code: def batch_predict(model, inputs, input_transform=None, device=None):
      if input_transform:
          batch = torch.stack(
              tuple(input_transform(i) for i in inputs), dim=0
          )
      else:
          batch = torch.stack(inputs, dim=0)
  
      device = device or torch.device(
          "cuda" if torch.cuda.is_available() else "cpu"
      )
      model.eval()
      model.to(device)
      batch = batch.to(device)
  
      outputs = model(batch)
  
      return outputs
  
file_path: tensorwatch/tensorwatch/pytorch_utils.py
imports: from torchvision import models, transforms
  import torch
  import torch.nn.functional
  from .None import utils, image_utils
  import os
label_desc: Use image node_id 6 for calling a global function with example usage: batch_predict(model, inputs, input_transform, device) and returns: outputs