diff --git a/examples/extract_features.py b/examples/extract_features.py index 4f8812121e..9d05d7905d 100644 --- a/examples/extract_features.py +++ b/examples/extract_features.py @@ -199,7 +199,7 @@ def main(): "bert-large-uncased, bert-base-cased, bert-base-multilingual, bert-base-chinese.") ## Other parameters - parser.add_argument("--do_lower_case", default=False, action='store_true', help="Set this flag if you are using an uncased model.") + parser.add_argument("--do_lower_case", action='store_true', help="Set this flag if you are using an uncased model.") parser.add_argument("--layers", default="-1,-2,-3,-4", type=str) parser.add_argument("--max_seq_length", default=128, type=int, help="The maximum total input sequence length after WordPiece tokenization. Sequences longer " @@ -210,7 +210,6 @@ def main(): default=-1, help = "local_rank for distributed training on gpus") parser.add_argument("--no_cuda", - default=False, action='store_true', help="Whether not to use CUDA when available") diff --git a/examples/run_classifier.py b/examples/run_classifier.py index 0afd443402..31877a5414 100644 --- a/examples/run_classifier.py +++ b/examples/run_classifier.py @@ -333,15 +333,12 @@ def main(): "Sequences longer than this will be truncated, and sequences shorter \n" "than this will be padded.") parser.add_argument("--do_train", - default=False, action='store_true', help="Whether to run training.") parser.add_argument("--do_eval", - default=False, action='store_true', help="Whether to run eval on the dev set.") parser.add_argument("--do_lower_case", - default=False, action='store_true', help="Set this flag if you are using an uncased model.") parser.add_argument("--train_batch_size", @@ -366,7 +363,6 @@ def main(): help="Proportion of training to perform linear learning rate warmup for. " "E.g., 0.1 = 10%% of training.") parser.add_argument("--no_cuda", - default=False, action='store_true', help="Whether not to use CUDA when available") parser.add_argument("--local_rank", @@ -382,7 +378,6 @@ def main(): default=1, help="Number of updates steps to accumulate before performing a backward/update pass.") parser.add_argument('--fp16', - default=False, action='store_true', help="Whether to use 16-bit float precision instead of 32-bit") parser.add_argument('--loss_scale', diff --git a/examples/run_lm_finetuning.py b/examples/run_lm_finetuning.py index 9ca9830eff..2c64f67b5f 100644 --- a/examples/run_lm_finetuning.py +++ b/examples/run_lm_finetuning.py @@ -432,7 +432,6 @@ def main(): "Sequences longer than this will be truncated, and sequences shorter \n" "than this will be padded.") parser.add_argument("--do_train", - default=False, action='store_true', help="Whether to run training.") parser.add_argument("--train_batch_size", @@ -457,11 +456,9 @@ def main(): help="Proportion of training to perform linear learning rate warmup for. " "E.g., 0.1 = 10%% of training.") parser.add_argument("--no_cuda", - default=False, action='store_true', help="Whether not to use CUDA when available") parser.add_argument("--on_memory", - default=False, action='store_true', help="Whether to load train samples into memory or use disk") parser.add_argument("--local_rank", @@ -477,7 +474,6 @@ def main(): default=1, help="Number of updates steps to accumualte before performing a backward/update pass.") parser.add_argument('--fp16', - default=False, action='store_true', help="Whether to use 16-bit float precision instead of 32-bit") parser.add_argument('--loss_scale', diff --git a/examples/run_squad.py b/examples/run_squad.py index a4a568d999..88ea590936 100644 --- a/examples/run_squad.py +++ b/examples/run_squad.py @@ -698,8 +698,8 @@ def main(): parser.add_argument("--max_query_length", default=64, type=int, help="The maximum number of tokens for the question. Questions longer than this will " "be truncated to this length.") - parser.add_argument("--do_train", default=False, action='store_true', help="Whether to run training.") - parser.add_argument("--do_predict", default=False, action='store_true', help="Whether to run eval on the dev set.") + parser.add_argument("--do_train", action='store_true', help="Whether to run training.") + parser.add_argument("--do_predict", action='store_true', help="Whether to run eval on the dev set.") parser.add_argument("--train_batch_size", default=32, type=int, help="Total batch size for training.") parser.add_argument("--predict_batch_size", default=8, type=int, help="Total batch size for predictions.") parser.add_argument("--learning_rate", default=5e-5, type=float, help="The initial learning rate for Adam.") @@ -714,11 +714,10 @@ def main(): parser.add_argument("--max_answer_length", default=30, type=int, help="The maximum length of an answer that can be generated. This is needed because the start " "and end predictions are not conditioned on one another.") - parser.add_argument("--verbose_logging", default=False, action='store_true', + parser.add_argument("--verbose_logging", action='store_true', help="If true, all of the warnings related to data processing will be printed. " "A number of warnings are expected for a normal SQuAD evaluation.") parser.add_argument("--no_cuda", - default=False, action='store_true', help="Whether not to use CUDA when available") parser.add_argument('--seed', @@ -730,7 +729,6 @@ def main(): default=1, help="Number of updates steps to accumulate before performing a backward/update pass.") parser.add_argument("--do_lower_case", - default=True, action='store_true', help="Whether to lower case the input text. True for uncased models, False for cased models.") parser.add_argument("--local_rank", @@ -738,7 +736,6 @@ def main(): default=-1, help="local_rank for distributed training on gpus") parser.add_argument('--fp16', - default=False, action='store_true', help="Whether to use 16-bit float precision instead of 32-bit") parser.add_argument('--loss_scale', diff --git a/examples/run_swag.py b/examples/run_swag.py index c31696fec8..3fb87ae3e7 100644 --- a/examples/run_swag.py +++ b/examples/run_swag.py @@ -265,15 +265,12 @@ def main(): "Sequences longer than this will be truncated, and sequences shorter \n" "than this will be padded.") parser.add_argument("--do_train", - default=False, action='store_true', help="Whether to run training.") parser.add_argument("--do_eval", - default=False, action='store_true', help="Whether to run eval on the dev set.") parser.add_argument("--do_lower_case", - default=False, action='store_true', help="Set this flag if you are using an uncased model.") parser.add_argument("--train_batch_size", @@ -298,7 +295,6 @@ def main(): help="Proportion of training to perform linear learning rate warmup for. " "E.g., 0.1 = 10%% of training.") parser.add_argument("--no_cuda", - default=False, action='store_true', help="Whether not to use CUDA when available") parser.add_argument("--local_rank", @@ -314,7 +310,6 @@ def main(): default=1, help="Number of updates steps to accumulate before performing a backward/update pass.") parser.add_argument('--fp16', - default=False, action='store_true', help="Whether to use 16-bit float precision instead of 32-bit") parser.add_argument('--loss_scale',