I'm getting an error even though I'm using less data

111555: <blockquote>
<h2>EPOCH: 1</h2>
<p>ValueError                                Traceback (most recent call last)<br>
 in ()<br>
80<br>
81 if not modelfiles:<br>
—&gt; 82     modelfiles = [train_mri_type(df_train, df_valid, m) for m in mri_types]<br>
83     print(modelfiles)</p>
<p>7 frames<br>
/usr/local/lib/python3.7/dist-packages/torch/_utils.py in reraise(self)<br>
423             # have message field<br>
424             raise self.exc_type(message=msg)<br>
 → 425         raise self.exc_type(msg)<br>
426<br>
427</p>
<p>ValueError: Caught ValueError in DataLoader worker process 2.<br>
Original Traceback (most recent call last):<br>
File “/usr/local/lib/python3.7/dist-packages/torch/utils/data/_utils/worker.py”, line 287, in _worker_loop<br>
data = fetcher.fetch(index)<br>
File “/usr/local/lib/python3.7/dist-packages/torch/utils/data/_utils/fetch.py”, line 44, in fetch<br>
data = [self.dataset[idx] for idx in possibly_batched_index]<br>
File “/usr/local/lib/python3.7/dist-packages/torch/utils/data/_utils/fetch.py”, line 44, in <br>
data = [self.dataset[idx] for idx in possibly_batched_index]<br>
File “”, line 23, in <strong>getitem</strong><br>
data = load_dicom_images_3d(str(scan_id).zfill(5), mri_type=self.mri_type[index], split=“train”, rotate=rotation)<br>
File “”, line 26, in load_dicom_images_3d<br>
img3d = np.stack([load_dicom_image(f, rotate=rotate) for f in files[p1:p2]]).T<br>
File “&lt;<strong>array_function</strong> internals&gt;”, line 6, in stack<br>
File “/usr/local/lib/python3.7/dist-packages/numpy/core/shape_base.py”, line 423, in stack<br>
raise ValueError(‘need at least one array to stack’)<br>
ValueError: need at least one array to stack</p>
</blockquote>
<p>hi!</p><aside class="onebox allowlistedgeneric" data-onebox-src="https://www.kaggle.com/rluethy/efficientnet3d-with-one-mri-type">
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      <a href="https://www.kaggle.com/rluethy/efficientnet3d-with-one-mri-type" target="_blank" rel="noopener nofollow ugc">kaggle.com</a>
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<h3><a href="https://www.kaggle.com/rluethy/efficientnet3d-with-one-mri-type" target="_blank" rel="noopener nofollow ugc">Efficientnet3D with one MRI type</a></h3>

  <p>Explore and run machine learning code with Kaggle Notebooks | Using data from multiple data sources</p>


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<p>I’m using this guy’s model, but when I do a train with googlecolab again, I get an Error.</p>
<p>What should I do?</p>
<p>By the way, the data is heavy, so I’ve reduced it to 1/20, but it doesn’t matter how much data I have.<br>
Isn’t it too hard to use googlecolab?<br>
If anyone has a cool answer, I’d appreciate it.<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/d/b/dba8092085113efa3e77aa942dbb54bc3467fbe7.png" data-download-href="https://discuss.pytorch.org/uploads/default/dba8092085113efa3e77aa942dbb54bc3467fbe7" title="1_Model_3d-ipynb-Colaboratory"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/d/b/dba8092085113efa3e77aa942dbb54bc3467fbe7_2_627x499.png" alt="1_Model_3d-ipynb-Colaboratory" data-base62-sha1="vlaA0pMZ10RGqIvsNVEWipLVhpd" width="627" height="499" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/d/b/dba8092085113efa3e77aa942dbb54bc3467fbe7_2_627x499.png, https://discuss.pytorch.org/uploads/default/optimized/3X/d/b/dba8092085113efa3e77aa942dbb54bc3467fbe7_2_940x748.png 1.5x, https://discuss.pytorch.org/uploads/default/optimized/3X/d/b/dba8092085113efa3e77aa942dbb54bc3467fbe7_2_1254x998.png 2x" data-dominant-color="3F3F40"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">1_Model_3d-ipynb-Colaboratory</span><span class="informations">2192×1746 442 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div><br>
By the way,this plan is great because it is a 50$ plan.</p>

ptrblck: <p>The error is raised by <code>np.stack</code> if you try to pass an empty list to <code>np.stack</code>:</p>
<pre><code class="lang-python">np.stack([])
&gt; ValueError: need at least one array to stack
</code></pre>