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    <title>topic &amp;quot;Unable to initialize python raster function with scalar arguments&amp;quot; on an NVIDIA machine in ArcGIS Notebooks Questions</title>
    <link>https://community.esri.com/t5/arcgis-notebooks-questions/quot-unable-to-initialize-python-raster-function/m-p/285887#M79</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I am trying to run a notebook given to me by Esri Support staff (case #&lt;SPAN style="color: #4c4c4c; background-color: #f8f8f8; font-weight: 300;"&gt;02587809) and when I try to run the&amp;nbsp;arcpy.ia.DetectObjectsUsingDeepLearning function I recieve the following error message:&lt;/SPAN&gt;&lt;/P&gt;&lt;PRE class="lia-code-sample line-numbers language-none"&gt;Line &lt;SPAN class="" style="color: #208ffb;"&gt;1&lt;/SPAN&gt;:     arcpy.ia.DetectObjectsUsingDeepLearning(imagery, &lt;SPAN class="" style="color: #ddb62b;"&gt;r&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;C:&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Users&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Administrator&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Documents&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;ArcGIS&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Projects&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Haiti_AI&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Haiti_AI.gdb&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;bldg_detected_jupyterGPU_10July2020&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #ddb62b;"&gt;r&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;D:&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;TrainingData&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;MaskRCNN_chips&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;models&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Building_footprint_40epochsGPU&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Building_footprint_40epochsGPU.emd&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;padding 64;batch_size 4;threshold 0.9;return_bboxes False&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;NO_NMS&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Confidence&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Class&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #208ffb;"&gt;0&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;PROCESS_AS_MOSAICKED_IMAGE&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;)  File &lt;SPAN class="" style="color: #208ffb;"&gt;c:\program files\arcgis\pro\Resources\arcpy\arcpy\ia\Functions.py&lt;/SPAN&gt;, in &lt;SPAN class="" style="color: #00a250;"&gt;DetectObjectsUsingDeepLearning&lt;/SPAN&gt;: Line &lt;SPAN class="" style="color: #208ffb;"&gt;2888&lt;/SPAN&gt;:  processing_mode)  File &lt;SPAN class="" style="color: #208ffb;"&gt;c:\program files\arcgis\pro\Resources\arcpy\arcpy\sa\Utils.py&lt;/SPAN&gt;, in &lt;SPAN class="" style="color: #00a250;"&gt;swapper&lt;/SPAN&gt;: Line &lt;SPAN class="" style="color: #208ffb;"&gt;53&lt;/SPAN&gt;:    result = wrapper(*args, **kwargs)  File &lt;SPAN class="" style="color: #208ffb;"&gt;c:\program files\arcgis\pro\Resources\arcpy\arcpy\ia\Functions.py&lt;/SPAN&gt;, in &lt;SPAN class="" style="color: #00a250;"&gt;Wrapper&lt;/SPAN&gt;: Line &lt;SPAN class="" style="color: #208ffb;"&gt;2877&lt;/SPAN&gt;:  processing_mode)  File &lt;SPAN class="" style="color: #208ffb;"&gt;c:\program files\arcgis\pro\Resources\arcpy\arcpy\geoprocessing\_base.py&lt;/SPAN&gt;, in &lt;SPAN class="" style="color: #00a250;"&gt;&amp;lt;lambda&amp;gt;&lt;/SPAN&gt;: Line &lt;SPAN class="" style="color: #208ffb;"&gt;511&lt;/SPAN&gt;:   &lt;SPAN class="" style="color: #208ffb;"&gt;return&lt;/SPAN&gt; &lt;SPAN class="" style="color: #208ffb;"&gt;lambda&lt;/SPAN&gt; *args: val(*gp_fixargs(args, &lt;SPAN class="" style="color: #208ffb;"&gt;True&lt;/SPAN&gt;)) &lt;SPAN class="" style="color: #e75c58;"&gt;ExecuteError&lt;/SPAN&gt;: ERROR 999999: Something unexpected caused the tool to fail. Contact Esri Technical Support (http://esriurl.com/support) to Report a Bug, and refer to the error help for potential solutions or workarounds. Unable to initialize python raster function with scalar arguments. &lt;D&gt; Traceback (most recent call last):   File "D:\TrainingData\MaskRCNN_chips\models\Building_footprint_40epochsGPU\ArcGISInstanceDetector.py", line 169, in initialize     self.child_instance_detector.initialize(model, model_as_file)   File "C:\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\lib\site-packages\arcgis\learn\models\_inferencing\_maskrcnn_inferencing.py", line 158, in initialize     self.mask_rcnn = MaskRCNN.from_model(emd_path=model)   File "C:\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\lib\site-packages\arcgis\learn\models\_maskrcnn.py", line 215, in from_model     data = _EmptyData(path=emd_path.parent.parent, loss_func=None, c=len(class_mapping) + 1, chip_size=emd['ImageHeight'])   File "C:\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\lib\site-packages\arcgis\learn\models\_arcgis_model.py", line 60, in __init__     if getattr(arcgis.env, "_processorType", "") == "GPU" and torch.cuda.is_available(): NameError: name 'torch' is not defined Unable to initialize python raster function with scalar arguments. Failed to execute (DetectObjectsUsingDeepLearning).

