RuntimeError: Not compiled with GPU support on Colab

[Kashu7100]

Thank you for sharing this interesting work.
When I try to run the Colab example, the execution of 6th cell of the notebook resulted in the following error.

[[[0, 12]], [[16, 19]], [[23, 32]]]

/usr/local/lib/python3.7/dist-packages/transformers/modeling_utils.py:813: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  "The `device` argument is deprecated and will be removed in v5 of Transformers.", FutureWarning

---------------------------------------------------------------------------

RuntimeError                              Traceback (most recent call last)

[<ipython-input-6-d454bb231030>](https://localhost:8080/#) in <module>()
      1 image = load('http://farm4.staticflickr.com/3693/9472793441_b7822c00de_z.jpg')
      2 caption = 'bobble heads on top of the shelf'
----> 3 result, _ = glip_demo.run_on_web_image(image, caption, 0.5)
      4 imshow(result, caption)

17 frames

[/content/GLIP/maskrcnn_benchmark/engine/predictor_glip.py](https://localhost:8080/#) in run_on_web_image(self, original_image, original_caption, thresh, custom_entity, alpha)
    138             custom_entity = None,
    139             alpha = 0.0):
--> 140         predictions = self.compute_prediction(original_image, original_caption, custom_entity)
    141         top_predictions = self._post_process(predictions, thresh)
    142 

[/content/GLIP/maskrcnn_benchmark/engine/predictor_glip.py](https://localhost:8080/#) in compute_prediction(self, original_image, original_caption, custom_entity)
    217         # compute predictions
    218         with torch.no_grad():
--> 219             predictions = self.model(image_list, captions=[original_caption], positive_map=positive_map_label_to_token)
    220             predictions = [o.to(self.cpu_device) for o in predictions]
    221         print("inference time per image: {}".format(timeit.time.perf_counter() - tic))

[/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py](https://localhost:8080/#) in _call_impl(self, *input, **kwargs)
   1049         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1050                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051             return forward_call(*input, **kwargs)
   1052         # Do not call functions when jit is used
   1053         full_backward_hooks, non_full_backward_hooks = [], []

[/content/GLIP/maskrcnn_benchmark/modeling/detector/generalized_vl_rcnn.py](https://localhost:8080/#) in forward(self, images, targets, captions, positive_map, greenlight_map)
    283         else:
    284             proposals, proposal_losses, fused_visual_features = self.rpn(images, visual_features, targets, language_dict_features, positive_map,
--> 285                                               captions, swint_feature_c4)
    286         if self.roi_heads:
    287             if self.cfg.MODEL.ROI_MASK_HEAD.PREDICTOR.startswith("VL"):

[/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py](https://localhost:8080/#) in _call_impl(self, *input, **kwargs)
   1049         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1050                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051             return forward_call(*input, **kwargs)
   1052         # Do not call functions when jit is used
   1053         full_backward_hooks, non_full_backward_hooks = [], []

[/content/GLIP/maskrcnn_benchmark/modeling/rpn/vldyhead.py](https://localhost:8080/#) in forward(self, images, features, targets, language_dict_features, positive_map, captions, swint_feature_c4)
    921                                                                         language_dict_features,
    922                                                                         embedding,
--> 923                                                                         swint_feature_c4
    924                                                                         )
    925         anchors = self.anchor_generator(images, features)

[/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py](https://localhost:8080/#) in _call_impl(self, *input, **kwargs)
   1049         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1050                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051             return forward_call(*input, **kwargs)
   1052         # Do not call functions when jit is used
   1053         full_backward_hooks, non_full_backward_hooks = [], []

[/content/GLIP/maskrcnn_benchmark/modeling/rpn/vldyhead.py](https://localhost:8080/#) in forward(self, x, language_dict_features, embedding, swint_feature_c4)
    737                        "lang": language_dict_features}
    738 
--> 739         dyhead_tower = self.dyhead_tower(feat_inputs)
    740 
    741         # soft token

[/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py](https://localhost:8080/#) in _call_impl(self, *input, **kwargs)
   1049         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1050                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051             return forward_call(*input, **kwargs)
   1052         # Do not call functions when jit is used
   1053         full_backward_hooks, non_full_backward_hooks = [], []

[/usr/local/lib/python3.7/dist-packages/torch/nn/modules/container.py](https://localhost:8080/#) in forward(self, input)
    137     def forward(self, input):
    138         for module in self:
--> 139             input = module(input)
    140         return input
    141 

[/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py](https://localhost:8080/#) in _call_impl(self, *input, **kwargs)
   1049         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1050                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051             return forward_call(*input, **kwargs)
   1052         # Do not call functions when jit is used
   1053         full_backward_hooks, non_full_backward_hooks = [], []

