Merge branch 'staging_optional_args' into 'staging'

made size arguments optional so they can be set from input function

See merge request ADLR/megatron-lm!53

examples/run_gpt2_eval.py

-"""
-example usage:
-python scripts/run_gpt2_eval.py \
-  --model-parallel-size 1 \
-  --num-layers 12 \
-  --hidden-size 768 \
-  --num-attention-heads 12 \
-  --model-path <gpt2_117_path> \
-  --data-path <wikitext_tokens_test_path> \
-  --batch-size 16 \
-  --cache-dir <cache dir path>
-"""
-import argparse
-import subprocess
-
-parser = argparse.ArgumentParser('run zero shot GPT2 eval')
-parser.add_argument('--model-path', type=str, required=True,
-                    help='Saved model path for evaluation')
-parser.add_argument('--batch-size', type=int, default=4,
-                    help='batch size to use for evaluation')
-parser.add_argument('--num-attention-heads', type=int, default=12,
-                    help='num of transformer attention heads')
-parser.add_argument('--hidden-size', type=int, default=768,
-                    help='tansformer hidden size')
-parser.add_argument('--num-layers', type=int, default=12,
-                    help='num decoder layers')
-parser.add_argument('--data-path', type=str, required=True,
-                    help='Data path for evaluation data')
-parser.add_argument('--cloze-eval', action='store_true',
-                    help='Run lambada cloze eval instead of perplexity eval.')
-parser.add_argument('--easy-lambada', action='store_true',
-                       help='use easier formulation of lambada')
-parser.add_argument('--model-parallel-size', type=int, default=1,
-                    help='model parallel size to use')
-args = parser.parse_args()
-
-multinode_args = ''
-if args.model_parallel_size > 1:
-    multinode_args += ' -m torch.distributed.launch --nproc_per_node {} '.format(args.model_parallel_size)
-
-CMD = ' --model-parallel-size {model_par} \
-       --num-layers {nlayers} \
-       --hidden-size {hidden} \
-       --log-interval 100 \
-       --load {model} \
-       --batch-size {batch} \
-       --num-attention-heads {natt} \
-       --seq-length 1024 \
-       --max-position-embeddings 1024 \
-       --tokenizer-type GPT2BPETokenizer \
-       --distributed-backend nccl \
-       --hidden-dropout 0.1 \
-       --attention-dropout 0.1 \
-       --fp16 \
-       --lr 1 --no-load-optim --no-load-rng --epochs 0 \
-       --overlapping-eval 32 \
-       --merge-file /home/universal-lm-data.cosmos549/repos/megatron_latest/vocab_cache/merges.txt \
-       --vocab-file /home/universal-lm-data.cosmos549/repos/megatron_latest/vocab_cache/vocab.json'.format(model_par=args.model_parallel_size,
-                                    nlayers=args.num_layers,
-                                    hidden=args.hidden_size,
-                                    model=args.model_path,
-                                    batch=args.batch_size,
-                                    natt=args.num_attention_heads,)
-
-if args.cloze_eval:
-    CMD += ' --valid-data {} '.format(args.data_path)
-    CMD += ' --task LAMBADA '
-    if not args.easy_lambada:
-      CMD += ' --strict-lambada '
-    CMD = 'main.py' + CMD
-    print('Running Lambada Eval Command:', flush=True)
-else:
-    CMD += ' --valid-data {} '.format(args.data_path)
-    CMD += ' --task WIKITEXT103 '
-    CMD = 'main.py' + CMD
-    print('Running PPL Eval Command:', flush=True)
-
-CMD = 'python3 '+multinode_args+CMD
-print(CMD, flush=True)
-
-subprocess.call(CMD.split())

megatron/arguments.py

@@ -35,8 +35,6 @@ def parse_args(extra_args_provider=None, defaults={}):
     parser = _add_validation_args(parser)
     parser = _add_data_args(parser)
     parser = _add_autoresume_args(parser)
-    # TODO: Refactor
-    parser = _add_gpt2_args(parser)
 
     # Custom arguments.
     if extra_args_provider is not None:
@@ -54,6 +52,12 @@ def parse_args(extra_args_provider=None, defaults={}):
             'defaults can only be overwritten for args with None values.'
         setattr(args, key, defaults[key])
 
+    # Check required arguments.
+    required_args = ['num_layers', 'hidden_size', 'num_attention_heads',
+                     'max_position_embeddings']
+    for req_arg in required_args: 
+        _check_arg_is_not_none(args, req_arg)
+
     # Distributed args.
     args.rank = int(os.getenv('RANK', '0'))
     args.world_size = int(os.getenv("WORLD_SIZE", '1'))
@@ -93,16 +97,20 @@ def _print_args(args):
         print('---------------- end of arguments ----------------', flush=True)
 
 
+def _check_arg_is_not_none(args, arg):
+    assert getattr(args, arg) is not None, '{} argument is None'.format(arg)
+
+
 def _add_network_size_args(parser):
     group = parser.add_argument_group(title='network size')
 
-    group.add_argument('--num-layers', type=int, required=True,
+    group.add_argument('--num-layers', type=int, default=None,
                        help='Number of transformer layers.')
-    group.add_argument('--hidden-size', type=int, required=True,
+    group.add_argument('--hidden-size', type=int, default=None,
                        help='Tansformer hidden size.')
-    group.add_argument('--num-attention-heads', type=int, required=True,
+    group.add_argument('--num-attention-heads', type=int, default=None,
                        help='Number of transformer attention heads.')
-    group.add_argument('--max-position-embeddings', type=int, required=True,
+    group.add_argument('--max-position-embeddings', type=int, default=None,
                        help='Maximum number of position embeddings to use. '
                        'This is the size of position embedding.')
     group.add_argument('--make-vocab-size-divisible-by', type=int, default=128,
@@ -342,28 +350,3 @@ def _add_autoresume_args(parser):
                        'termination signal')
 
     return parser
-
-
-########################################################################
-
-
-def _add_gpt2_args(parser):
-    group = parser.add_argument_group(title='gpt2')
-
-    group.add_argument('--input-data-sizes-file', type=str, default='sizes.txt',
-                       help='The filename containing all the shards '
-                       'sizes for numpy data loader')
-
-    return parser
-
-
-def add_data_args_(parser):
-    """Train/valid/test data arguments."""
-
-    group = parser.add_argument_group('data', 'data configurations')
-
-    group.add_argument('--data-loader', type=str, default=None,
-                       choices=['raw', 'lazy', 'tfrecords', 'numpy', 'binary'],
-                       help='Which data loader to use. Default varies by model.')
-
-    return parser