I have tried various workarounds from similar threads but nothing so far. I am using a g3s.xlarge machine and remote desktop (windows machine) with GPU enabled.
I have verified that the GPU is being used by running:

cudaDevice=torch.cuda.current_device()
print ("GPU-Device: "+str(cudaDevice))
print ("GPU-Device-Info: "+str(torch.cuda.device(cudaDevice)))
print ("GPU-Device-Count: "+str(torch.cuda.device_count()))
print ("GPU-Device-Name: "+str(torch.cuda.get_device_name(cudaDevice)))
print ("GPU-Device-Availability: "+str(torch.cuda.is_available()))
#now some more info
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
print('Using device:', device)
print()
#Additional Info when using cuda
if device.type == 'cuda':
 print(torch.cuda.get_device_name(0))
 print('Memory Usage:')
 print('Allocated:', round(torch.cuda.memory_allocated(0)/1024**3,1), 'GB')
 print('Cached: ', round(torch.cuda.memory_cached(0)/1024**3,1), 'GB')

# use this to test: Run code, dont close,
# go to OS and run nvidia-smi to see process runs on GPU
print (torch.rand(3,3).cuda())
os.system('nvidia-smi.exe&amp;gt;c:/temp/log.txt')
with open(r'c:/temp/log.txt', 'r') as f:
 print(f.read())&lt;/D&gt;&lt;/PRE&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Resulting in:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;PRE class="lia-code-sample line-numbers language-none"&gt;GPU-Device: 0 GPU-Device-Info: &amp;lt;torch.cuda.device object at 0x000002B5B5DCD390&amp;gt; GPU-Device-Count: 1 GPU-Device-Name: Tesla M60 GPU-Device-Availability: True Using device: cuda  Tesla M60 Memory Usage: Allocated: 0.0 GB Cached:    0.0 GB tensor([[0.3166, 0.1292, 0.2083],         [0.2514, 0.0501, 0.4692],         [0.8568, 0.1868, 0.6476]], device='cuda:0')

