copy test_dynamic_model

config.json

@@ -0,0 +1,30 @@
+{
+  "_name_or_path": "hf-internal-testing/tiny-bert",
+  "architectures": [
+    "NewModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "auto_map": {
+    "AutoConfig": "configuration.NewModelConfig",
+    "AutoModel": "modeling.NewModel"
+  },
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 128,
+  "initializer_range": 0.02,
+  "intermediate_size": 512,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "new-model",
+  "new_hidden_size": 12,
+  "num_attention_heads": 2,
+  "num_hidden_layers": 2,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.16.0.dev0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

configuration.py

@@ -0,0 +1,9 @@
+
+from transformers import BertConfig
+
+class NewModelConfig(BertConfig):
+    model_type = "new-model"
+    
+    def __init__(self, *args, new_hidden_size=12, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.new_hidden_size = new_hidden_size

modeling.py

@@ -0,0 +1,11 @@
+import torch
+from transformers import BertModel
+
+from .configuration import NewModelConfig
+
+class NewModel(BertModel):
+    config_class = NewModelConfig
+
+    def __init__(self, config):
+        super().__init__(config)
+        self.last_layer = torch.nn.Linear(config.hidden_size, config.new_hidden_size)

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:abe537dcbbc0a24d9d81979744669d1f8d7adca535f81cb76f68c42b3fe18ace
+size 17568615