Refine test_lac.py for eager mode (#40951)

* Refine test_lac.py for eager mode

* refine code

* Fix test_program_translator for eager

paddle/fluid/pybind/op_function_generator.h

@@ -98,6 +98,9 @@ std::map<std::string, std::set<std::string>> op_ins_map = {
       "CustomDistAlias", "CustomDistAliasProbs"}},
     {"check_finite_and_unscale", {"X", "Scale", "FloatStatus"}},
     {"group_norm", {"X", "Scale", "Bias"}},
+    {"linear_chain_crf", {"Emission", "Transition", "Label", "Length"}},
+    {"crf_decoding", {"Emission", "Transition", "Label", "Length"}},
+    {"chunk_eval", {"Inference", "Label", "SeqLength"}},
 };
 
 // NOTE(zhiqiu): Like op_ins_map.

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

@@ -27,6 +27,8 @@ from paddle.fluid.dygraph import to_variable
 from paddle.fluid.dygraph import Embedding, Linear, GRUUnit
 from paddle.fluid.dygraph import declarative, ProgramTranslator
 from paddle.fluid.dygraph.io import INFER_MODEL_SUFFIX, INFER_PARAMS_SUFFIX
+from paddle.fluid.framework import _non_static_mode
+from paddle import _C_ops
 
 SEED = 2020
 
@@ -167,6 +169,11 @@ class LinearChainCRF(fluid.dygraph.Layer):
         self._transition = value
 
     def forward(self, input, label, length=None):
+        if _non_static_mode():
+            _, _, _, log_likelihood = _C_ops.linear_chain_crf(
+                input, self._transition, label, length, "is_test",
+                self._is_test)
+            return log_likelihood
 
         alpha = self._helper.create_variable_for_type_inference(
             dtype=self._dtype)
@@ -218,6 +225,9 @@ class CRFDecoding(fluid.dygraph.Layer):
         self._transition = value
 
     def forward(self, input, label=None, length=None):
+        if _non_static_mode():
+            return _C_ops.crf_decoding(input, self._transition, label, length,
+                                       "is_test", self._is_test)
 
         viterbi_path = self._helper.create_variable_for_type_inference(
             dtype=self._dtype)
@@ -245,6 +255,11 @@ class ChunkEval(fluid.dygraph.Layer):
         self.excluded_chunk_types = excluded_chunk_types
 
     def forward(self, input, label, seq_length=None):
+        if _non_static_mode():
+            return _C_ops.chunk_eval(
+                input, label, seq_length, "num_chunk_types",
+                self.num_chunk_types, "chunk_scheme", self.chunk_scheme,
+                "excluded_chunk_types", self.excluded_chunk_types or [])
 
         precision = self._helper.create_variable_for_type_inference(
             dtype="float32")

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

@@ -232,7 +232,9 @@ class TestEnableDeclarative(unittest.TestCase):
             dygraph_func = self.program_translator.get_func(simple_func)
             self.assertTrue(callable(dygraph_func))
             dygraph_output = dygraph_func(self.x, self.weight)
-            self.assertTrue(isinstance(dygraph_output, fluid.core.VarBase))
+            self.assertTrue(
+                isinstance(dygraph_output, (fluid.core.VarBase,
+                                            fluid.core.eager.Tensor)))
 
     def test_enable_disable_get_program(self):
 
@@ -254,7 +256,9 @@ class TestEnableDeclarative(unittest.TestCase):
         with fluid.dygraph.guard():
             dygraph_output = self.program_translator.get_program(
                 simple_func, self.x, self.weight)
-            self.assertTrue(isinstance(dygraph_output, fluid.core.VarBase))
+            self.assertTrue(
+                isinstance(dygraph_output, (fluid.core.VarBase,
+                                            fluid.core.eager.Tensor)))
 
     def test_enable_disable_declarative(self):