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. |