static()
+        core._set_prim_all_enabled(True)
+
+    def tearDown(self):
+        core._set_prim_all_enabled(False)
+
+    def test_run(self):
+        net = NegSpecNet()
+        net = paddle.jit.to_static(
+            net, input_spec=[paddle.static.InputSpec(shape=[-1, 10])]
+        )
+        x = paddle.randn([2, 10])
+        out = net(x)
+        np.testing.assert_equal(out.shape, [2, 5])
+
+
 if __name__ == '__main__':
     unittest.main()

python/paddle/jit/dy2static/partial_program.py

@@ -1069,32 +1069,6 @@ def _valid_vars(self, vars):
         return vars if vars else None
 
 
-def _create_fake_var():
-    """
-    Create a fake_var (force on CPU) to handle empty input or output
-    """
-    if not framework.global_var._in_eager_mode_:
-        return [
-            core.VarBase(
-                core.VarDesc.VarType.FP32,
-                [],
-                "Fake_var",
-                core.VarDesc.VarType.RAW,
-                False,
-            )
-        ]
-    else:
-        return [
-            core.eager.Tensor(
-                core.VarDesc.VarType.FP32,
-                [],
-                "Fake_var",
-                core.VarDesc.VarType.RAW,
-                False,
-            )
-        ]
-
-
 def partial_program_from(concrete_program):
     inputs = concrete_program.inputs
     if inputs and isinstance(inputs[0], layers.Layer):

python/paddle/jit/dy2static/program_translator.py

@@ -48,6 +48,7 @@
     func_to_source_code,
     input_specs_compatible,
     make_hashable,
+    prim_or_cinn_is_enabled,
     type_name,
     unwrap,
 )
@@ -320,6 +321,17 @@ def __init__(self, function, input_spec=None, **kwargs):
             self._dygraph_function = function
             self._class_instance = None
 
+        if input_spec is not None and prim_or_cinn_is_enabled(
+            kwargs.get("build_strategy", None)
+        ):
+            for spec in input_spec:
+                if spec is not None and -1 in spec.shape:
+                    input_spec = None
+                    warnings.warn(
+                        'Now prim and cinn do not support -1 shape, but input_spec has -1 shape so we set it to None.'
+                    )
+                    break
+
         self._input_spec = input_spec
         self._function_spec = FunctionSpec(function, input_spec)
         self._program_cache = ProgramCache()
@@ -1046,17 +1058,6 @@ def from_func_spec(
         )
 
 
-def _extract_indeed_params_buffers(class_instance):
-    """
-    To filter not initialzed buffers.
-    """
-    params = list(get_parameters(class_instance).values())
-    buffers = list(get_buffers(class_instance).values())
-    buffers = [buffer for buffer in buffers if len(buffer.shape) != 0]
-
-    return params + buffers
-
-
 class ParametersRecorder:
     def __init__(self):
         self.params_dict = {}
@@ -1177,6 +1178,15 @@ def _build_once(self, cache_key):
             else:
                 raise
 
+        if prim_or_cinn_is_enabled(cache_key.kwargs['build_strategy']):
+            for var in concrete_program.main_program.list_vars():
+                if -1 in var.shape:
+                    warnings.warn(
+                        "Now prim and cinn do not support -1 shape, but the shape of var {} is {}".format(
+                            var.name, var.shape
+                        )
+                    )
+
         concrete_program._to_prim()
         return concrete_program, partial_program_from(concrete_program)
 

python/paddle/jit/dy2static/utils.py

@@ -1493,7 +1493,7 @@ def _param_grad_names(program_desc, params):
     Parse PARAM@GARD name from original train and infer program.
     """
     names = []
-    # NOTE: `names` and `self._params` must be in the same order so that
+    # NOTE: `names` and `params` must be in the same order so that
     # the param grad name can be set correctly in the run_program.
     for param in params:
         candidate = [
@@ -1523,3 +1523,25 @@ def _out_grad_names(program_desc, fwd_end_op_index, out_size):
             var_name = op.output('Out')[0]
             names.append(var_name)
     return names
+
+
+def prim_or_cinn_is_enabled(build_strategy):
+    if build_strategy is not None and build_strategy.build_cinn_pass:
+        return True
+
+    if core._is_bwd_prim_enabled() or core._is_fwd_prim_enabled():
+        return True
+
+    env_flags = [
+        'FLAGS_prim_forward',
+        'FLAGS_prim_backward',
+        'FLAGS_prim_all',
+        'FLAGS_use_cinn',
+    ]
+    for flag in env_flags:
+        value = os.getenv(flag)
+        if value is None:
+            continue
+        elif value.lower() in ['true', '1']:
+            return True
+    return False