Add TF weights
#1
by
amyeroberts
HF staff
- opened
Model converted by the transformers' pt_to_tf CLI. All converted model outputs and hidden layers were validated against its Pytorch counterpart.
Maximum crossload output difference=3.338e-06; Maximum crossload hidden layer difference=3.569e-05;
Maximum conversion output difference=3.338e-06; Maximum conversion hidden layer difference=3.569e-05;
amyeroberts
changed pull request status to
merged
I've tried with TF weight, but got error.
from transformers import SegformerFeatureExtractor, SegformerForImageClassification
from PIL import Image
import requests
url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)
feature_extractor = SegformerFeatureExtractor.from_pretrained("nvidia/mit-b0")
model = SegformerForImageClassification.from_pretrained("nvidia/mit-b0")
inputs = feature_extractor(images=image, return_tensors="tf")
outputs = model(**inputs)
logits = outputs.logits
# model predicts one of the 1000 ImageNet classes
predicted_class_idx = logits.argmax(-1).item()
print("Predicted class:", model.config.id2label[predicted_class_idx])
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/tmp/ipykernel_33/1248207528.py in <module>
10
11 inputs = feature_extractor(images=image, return_tensors="tf")
---> 12 outputs = model(**inputs)
13 logits = outputs.logits
14 # model predicts one of the 1000 ImageNet classe
TypeError: conv2d() received an invalid combination of arguments - got (tensorflow.python.framework.ops.EagerTensor, Parameter, Parameter, tuple, tuple, tuple, int), but expected one of:
* (Tensor input, Tensor weight, Tensor bias, tuple of ints stride, tuple of ints padding, tuple of ints dilation, int groups)
didn't match because some of the arguments have invalid types: (!tensorflow.python.framework.ops.EagerTensor!, !Parameter!, !Parameter!, !tuple!, !tuple!, !tuple!, int)
* (Tensor input, Tensor weight, Tensor bias, tuple of ints stride, str padding, tuple of ints dilation, int groups)
didn't match because some of the arguments have invalid types: (!tensorflow.python.framework.ops.EagerTensor!, !Parameter!, !Parameter!, !tuple!, !tuple!, !tuple!, int)
This comment has been hidden
This issue is arising because SegformerForImageClassification is a PyTorch model and the inputs are tensorflow tensors. To load the TF model, you want to import TFSegformerForImageClassification.
uh, got it. Thanks.