pmh47 / dirt

DIRT: a fast differentiable renderer for TensorFlow
MIT License
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Error while running sanity test #91

Closed man1989 closed 3 years ago

man1989 commented 3 years ago

When i am running python tests/square_test.py i am getting below error

traceback (most recent call last):
  File "tests/square_test.py", line 61, in <module>
    main()
  File "tests/square_test.py", line 47, in main
    dirt_pixels = get_dirt_pixels().eval()
  File "/miniconda3/envs/py2/lib/python2.7/site-packages/tensorflow_core/python/framework/ops.py", line 798, in eval
    return _eval_using_default_session(self, feed_dict, self.graph, session)
  File "<USER_HOME>/miniconda3/envs/py2/lib/python2.7/site-packages/tensorflow_core/python/framework/ops.py", line 5407, in _eval_using_default_session
    return session.run(tensors, feed_dict)
  File "<USER_HOME>/miniconda3/envs/py2/lib/python2.7/site-packages/tensorflow_core/python/client/session.py", line 956, in run
    run_metadata_ptr)
  File "<USER_HOME>/miniconda3/envs/py2/lib/python2.7/site-packages/tensorflow_core/python/client/session.py", line 1180, in _run
    feed_dict_tensor, options, run_metadata)
  File "<USER_HOME>/miniconda3/envs/py2/lib/python2.7/site-packages/tensorflow_core/python/client/session.py", line 1359, in _do_run
    run_metadata)
  File "<USER_HOME>/miniconda3/envs/py2/lib/python2.7/site-packages/tensorflow_core/python/client/session.py", line 1384, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: No OpKernel was registered to support Op 'Rasterise' used by node Rasterise/RasteriseBatch (defined at <USER_HOME>/miniconda3/envs/py2/lib/python2.7/site-packages/tensorflow_core/python/framework/ops.py:1748) with these attrs: [channels=1, width=128, height=128]
Registered devices: [CPU, XLA_CPU, XLA_GPU]
Registered kernels:
  device='GPU'miniconda3

         [[Rasterise/RasteriseBatch]]

I am using tensorflow==1.15.0 and tensorflow-gpu==1.15.0 and python 2.7

pmh47 commented 3 years ago

This is not an issue with DIRT; rather, tensorflow cannot see your gpu.