Any thoughts?&lt;/PRE&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Sat, 11 Dec 2021 13:49:18 GMT</pubDate>
    <dc:creator>AsafEvenPaz</dc:creator>
    <dc:date>2021-12-11T13:49:18Z</dc:date>
    <item>
      <title>"Unable to initialize python raster function with scalar arguments" on an NVIDIA machine</title>
      <link>https://community.esri.com/t5/arcgis-notebooks-questions/quot-unable-to-initialize-python-raster-function/m-p/285887#M79</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I am trying to run a notebook given to me by Esri Support staff (case #&lt;SPAN style="color: #4c4c4c; background-color: #f8f8f8; font-weight: 300;"&gt;02587809) and when I try to run the&amp;nbsp;arcpy.ia.DetectObjectsUsingDeepLearning function I recieve the following error message:&lt;/SPAN&gt;&lt;/P&gt;&lt;PRE class="lia-code-sample line-numbers language-none"&gt;Line &lt;SPAN class="" style="color: #208ffb;"&gt;1&lt;/SPAN&gt;:     arcpy.ia.DetectObjectsUsingDeepLearning(imagery, &lt;SPAN class="" style="color: #ddb62b;"&gt;r&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;C:&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Users&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Administrator&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Documents&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;ArcGIS&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Projects&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Haiti_AI&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Haiti_AI.gdb&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;bldg_detected_jupyterGPU_10July2020&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #ddb62b;"&gt;r&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;D:&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;TrainingData&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;MaskRCNN_chips&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;models&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Building_footprint_40epochsGPU&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;\&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Building_footprint_40epochsGPU.emd&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;padding 64;batch_size 4;threshold 0.9;return_bboxes False&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;NO_NMS&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Confidence&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;Class&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #208ffb;"&gt;0&lt;/SPAN&gt;, &lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;PROCESS_AS_MOSAICKED_IMAGE&lt;/SPAN&gt;&lt;SPAN class="" style="color: #ddb62b;"&gt;"&lt;/SPAN&gt;)  File &lt;SPAN class="" style="color: #208ffb;"&gt;c:\program files\arcgis\pro\Resources\arcpy\arcpy\ia\Functions.py&lt;/SPAN&gt;, in &lt;SPAN class="" style="color: #00a250;"&gt;DetectObjectsUsingDeepLearning&lt;/SPAN&gt;: Line &lt;SPAN class="" style="color: #208ffb;"&gt;2888&lt;/SPAN&gt;:  processing_mode)  File &lt;SPAN class="" style="color: #208ffb;"&gt;c:\program files\arcgis\pro\Resources\arcpy\arcpy\sa\Utils.py&lt;/SPAN&gt;, in &lt;SPAN class="" style="color: #00a250;"&gt;swapper&lt;/SPAN&gt;: Line &lt;SPAN class="" style="color: #208ffb;"&gt;53&lt;/SPAN&gt;:    result = wrapper(*args, **kwargs)  File &lt;SPAN class="" style="color: #208ffb;"&gt;c:\program files\arcgis\pro\Resources\arcpy\arcpy\ia\Functions.py&lt;/SPAN&gt;, in &lt;SPAN class="" style="color: #00a250;"&gt;Wrapper&lt;/SPAN&gt;: Line &lt;SPAN class="" style="color: #208ffb;"&gt;2877&lt;/SPAN&gt;:  processing_mode)  File &lt;SPAN class="" style="color: #208ffb;"&gt;c:\program files\arcgis\pro\Resources\arcpy\arcpy\geoprocessing\_base.py&lt;/SPAN&gt;, in &lt;SPAN class="" style="color: #00a250;"&gt;&amp;lt;lambda&amp;gt;&lt;/SPAN&gt;: Line &lt;SPAN class="" style="color: #208ffb;"&gt;511&lt;/SPAN&gt;:   &lt;SPAN class="" style="color: #208ffb;"&gt;return&lt;/SPAN&gt; &lt;SPAN class="" style="color: #208ffb;"&gt;lambda&lt;/SPAN&gt; *args: val(*gp_fixargs(args, &lt;SPAN class="" style="color: #208ffb;"&gt;True&lt;/SPAN&gt;)) &lt;SPAN class="" style="color: #e75c58;"&gt;ExecuteError&lt;/SPAN&gt;: ERROR 999999: Something unexpected caused the tool to fail. Contact Esri Technical Support (http://esriurl.com/support) to Report a Bug, and refer to the error help for potential solutions or workarounds. Unable to initialize python raster function with scalar arguments. &lt;D&gt; Traceback (most recent call last):   File "D:\TrainingData\MaskRCNN_chips\models\Building_footprint_40epochsGPU\ArcGISInstanceDetector.py", line 169, in initialize     self.child_instance_detector.initialize(model, model_as_file)   File "C:\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\lib\site-packages\arcgis\learn\models\_inferencing\_maskrcnn_inferencing.py", line 158, in initialize     self.mask_rcnn = MaskRCNN.from_model(emd_path=model)   File "C:\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\lib\site-packages\arcgis\learn\models\_maskrcnn.py", line 215, in from_model     data = _EmptyData(path=emd_path.parent.parent, loss_func=None, c=len(class_mapping) + 1, chip_size=emd['ImageHeight'])   File "C:\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\lib\site-packages\arcgis\learn\models\_arcgis_model.py", line 60, in __init__     if getattr(arcgis.env, "_processorType", "") == "GPU" and torch.cuda.is_available(): NameError: name 'torch' is not defined Unable to initialize python raster function with scalar arguments. Failed to execute (DetectObjectsUsingDeepLearning).

