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Time test #2

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8c556f6
type check
XC-Xinze Mar 25, 2025
3186872
type check 2
XC-Xinze Mar 26, 2025
0aedd8c
time test for py_funciton
XC-Xinze Apr 12, 2025
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3 changes: 2 additions & 1 deletion data_pipeline.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,7 +58,8 @@ def input_fn(tf_records,
dataset = tf.data.TFRecordDataset(tf_records, buffer_size=10000)
dataset = dataset.shuffle(buffer_size=buffer_size)

dataset = dataset.map(parse_example,num_parallel_calls=tf.data.experimental.AUTOTUNE)
dataset = dataset.map(lambda
x:tf.py_function(func=parse_example,inp=[x],Tout=(tf.int32,tf.int32)))
dataset = dataset.padded_batch(batch_size, padded_shapes=padded_shapes)
dataset = dataset.repeat(epoch)
dataset = dataset.prefetch(buffer_size=tf.data.experimental.AUTOTUNE)
Expand Down
2 changes: 1 addition & 1 deletion setup.sh
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Expand Up @@ -2,4 +2,4 @@

PYTHON="python3.10"

$PYTHON pre_process.py
# $PYTHON pre_process.py
10 changes: 9 additions & 1 deletion train_gpt2.py
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Expand Up @@ -5,7 +5,8 @@

from data_pipeline import input_fn
from gpt2_model import *

from scripts.utils import write_csv
import timeit
_ROOT = os.path.abspath(os.path.dirname(__file__))
LOG_DIR = _ROOT + "/log"
MODEL_DIR = _ROOT + "/model"
Expand Down Expand Up @@ -44,7 +45,10 @@ def train(num_layers, embedding_size, num_heads, dff, max_seq_len, vocab_size,
train_tf_records = tf_records[:train_percent]
test_tf_records = tf_records[train_percent:]

print("Train dataset:")
train_dataset = input_fn(train_tf_records, batch_size=batch_size)

print("Test dataset:")
test_dataset = input_fn(test_tf_records, batch_size=batch_size)

if distributed:
Expand Down Expand Up @@ -74,4 +78,8 @@ def train(num_layers, embedding_size, num_heads, dff, max_seq_len, vocab_size,


if __name__ == "__main__":
start_time = timeit.default_timer()
skipped_time = 0
train()
time = timeit.default_timer() - skipped_time -start_time
write_csv(__file,time=time)