Remove `formats` variable to avoid `pd` conflict (#7993)

* Remove `formats` variable to avoid `pd` conflict

* Update export.py

export.py

 ):
     t = time.time()
     include = [x.lower() for x in include]  # to lowercase
-    formats = tuple(export_formats()['Argument'][1:])  # --include arguments
-    flags = [x in include for x in formats]
-    assert sum(flags) == len(include), f'ERROR: Invalid --include {include}, valid --include arguments are {formats}'
+    fmts = tuple(export_formats()['Argument'][1:])  # --include arguments
+    flags = [x in include for x in fmts]
+    assert sum(flags) == len(include), f'ERROR: Invalid --include {include}, valid --include arguments are {fmts}'
     jit, onnx, xml, engine, coreml, saved_model, pb, tflite, edgetpu, tfjs = flags  # export booleans
     file = Path(url2file(weights) if str(weights).startswith(('http:/', 'https:/')) else weights)  # PyTorch weights
 
     im = torch.zeros(batch_size, 3, *imgsz).to(device)  # image size(1,3,320,192) BCHW iDetection
 
     # Update model
-    if half and not (coreml or xml):
+    if half and not coreml and not xml:
         im, model = im.half(), model.half()  # to FP16
     model.train() if train else model.eval()  # training mode = no Detect() layer grid construction
     for k, m in model.named_modules():
     if any((saved_model, pb, tflite, edgetpu, tfjs)):
         if int8 or edgetpu:  # TFLite --int8 bug https://github.com/ultralytics/yolov5/issues/5707
             check_requirements(('flatbuffers==1.12',))  # required before `import tensorflow`
-        assert not (tflite and tfjs), 'TFLite and TF.js models must be exported separately, please pass only one type.'
+        assert not tflite or not tfjs, 'TFLite and TF.js models must be exported separately, please pass only one type.'
         model, f[5] = export_saved_model(model.cpu(),
                                          im,
                                          file,

utils/benchmarks.py

         pt_only=False,  # test PyTorch only
 ):
     y, t = [], time.time()
-    formats = export.export_formats()
     device = select_device(device)
-    for i, (name, f, suffix, gpu) in formats.iterrows():  # index, (name, file, suffix, gpu-capable)
+    for i, (name, f, suffix, gpu) in export.export_formats().iterrows():  # index, (name, file, suffix, gpu-capable)
         try:
             assert i != 9, 'Edge TPU not supported'
             assert i != 10, 'TF.js not supported'
         pt_only=False,  # test PyTorch only
 ):
     y, t = [], time.time()
-    formats = export.export_formats()
     device = select_device(device)
-    for i, (name, f, suffix, gpu) in formats.iterrows():  # index, (name, file, suffix, gpu-capable)
+    for i, (name, f, suffix, gpu) in export.export_formats().iterrows():  # index, (name, file, suffix, gpu-capable)
         try:
             w = weights if f == '-' else \
                 export.run(weights=weights, imgsz=[imgsz], include=[f], device=device, half=half)[-1]  # weights