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

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

* Update export.py
pull/7997/head
Glenn Jocher 2022-05-26 16:07:58 +02:00 committed by GitHub
parent 1dcb774998
commit 945579699a
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2 changed files with 7 additions and 9 deletions

View File

@ -475,9 +475,9 @@ def run(
): ):
t = time.time() t = time.time()
include = [x.lower() for x in include] # to lowercase include = [x.lower() for x in include] # to lowercase
formats = tuple(export_formats()['Argument'][1:]) # --include arguments fmts = tuple(export_formats()['Argument'][1:]) # --include arguments
flags = [x in include for x in formats] flags = [x in include for x in fmts]
assert sum(flags) == len(include), f'ERROR: Invalid --include {include}, valid --include arguments are {formats}' 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 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 file = Path(url2file(weights) if str(weights).startswith(('http:/', 'https:/')) else weights) # PyTorch weights
@ -499,7 +499,7 @@ def run(
im = torch.zeros(batch_size, 3, *imgsz).to(device) # image size(1,3,320,192) BCHW iDetection im = torch.zeros(batch_size, 3, *imgsz).to(device) # image size(1,3,320,192) BCHW iDetection
# Update model # 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 im, model = im.half(), model.half() # to FP16
model.train() if train else model.eval() # training mode = no Detect() layer grid construction model.train() if train else model.eval() # training mode = no Detect() layer grid construction
for k, m in model.named_modules(): for k, m in model.named_modules():
@ -531,7 +531,7 @@ def run(
if any((saved_model, pb, tflite, edgetpu, tfjs)): if any((saved_model, pb, tflite, edgetpu, tfjs)):
if int8 or edgetpu: # TFLite --int8 bug https://github.com/ultralytics/yolov5/issues/5707 if int8 or edgetpu: # TFLite --int8 bug https://github.com/ultralytics/yolov5/issues/5707
check_requirements(('flatbuffers==1.12',)) # required before `import tensorflow` 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(), model, f[5] = export_saved_model(model.cpu(),
im, im,
file, file,

View File

@ -56,9 +56,8 @@ def run(
pt_only=False, # test PyTorch only pt_only=False, # test PyTorch only
): ):
y, t = [], time.time() y, t = [], time.time()
formats = export.export_formats()
device = select_device(device) 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: try:
assert i != 9, 'Edge TPU not supported' assert i != 9, 'Edge TPU not supported'
assert i != 10, 'TF.js not supported' assert i != 10, 'TF.js not supported'
@ -104,9 +103,8 @@ def test(
pt_only=False, # test PyTorch only pt_only=False, # test PyTorch only
): ):
y, t = [], time.time() y, t = [], time.time()
formats = export.export_formats()
device = select_device(device) 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: try:
w = weights if f == '-' else \ w = weights if f == '-' else \
export.run(weights=weights, imgsz=[imgsz], include=[f], device=device, half=half)[-1] # weights export.run(weights=weights, imgsz=[imgsz], include=[f], device=device, half=half)[-1] # weights