Add 1M train step model

config.json

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+{
+  "architectures": [
+    "ElectraForPreTraining"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "embedding_size": 768,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "electra",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "summary_activation": "gelu",
+  "summary_last_dropout": 0.1,
+  "summary_type": "first",
+  "summary_use_proj": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.17.0.dev0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 50265
+}

events.out.tfevents.1644944635.t1v-n-9798b699-w-0

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6effde0ada817c9f414976dd5ecc00424fa01a6891938084c148f735ab06c7b7
+size 31594395

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:624ae7c30d4b5cb961bc5b16849a19dcb607ed3486a97b1b6b653aec80447c64
+size 498665133

tf_rename_checkpoint_variables.py

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+# Adapted from https://gist.github.com/qqaatw/82b47c2b3da602fa1df604167bfcb9b0
+
+import getopt
+import sys
+import re
+
+import tensorflow.compat.v1 as tf
+
+
+usage_str = ('python tensorflow_rename_variables.py '
+             '--checkpoint_dir=path/to/dir/ --replace_from=substr '
+             '--replace_to=substr --add_prefix=abc --dry_run')
+find_usage_str = ('python tensorflow_rename_variables.py '
+                  '--checkpoint_dir=path/to/dir/ --find_str=[\'!\']substr')
+comp_usage_str = ('python tensorflow_rename_variables.py '
+                  '--checkpoint_dir=path/to/dir/ '
+                  '--checkpoint_dir2=path/to/dir/')
+
+
+def print_usage_str():
+    print('Please specify a checkpoint_dir. Usage:')
+    print('%s\nor\n%s\nor\n%s' % (usage_str, find_usage_str, comp_usage_str))
+    print('Note: checkpoint_dir should be a *DIR*, not a file')
+
+
+def compare(checkpoint_dir, checkpoint_dir2):
+    import difflib
+    with tf.Session():
+        list1 = [el1 for (el1, el2) in
+                 tf.train.list_variables(checkpoint_dir)]
+        list2 = [el1 for (el1, el2) in
+                 tf.train.list_variables(checkpoint_dir2)]
+        for k1 in list1:
+            if k1 in list2:
+                continue
+            else:
+                print('{} close matches: {}'.format(
+                    k1, difflib.get_close_matches(k1, list2)))
+
+
+def find(checkpoint_dir, find_str):
+    with tf.Session():
+        negate = find_str.startswith('!')
+        if negate:
+            find_str = find_str[1:]
+        for var_name, _ in tf.train.list_variables(checkpoint_dir):
+            if negate and find_str not in var_name:
+                print('%s missing from %s.' % (find_str, var_name))
+            if not negate and find_str in var_name:
+                print('Found %s in %s.' % (find_str, var_name))
+
+
+def rename(checkpoint_dir, replace_from, replace_to, add_prefix, dry_run):
+    checkpoint = tf.train.get_checkpoint_state(checkpoint_dir)
+    print('print: ', checkpoint)
+    with tf.Session() as sess:
+        for var_name, _ in tf.train.list_variables(checkpoint_dir):
+            # Load the variable
+    
+            var= tf.train.load_variable(checkpoint_dir, var_name)
+
+            # Set the new name
+            if None not in [replace_from, replace_to]:
+                new_name = re.sub(replace_from, replace_to, var_name)
+                if add_prefix:
+                    new_name = add_prefix + new_name
+                if dry_run:
+                    print('%s would be renamed to %s.' % (var_name,
+                                                            new_name))
+                else:
+                    if var_name != new_name:
+                        print('Renaming %s to %s.' % (var_name, new_name))
+                # Create the variable, potentially renaming it
+                var = tf.Variable(var, name=new_name)
+
+        if not dry_run:
+            # Save the variables
+            saver = tf.train.Saver()
+            sess.run(tf.global_variables_initializer())
+            #saver.save(sess, checkpoint.model_checkpoint_path)
+            saver.save(sess, "renamed-model.ckpt")
+
+
+def main(argv):
+    checkpoint_dir = None
+    checkpoint_dir2 = None
+    replace_from = None
+    replace_to = None
+    add_prefix = None
+    dry_run = False
+    find_str = None
+
+    try:
+        opts, args = getopt.getopt(argv, 'h', ['help=', 'checkpoint_dir=',
+                                               'replace_from=', 'replace_to=',
+                                               'add_prefix=', 'dry_run',
+                                               'find_str=',
+                                               'checkpoint_dir2='])
+    except getopt.GetoptError as e:
+        print(e)
+        print_usage_str()
+        sys.exit(2)
+    for opt, arg in opts:
+        if opt in ('-h', '--help'):
+            print(usage_str)
+            sys.exit()
+        elif opt == '--checkpoint_dir':
+            checkpoint_dir = arg
+        elif opt == '--checkpoint_dir2':
+            checkpoint_dir2 = arg
+        elif opt == '--replace_from':
+            replace_from = arg
+        elif opt == '--replace_to':
+            replace_to = arg
+        elif opt == '--add_prefix':
+            add_prefix = arg
+        elif opt == '--dry_run':
+            dry_run = True
+        elif opt == '--find_str':
+            find_str = arg
+
+    if not checkpoint_dir:
+        print_usage_str()
+        sys.exit(2)
+
+    if checkpoint_dir2:
+        compare(checkpoint_dir, checkpoint_dir2)
+    elif find_str:
+        find(checkpoint_dir, find_str)
+    else:
+        rename(checkpoint_dir, replace_from, replace_to, add_prefix, dry_run)
+
+
+if __name__ == '__main__':
+    main(sys.argv[1:])