Benchmarks: Unify metric names of benchmarks (#252)

**Description**
Unify metric names of benchmarks.

tests/benchmarks/model_benchmarks/test_pytorch_bert.py

@@ -50,9 +50,8 @@ def test_pytorch_bert_base():
     assert (benchmark.run_count == 1)
     assert (benchmark.return_code == ReturnCode.SUCCESS)
     for metric in [
-        'steptime_train_float32', 'throughput_train_float32', 'steptime_train_float16', 'throughput_train_float16',
-        'steptime_inference_float32', 'throughput_inference_float32', 'steptime_inference_float16',
-        'throughput_inference_float16'
+        'fp32_train_step_time', 'fp32_train_throughput', 'fp16_train_step_time', 'fp16_train_throughput',
+        'fp32_inference_step_time', 'fp32_inference_throughput', 'fp16_inference_step_time', 'fp16_inference_throughput'
     ]:
         assert (len(benchmark.raw_data[metric]) == benchmark.run_count)
         assert (len(benchmark.raw_data[metric][0]) == benchmark._args.num_steps)

tests/benchmarks/model_benchmarks/test_pytorch_cnn.py

@@ -17,9 +17,9 @@ def test_pytorch_cnn_with_gpu():
         parameters='--batch_size 1 --image_size 224 --num_classes 5 --num_warmup 2 --num_steps 4 \
             --model_action train inference',
         check_metrics=[
-            'steptime_train_float32', 'throughput_train_float32', 'steptime_train_float16', 'throughput_train_float16',
-            'steptime_inference_float32', 'throughput_inference_float32', 'steptime_inference_float16',
-            'throughput_inference_float16'
+            'fp32_train_step_time', 'fp32_train_throughput', 'fp16_train_step_time', 'fp16_train_throughput',
+            'fp32_inference_step_time', 'fp32_inference_throughput', 'fp16_inference_step_time',
+            'fp16_inference_throughput'
         ]
     )
 
@@ -32,8 +32,7 @@ def test_pytorch_cnn_no_gpu():
         parameters='--batch_size 1 --image_size 224 --num_classes 5 --num_warmup 2 --num_steps 4 \
                 --model_action train inference --precision float32 --no_gpu',
         check_metrics=[
-            'steptime_train_float32', 'throughput_train_float32', 'steptime_inference_float32',
-            'throughput_inference_float32'
+            'fp32_train_step_time', 'fp32_train_throughput', 'fp32_inference_step_time', 'fp32_inference_throughput'
         ]
     )
 

tests/benchmarks/model_benchmarks/test_pytorch_gpt2.py

@@ -49,9 +49,8 @@ def test_pytorch_gpt2_small():
     assert (benchmark.run_count == 1)
     assert (benchmark.return_code == ReturnCode.SUCCESS)
     for metric in [
-        'steptime_train_float32', 'throughput_train_float32', 'steptime_train_float16', 'throughput_train_float16',
-        'steptime_inference_float32', 'throughput_inference_float32', 'steptime_inference_float16',
-        'throughput_inference_float16'
+        'fp32_train_step_time', 'fp32_train_throughput', 'fp16_train_step_time', 'fp16_train_throughput',
+        'fp32_inference_step_time', 'fp32_inference_throughput', 'fp16_inference_step_time', 'fp16_inference_throughput'
     ]:
         assert (len(benchmark.raw_data[metric]) == benchmark.run_count)
         assert (len(benchmark.raw_data[metric][0]) == benchmark._args.num_steps)

tests/benchmarks/model_benchmarks/test_pytorch_lstm.py

@@ -16,9 +16,9 @@ def test_pytorch_lstm_with_gpu():
         parameters='--batch_size 1 --num_classes 5 --seq_len 8 --num_warmup 2 --num_steps 4 \
             --model_action train inference',
         check_metrics=[
-            'steptime_train_float32', 'throughput_train_float32', 'steptime_train_float16', 'throughput_train_float16',
-            'steptime_inference_float32', 'throughput_inference_float32', 'steptime_inference_float16',
-            'throughput_inference_float16'
+            'fp32_train_step_time', 'fp32_train_throughput', 'fp16_train_step_time', 'fp16_train_throughput',
+            'fp32_inference_step_time', 'fp32_inference_throughput', 'fp16_inference_step_time',
+            'fp16_inference_throughput'
         ]
     )
 
@@ -30,8 +30,7 @@ def test_pytorch_lstm_no_gpu():
         parameters='--batch_size 1 --num_classes 5 --seq_len 8 --num_warmup 2 --num_steps 4 \
             --model_action train inference --precision float32 --no_gpu',
         check_metrics=[
-            'steptime_train_float32', 'throughput_train_float32', 'steptime_inference_float32',
-            'throughput_inference_float32'
+            'fp32_train_step_time', 'fp32_train_throughput', 'fp32_inference_step_time', 'fp32_inference_throughput'
         ]
     )