delete transmission args in linear_chain_crf op (#19619)

* delete args on linear_chain_crf_op doc

* delete args on linear_chain_crf_op doc

* delete args on linear_chain_crf_op doc

* add code example

* fix api doc

* fix doc of crf

* fix doc of crf

* add test=develop

* modify API.spec, test=develop

paddle/fluid/API.spec

@@ -115,7 +115,7 @@ paddle.fluid.layers.dynamic_lstm (ArgSpec(args=['input', 'size', 'h_0', 'c_0', '
 paddle.fluid.layers.dynamic_lstmp (ArgSpec(args=['input', 'size', 'proj_size', 'param_attr', 'bias_attr', 'use_peepholes', 'is_reverse', 'gate_activation', 'cell_activation', 'candidate_activation', 'proj_activation', 'dtype', 'name', 'h_0', 'c_0', 'cell_clip', 'proj_clip'], varargs=None, keywords=None, defaults=(None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'tanh', 'float32', None, None, None, None, None)), ('document', 'c37d51aad655c8a9f9b045c64717320a'))
 paddle.fluid.layers.dynamic_gru (ArgSpec(args=['input', 'size', 'param_attr', 'bias_attr', 'is_reverse', 'gate_activation', 'candidate_activation', 'h_0', 'origin_mode'], varargs=None, keywords=None, defaults=(None, None, False, 'sigmoid', 'tanh', None, False)), ('document', '83617c165827e030636c80486d5de6f3'))
 paddle.fluid.layers.gru_unit (ArgSpec(args=['input', 'hidden', 'size', 'param_attr', 'bias_attr', 'activation', 'gate_activation', 'origin_mode'], varargs=None, keywords=None, defaults=(None, None, 'tanh', 'sigmoid', False)), ('document', '33974b9bfa69f2f1eb85e6f956dff04e'))
-paddle.fluid.layers.linear_chain_crf (ArgSpec(args=['input', 'label', 'param_attr', 'length'], varargs=None, keywords=None, defaults=(None, None)), ('document', '715f8f12d68ae90504a7b768e82be6f4'))
+paddle.fluid.layers.linear_chain_crf (ArgSpec(args=['input', 'label', 'param_attr', 'length'], varargs=None, keywords=None, defaults=(None, None)), ('document', '9045b8971e4232132ec9952695f4c3ae'))
 paddle.fluid.layers.crf_decoding (ArgSpec(args=['input', 'param_attr', 'label'], varargs=None, keywords=None, defaults=(None,)), ('document', '5ce117258e243be1c81539e254178d90'))
 paddle.fluid.layers.cos_sim (ArgSpec(args=['X', 'Y'], varargs=None, keywords=None, defaults=None), ('document', '8e6ce424cf9e261ef32ee229c06a6e66'))
 paddle.fluid.layers.cross_entropy (ArgSpec(args=['input', 'label', 'soft_label', 'ignore_index'], varargs=None, keywords=None, defaults=(False, -100)), ('document', 'f43c659ca1749a3f0ff2231e6dfda07d'))

python/paddle/fluid/layers/nn.py

@@ -1414,10 +1414,9 @@ def linear_chain_crf(input, label, param_attr=None, length=None):
 
     Args:
         input(${emission_type}): ${emission_comment}
-        input(${transition_type}): ${transition_comment}
         label(${label_type}): ${label_comment}
         Length(${length_type}): ${length_comment}
-        param_attr(ParamAttr): The attribute of the learnable parameter.
+        param_attr(ParamAttr): The attribute of the learnable parameter for transition parameter.
 
     Returns:
         output(${emission_exps_type}): ${emission_exps_comment} \n
@@ -1483,6 +1482,10 @@ def linear_chain_crf(input, label, param_attr=None, length=None):
 
             loss2= exe.run(train_program,feed=feed2, fetch_list=[crf_cost2])
             print(loss2) 
+            
+            #you can use find_var to get transition parameter.
+            transition=np.array(fluid.global_scope().find_var('crfw').get_tensor())
+            print(transition)
     """
     helper = LayerHelper('linear_chain_crf', **locals())
     size = input.shape[1]