Option to benchmark only one of the two libraries

examples/benchmarks.py

@@ -14,7 +14,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """ Benchmarking the library on inference and training """
-import tensorflow as tf
 
 # If checking the tensors placement
 # tf.debugging.set_log_device_placement(True)
@@ -23,15 +22,18 @@ from typing import List
 import timeit
 from transformers import is_tf_available, is_torch_available
 from time import time
-import torch
-
 import argparse
 import csv
 
-if not is_torch_available() or not is_tf_available():
+if is_tf_available():
-    raise ImportError("TensorFlow and Pytorch should be installed on the system.")
+    import tensorflow as tf
+    from transformers import TFAutoModel
 
-from transformers import AutoConfig, AutoModel, AutoTokenizer, TFAutoModel
+if is_torch_available():
+    import torch
+    from transformers import AutoModel
+
+from transformers import AutoConfig, AutoTokenizer
 
 input_text = """Bent over their instruments, three hundred Fertilizers were plunged, as 
 the Director of Hatcheries and Conditioning entered the room, in the 
@@ -434,6 +436,7 @@ def main():
     print("Running with arguments", args)
 
     if args.torch:
+        if is_torch_available():
             create_setup_and_compute(
                 model_names=args.models,
                 tensorflow=False,
@@ -443,8 +446,11 @@ def main():
                 csv_filename=args.csv_filename,
                 average_over=args.average_over
             )
+        else:
+            raise ImportError("Trying to run a PyTorch benchmark but PyTorch was not found in the environment.")
 
     if args.tensorflow:
+        if is_tf_available():
             create_setup_and_compute(
                 model_names=args.models,
                 tensorflow=True,
@@ -453,7 +459,8 @@ def main():
                 csv_filename=args.csv_filename,
                 average_over=args.average_over
             )
-
+        else:
+            raise ImportError("Trying to run a TensorFlow benchmark but TensorFlow was not found in the environment.")
 
 if __name__ == '__main__':
     main()