Ahmadzei's picture
added 3 more tables for large emb model
5fa1a76
from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
args = PyTorchBenchmarkArguments(models=["google-bert/bert-base-uncased"], batch_sizes=[8], sequence_lengths=[8, 32, 128, 512])
benchmark = PyTorchBenchmark(args)
</pt>
<tf>py
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
args = TensorFlowBenchmarkArguments(
models=["google-bert/bert-base-uncased"], batch_sizes=[8], sequence_lengths=[8, 32, 128, 512]
)
benchmark = TensorFlowBenchmark(args)
Here, three arguments are given to the benchmark argument data classes, namely models, batch_sizes, and
sequence_lengths.