[/content/GLIP/maskrcnn_benchmark/modeling/rpn/vldyhead.py](https://localhost:8080/#) in forward(self, inputs)
    203                 conv_args = dict(offset=offset, mask=mask)
    204 
--> 205             temp_fea = [self.DyConv[1](feature, **conv_args)]
    206 
    207             if level > 0:

[/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py](https://localhost:8080/#) in _call_impl(self, *input, **kwargs)
   1049         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1050                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051             return forward_call(*input, **kwargs)
   1052         # Do not call functions when jit is used
   1053         full_backward_hooks, non_full_backward_hooks = [], []

[/content/GLIP/maskrcnn_benchmark/modeling/rpn/vldyhead.py](https://localhost:8080/#) in forward(self, input, **kwargs)
    133 
    134     def forward(self, input, **kwargs):
--> 135         x = self.conv(input, **kwargs)
    136         if self.bn:
    137             x = self.bn(x)

[/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py](https://localhost:8080/#) in _call_impl(self, *input, **kwargs)
   1049         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1050                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051             return forward_call(*input, **kwargs)
   1052         # Do not call functions when jit is used
   1053         full_backward_hooks, non_full_backward_hooks = [], []

[/usr/local/lib/python3.7/dist-packages/torch/cuda/amp/autocast_mode.py](https://localhost:8080/#) in decorate_fwd(*args, **kwargs)
    217                     return fwd(*_cast(args, cast_inputs), **_cast(kwargs, cast_inputs))
    218             else:
--> 219                 return fwd(*args, **kwargs)
    220     return decorate_fwd
    221 

[/content/GLIP/maskrcnn_benchmark/layers/deform_conv.py](https://localhost:8080/#) in forward(self, input, offset, mask)
    380         return modulated_deform_conv(
    381             input, offset, mask, self.weight, self.bias, self.stride,
--> 382             self.padding, self.dilation, self.groups, self.deformable_groups)
    383 
    384     def __repr__(self):

[/content/GLIP/maskrcnn_benchmark/layers/deform_conv.py](https://localhost:8080/#) in forward(ctx, input, offset, mask, weight, bias, stride, padding, dilation, groups, deformable_groups)
    201             ctx.groups,
    202             ctx.deformable_groups,
--> 203             ctx.with_bias
    204         )
    205         return output

RuntimeError: Not compiled with GPU support

Here is the GPU information that I used:

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.32.03    Driver Version: 460.32.03    CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |
| N/A   51C    P8     9W /  70W |      0MiB / 15109MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

Any advice is appreciated.

Sincerely,

[zyong812]

Remove ./build and re-install. This solved the problem for me.

[neerajdr]

@zyong812 Where is ./build in directory

[zyong812]

Created by python setup.py build develop --user @neerajdr

[neerajdr]

@zyong812 How did you resolve this issue

I am getting isssue

/content/GLIP/maskrcnn_benchmark/engine/predictor_glip.py in overlay_entity_names(self, image, predictions, names, text_size, text_pixel, text_offset, text_offset_original)
345
346 cv2.putText(
--> 347 image, s, (int(x), int(y)-text_offset_original), cv2.FONT_HERSHEY_SIMPLEX, text_size, (self.color, self.color, self.color), text_pixel, cv2.LINE_AA
348 )
349 previous_locations.append((int(x), int(y)))

AttributeError: 'GLIPDemo' object has no attribute 'color'

[weinman]

@neerajdr I too had this issue; I surmise it may have to do with when the colab was published versus the current code.

Anyhow, there's probably a better way, but you can hack your way around this problem (and see some quick results at least) by inserting self.color = 255 at the beginning of method run_on_web_image of class GLIPDemo in file maskrcnn_benchmark/engine/predictor_glip.py

At least that will get you some white boxes to look at.

E.g., here's a diff:

index 6d28576..1fda54a 100644
--- a/maskrcnn_benchmark/engine/predictor_glip.py
+++ b/maskrcnn_benchmark/engine/predictor_glip.py
@@ -137,6 +137,7 @@ class GLIPDemo(object):
             thresh=0.5,
             custom_entity = None,
             alpha = 0.0):
+        self.color = 255
         predictions = self.compute_prediction(original_image, original_caption, custom_entity)
         top_predictions = self._post_process(predictions, thresh)

[Haotian-Zhang]

Please refer to #31 for a quick fix, thanks!

[JasonHysy]

Created by python setup.py build develop --user @neerajdr

Hello,
I have the same issue. Sorry do you mind specifying what does it mean by re-installation?
like re-run the following 3 command?

pip install einops shapely timm yacs tensorboardX ftfy prettytable pymongo

pip install transformers 

python setup.py build develop --user