I have tried various workarounds from similar threads but nothing so far. I am using a g3s.xlarge machine and remote desktop (windows machine) with GPU enabled.
I have verified that the GPU is being used by running:

cudaDevice=torch.cuda.current_device()
print ("GPU-Device: "+str(cudaDevice))
print ("GPU-Device-Info: "+str(torch.cuda.device(cudaDevice)))
print ("GPU-Device-Count: "+str(torch.cuda.device_count()))
print ("GPU-Device-Name: "+str(torch.cuda.get_device_name(cudaDevice)))
print ("GPU-Device-Availability: "+str(torch.cuda.is_available()))
#now some more info
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
print('Using device:', device)
print()
#Additional Info when using cuda
if device.type == 'cuda':
 print(torch.cuda.get_device_name(0))
 print('Memory Usage:')
 print('Allocated:', round(torch.cuda.memory_allocated(0)/1024**3,1), 'GB')
 print('Cached: ', round(torch.cuda.memory_cached(0)/1024**3,1), 'GB')

# use this to test: Run code, dont close,
# go to OS and run nvidia-smi to see process runs on GPU
print (torch.rand(3,3).cuda())
os.system('nvidia-smi.exe&amp;gt;c:/temp/log.txt')
with open(r'c:/temp/log.txt', 'r') as f:
 print(f.read())&lt;/D&gt;&lt;/PRE&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Resulting in:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;PRE class="lia-code-sample line-numbers language-none"&gt;GPU-Device: 0 GPU-Device-Info: &amp;lt;torch.cuda.device object at 0x000002B5B5DCD390&amp;gt; GPU-Device-Count: 1 GPU-Device-Name: Tesla M60 GPU-Device-Availability: True Using device: cuda  Tesla M60 Memory Usage: Allocated: 0.0 GB Cached:    0.0 GB tensor([[0.3166, 0.1292, 0.2083],         [0.2514, 0.0501, 0.4692],         [0.8568, 0.1868, 0.6476]], device='cuda:0')

Any thoughts?&lt;/PRE&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Sat, 11 Dec 2021 13:49:18 GMT</pubDate>
      <guid>https://community.esri.com/t5/arcgis-notebooks-questions/quot-unable-to-initialize-python-raster-function/m-p/285887#M79</guid>
      <dc:creator>AsafEvenPaz</dc:creator>
      <dc:date>2021-12-11T13:49:18Z</dc:date>
    </item>
    <item>
      <title>Re: "Unable to initialize python raster function with scalar arguments" on an NVIDIA machine</title>
      <link>https://community.esri.com/t5/arcgis-notebooks-questions/quot-unable-to-initialize-python-raster-function/m-p/285888#M80</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;The error is coming from&lt;SPAN style="font-size: 11.0pt;"&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN style="font-size: 10.5pt; color: black;"&gt;C:\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\lib\site-packages\arcgis\learn\models\_arcgis_model.py&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN style="font-size: 10.5pt; color: black;"&gt;Here '&lt;SPAN&gt;arcgispro-py3'&amp;nbsp;&lt;/SPAN&gt;is the default environment, you need to setup your&amp;nbsp; environment to use this tool.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P style="color: #3d3d3d;"&gt;I am pasting the current installation commands From the documentation page&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;A href="https://developers.arcgis.com/python/guide/install-and-set-up/" style="color: #2989c5; text-decoration: none;"&gt;here&lt;/A&gt;.&amp;nbsp;&lt;/P&gt;&lt;P style="color: #3d3d3d;"&gt;&lt;/P&gt;&lt;OL style="color: #3d3d3d; padding: 0px 0px 0px 30px;"&gt;&lt;LI style="margin: 0.2em 0px;"&gt;You need to first clone the default environment and activate the cloned environment, help page for the same is&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;A href="https://pro.arcgis.com/en/pro-app/arcpy/get-started/what-is-conda.htm" style="color: #2989c5; text-decoration: none;"&gt;here&lt;/A&gt;.&lt;/LI&gt;&lt;LI style="margin: 0.2em 0px;"&gt;You can then run the following command in python command prompt to install ArcGIS Python API with deep learning dependencies&lt;/LI&gt;&lt;/OL&gt;&lt;PRE style="color: #3d3d3d; font-size: 15px;"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;conda install -c esri -c fastai -c pytorch arcgis=1.8.2 scikit-image=0.15.0 pillow=6.2.2 libtiff=4.0.10 fastai=1.0.60 pytorch=1.4.0 torchvision=0.5.0 --no-pin&lt;/PRE&gt;&lt;P style="color: #3d3d3d;"&gt;&lt;/P&gt;&lt;P style="color: #3d3d3d;"&gt;Thanks,&lt;BR /&gt;Sandeep&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Tue, 28 Jul 2020 06:30:21 GMT</pubDate>
      <guid>https://community.esri.com/t5/arcgis-notebooks-questions/quot-unable-to-initialize-python-raster-function/m-p/285888#M80</guid>
      <dc:creator>Anonymous User</dc:creator>
      <dc:date>2020-07-28T06:30:21Z</dc:date>
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