add hub config for bert base and nezha

model_zoo/official/nlp/bert/mindspore_hub_conf.py

@@ -0,0 +1,77 @@
+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+'''
+Bert hub interface for bert base and bert nezha
+'''
+from src.bert_model import BertModel
+from src.bert_model import BertConfig
+import mindspore.common.dtype as mstype
+bert_net_cfg_base = BertConfig(
+    batch_size=32,
+    seq_length=128,
+    vocab_size=21128,
+    hidden_size=768,
+    num_hidden_layers=12,
+    num_attention_heads=12,
+    intermediate_size=3072,
+    hidden_act="gelu",
+    hidden_dropout_prob=0.1,
+    attention_probs_dropout_prob=0.1,
+    max_position_embeddings=512,
+    type_vocab_size=2,
+    initializer_range=0.02,
+    use_relative_positions=False,
+    input_mask_from_dataset=True,
+    token_type_ids_from_dataset=True,
+    dtype=mstype.float32,
+    compute_type=mstype.float16
+)
+bert_net_cfg_nezha = BertConfig(
+    batch_size=32,
+    seq_length=128,
+    vocab_size=21128,
+    hidden_size=1024,
+    num_hidden_layers=24,
+    num_attention_heads=16,
+    intermediate_size=4096,
+    hidden_act="gelu",
+    hidden_dropout_prob=0.1,
+    attention_probs_dropout_prob=0.1,
+    max_position_embeddings=512,
+    type_vocab_size=2,
+    initializer_range=0.02,
+    use_relative_positions=True,
+    input_mask_from_dataset=True,
+    token_type_ids_from_dataset=True,
+    dtype=mstype.float32,
+    compute_type=mstype.float16
+)
+def create_network(name, *args, **kwargs):
+    '''
+    Create bert network for base and nezha.
+    '''
+    if name == 'bert_base':
+        if "batch_size" in kwargs:
+            bert_net_cfg_base.batch_size = kwargs["batch_size"]
+        if "seq_length" in kwargs:
+            bert_net_cfg_base.seq_length = kwargs["seq_length"]
+        return BertModel(bert_net_cfg_base, *args)
+    if name == 'bert_nezha':
+        if "batch_size" in kwargs:
+            bert_net_cfg_nezha.batch_size = kwargs["batch_size"]
+        if "seq_length" in kwargs:
+            bert_net_cfg_nezha.seq_length = kwargs["seq_length"]
+        return BertModel(bert_net_cfg_nezha, *args)
+    raise NotImplementedError(f"{name} is not implemented in the repo")