modify uncorrect name

model_zoo/official/nlp/gnmt_v2/src/gnmt_model/attention.py

@@ -115,7 +115,7 @@ class BahdanauAttention(nn.Cell):
         if self.is_training:
             query_trans = self.cast(query_trans, mstype.float16)
         processed_query = self.linear_q(query_trans)
-        if self.is_trining:
+        if self.is_training:
             processed_query = self.cast(processed_query, mstype.float32)
         processed_query = self.reshape(processed_query, (batch_size, t_q_length, self.num_units))
         # (N, t_k_length, D)
@@ -123,7 +123,7 @@ class BahdanauAttention(nn.Cell):
         if self.is_training:
             keys = self.cast(keys, mstype.float16)
         processed_key = self.linear_k(keys)
-        if self.is_trining:
+        if self.is_training:
             processed_key = self.cast(processed_key, mstype.float32)
         processed_key = self.reshape(processed_key, (batch_size, t_k_length, self.num_units))
 

model_zoo/official/nlp/gnmt_v2/src/gnmt_model/beam_search.py

@@ -219,7 +219,7 @@ class BeamSearchDecoder(nn.Cell):
         self.start_ids = Tensor(np.full([batch_size * beam_width, 1], sos_id), mstype.int32)
         if self.is_using_while:
             self.start = Tensor(0, dtype=mstype.int32)
-            self.init_seq = Tensor(np.full([batch_size, beam_width, self.max_decode_length], sos_id),
+            self.init_seq = Tensor(np.full([batch_size, beam_width, self.max_decode_length + 1], sos_id),
                                    mstype.int32)
         else:
             self.init_seq = Tensor(np.full([batch_size, beam_width, 1], sos_id), mstype.int32)
@@ -402,7 +402,7 @@ class BeamSearchDecoder(nn.Cell):
         accu_attn_scores = self.accu_attn_scores
 
         if not self.is_using_while:
-            for _ in range(self.max_decode_length + 1):
+            for _ in range(self.max_decode_length):
                 cur_input_ids, state_log_probs, state_seq, state_length, decoder_hidden_state, accu_attn_scores, \
                 state_finished = self.one_step(cur_input_ids, enc_states, enc_attention_mask, state_log_probs,
                                                state_seq, state_length, None, decoder_hidden_state, accu_attn_scores,