adding more tests on TF and pytorch serialization - updating configuration for better serialization

transformers/modeling_tf_gpt2.py

@@ -32,7 +32,6 @@ from .modeling_tf_utils import (TFPreTrainedModel, TFConv1D, TFSharedEmbeddings,
                                 TFSequenceSummary, shape_list, get_initializer)
 from .configuration_gpt2 import GPT2Config
 from .file_utils import add_start_docstrings
-from .modeling_tf_pytorch_utils import load_pytorch_checkpoint_in_tf2_model
 
 logger = logging.getLogger(__name__)
 
@@ -42,14 +41,6 @@ TF_GPT2_PRETRAINED_MODEL_ARCHIVE_MAP = {"gpt2": "https://s3.amazonaws.com/models
                                      "distilgpt2": "https://s3.amazonaws.com/models.huggingface.co/bert/distilgpt2-tf_model.h5",}
 
 
-def load_gpt2_pt_weights_in_tf2(tf_model, pytorch_checkpoint_path):
-    # build the network
-    inputs_list = [[7, 6, 0, 0, 1], [1, 2, 3, 0, 0], [0, 0, 0, 4, 5]]
-    tf_inputs = tf.constant(inputs_list)
-    tfo = tf_model(tf_inputs, training=False)
-    return load_pytorch_checkpoint_in_tf2_model(tf_model, pytorch_checkpoint_path, tf_inputs=tf_inputs)
-
-
 def gelu(x):
     """Gaussian Error Linear Unit.
     This is a smoother version of the RELU.
@@ -350,7 +341,6 @@ class TFGPT2PreTrainedModel(TFPreTrainedModel):
     """
     config_class = GPT2Config
     pretrained_model_archive_map = TF_GPT2_PRETRAINED_MODEL_ARCHIVE_MAP
-    load_pt_weights = load_gpt2_pt_weights_in_tf2
     base_model_prefix = "transformer"