!6393 bugfix delete batch_size

Merge pull request !6393 from yoonlee666/master
This commit is contained in:
mindspore-ci-bot 2020-09-17 16:43:15 +08:00 committed by Gitee
commit db0c0caf10
4 changed files with 7 additions and 7 deletions

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@ -235,7 +235,7 @@ def run_ner():
ds.get_dataset_size(), epoch_num, "ner")
if args_opt.do_eval.lower() == "true":
ds = create_ner_dataset(batch_size=bert_net_cfg.batch_size, repeat_count=1,
ds = create_ner_dataset(batch_size=optimizer_cfg.batch_size, repeat_count=1,
assessment_method=assessment_method, data_file_path=args_opt.eval_data_file_path,
schema_file_path=args_opt.schema_file_path,
do_shuffle=(args_opt.eval_data_shuffle.lower() == "true"))

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@ -16,8 +16,8 @@
echo "=============================================================================================================="
echo "Please run the scipt as: "
echo "bash run_distributed_pretrain.sh DATA_DIR RANK_TABLE_FILE"
echo "for example: bash run_distributed_pretrain.sh /path/dataset /path/hccl.json"
echo "bash run_distributed_pretrain_ascend.sh DATA_DIR RANK_TABLE_FILE"
echo "for example: bash run_distributed_pretrain_ascend.sh /path/dataset /path/hccl.json"
echo "It is better to use absolute path."
echo "For hyper parameter, please note that you should customize the scripts:
'{CUR_DIR}/scripts/ascend_distributed_launcher/hyper_parameter_config.ini' "

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@ -16,8 +16,8 @@
echo "=============================================================================================================="
echo "Please run the scipt as: "
echo "bash run_standalone_pretrain.sh DEVICE_ID EPOCH_SIZE DATA_DIR SCHEMA_DIR"
echo "for example: bash run_standalone_pretrain.sh 0 40 /path/zh-wiki/ /path/Schema.json"
echo "bash run_standalone_pretrain_ascend.sh DEVICE_ID EPOCH_SIZE DATA_DIR SCHEMA_DIR"
echo "for example: bash run_standalone_pretrain_ascend.sh 0 40 /path/zh-wiki/ /path/Schema.json"
echo "=============================================================================================================="
DEVICE_ID=$1

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@ -542,7 +542,7 @@ class BertAttention(nn.Cell):
attention_probs_r = self.reshape(
attention_probs_t,
(self.from_seq_length,
self.batch_num,
-1,
self.to_seq_length))
# value_position_scores is [F, B * N, H]
value_position_scores = self.matmul(attention_probs_r,
@ -550,7 +550,7 @@ class BertAttention(nn.Cell):
# value_position_scores_r is [F, B, N, H]
value_position_scores_r = self.reshape(value_position_scores,
(self.from_seq_length,
self.batch_size,
-1,
self.num_attention_heads,
self.size_per_head))
# value_position_scores_r_t is [B, N, F, H]