Questions tagged [user-warning]

22 questions
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UserWarning: volatile was removed and now has no essfet. Use 'with torch.no_grad():' insted

The version of PyTorch: 1.4.0+cu100 When running val_L= Variable(torch.from_numpy(val_L.copy()), volatile=True).cuda() occurred: UserWarning: volatile was removed and now has no essfet. Use 'with torch.no_grad():' insted. So, how should I modify…
hkzhang
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How do I fix the UserWarning: Using a target size (torch.Size([1])) that is different to the input size (torch.Size([])) is deprecated

When I try to run my model, I get this UserWarning. How do I go about fixing this? My model's input is expecting (torch.Size([])), a scalar, but my target is torch.Size([1])). Should I be changed my input size or my target size? Any help would be…
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UserWarning: The output shape of `ResNet50(include_top=False)` has been changed since Keras 2.2.0

For transfer learning I am using a ResNet50 model pre trained on ImageNet. After removing the last layer I want to use outputs of the layer before the last layer (as the last layer is removed by making top = False) as a feature extractor to train a…
hafiz031
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I tried the python code using keras and i got a warning

While executing the line bellow model.add(Dense(input_dim=23,init="random_uniform",activation="relu",output_dim=12)) I get this warning: UserWarning: Update your `Dense` call to the Keras 2 API: `Dense(input_dim=23, activation="relu", units=12,…
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Manage user warnings

I'm not used to work with values that should decrement every a timelapse like for a user warned, for example a warn which persist for 30 days that can reach a maximum value of 3 warns before the user get banned I thought to design a user table like…
vitto
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UserWarning: Encountered more than 100 detections in a single image

I am currently using the retinanet model to identify cells in clinical images. When training the model I get the following error: EPOCH 1 of 50 Training Loss: 1.0731:…
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Python bs4 module

import requests from bs4 import BeautifulSoup ''' It's a web crawler working in ebay, collecting every single item data ''' def ebay_spider(max_pages): page = 1 while page <= max_pages: url =…
Auginis
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