Config - Disable disk-benchmark in ndmv4.yaml and change batch size to 1 in default.yaml (#292)

**Description**
Disable disk-benchmark in ndmv4.yaml and change batch size to 1 in default.yaml

superbench/config/azure_ndmv4.yaml

@@ -81,7 +81,7 @@ superbench:
           prefix: CUDA_VISIBLE_DEVICES={proc_rank} numactl -N $(({proc_rank}/2))
           parallel: no
     disk-benchmark:
-      enable: true
+      enable: false
       modes:
         - name: local
           proc_num: 1

superbench/config/azure_ndv4.yaml

@@ -83,7 +83,21 @@ superbench:
           proc_num: 1
           parallel: no
       parameters:
-        block_devices: []
+        block_devices:
+          - /dev/nvme0n1
+          - /dev/nvme1n1
+          - /dev/nvme2n1
+          - /dev/nvme3n1
+          - /dev/nvme4n1
+          - /dev/nvme5n1
+          - /dev/nvme6n1
+          - /dev/nvme7n1
+        seq_read_runtime: 60
+        seq_write_runtime: 60
+        seq_readwrite_runtime: 60
+        rand_read_runtime: 60
+        rand_write_runtime: 60
+        rand_readwrite_runtime: 60
     gpu-copy-bw:
       enable: true
       modes:

superbench/config/default.yaml

@@ -26,6 +26,7 @@ superbench:
       duration: 0
       num_warmup: 16
       num_steps: 128
+      batch_size: 1
       precision:
         - float32
         - float16
@@ -143,6 +144,8 @@ superbench:
         port: 22
     ort-inference:
       <<: *default_local_mode
+      parameters:
+        batch_size: 1
     tensorrt-inference:
       <<: *default_local_mode
       parameters:
@@ -155,7 +158,7 @@ superbench:
           - bert-base
           - bert-large
         seq_length: 224
-        batch_size: 32
+        batch_size: 1
         precision: int8
     gpt_models:
       <<: *default_pytorch_mode
@@ -164,7 +167,6 @@ superbench:
         - gpt2-large
       parameters:
         <<: *common_model_config
-        batch_size: 4
     bert_models:
       <<: *default_pytorch_mode
       models:
@@ -172,14 +174,12 @@ superbench:
         - bert-large
       parameters:
         <<: *common_model_config
-        batch_size: 8
     lstm_models:
       <<: *default_pytorch_mode
       models:
         - lstm
       parameters:
         <<: *common_model_config
-        batch_size: 128
     resnet_models:
       <<: *default_pytorch_mode
       models:
@@ -188,7 +188,6 @@ superbench:
         - resnet152
       parameters:
         <<: *common_model_config
-        batch_size: 128
     densenet_models:
       <<: *default_pytorch_mode
       models:
@@ -196,7 +195,6 @@ superbench:
         - densenet201
       parameters:
         <<: *common_model_config
-        batch_size: 128
     vgg_models:
       <<: *default_pytorch_mode
       models:
@@ -206,4 +204,3 @@ superbench:
         - vgg19
       parameters:
         <<: *common_model_config
-        batch_size: 128