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Model initialization step within colab using tpu and default configuration exits with error. #24

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owenschris opened this issue Apr 11, 2022 · 7 comments

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@owenschris
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Model initialization step within colab using tpu and default configuration exits with error.

Errors are nested through jax and hypernerf, but it appear that the root is

accum_prod = jnp.concatenate([

within the volumetric_rendering function, jnp.broadcast_to([last_sample_z], z_vals[..., :1].shape).

The relevant error is

/usr/local/lib/python3.7/dist-packages/hypernerf/model_utils.py in volumetric_rendering(rgb, sigma, z_vals, dirs, use_white_background, sample_at_infinity, eps)
113 z_vals[..., 1:] - z_vals[..., :-1],
--> 114 jnp.broadcast_to([last_sample_z], z_vals[..., :1].shape)
115 ], -1)

/usr/local/lib/python3.7/dist-packages/jax/_src/numpy/util.py in _broadcast_to(arr, shape)
341 return arr.broadcast_to(shape)
--> 342 _check_arraylike("broadcast_to", arr)
343 arr = arr if isinstance(arr, ndarray) else _asarray(arr)

/usr/local/lib/python3.7/dist-packages/jax/_src/numpy/util.py in _check_arraylike(fun_name, *args)
294 msg = "{} requires ndarray or scalar arguments, got {} at position {}."
--> 295 raise TypeError(msg.format(fun_name, type(arg), pos))
296

UnfilteredStackTrace: TypeError: broadcast_to requires ndarray or scalar arguments, got <class 'list'> at position 0.

The stack trace below excludes JAX-internal frames.
The preceding is the original exception that occurred, unmodified.

A quick search brought up things like https://jax.readthedocs.io/en/latest/notebooks/Common_Gotchas_in_JAX.html#non-array-inputs-numpy-vs-jax which suggested all elements should be converted to the jnp arrays. Haven't gotten it working yet, though.

@saunair
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saunair commented Apr 11, 2022

I got it to work by changing the line to: jnp.broadcast_to(jnp.array([last_sample_z]), z_vals[..., :1].shape)

treder added a commit to treder/nerfies that referenced this issue Apr 15, 2022
@corlangerak
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saunair

Could you maybe share your version of the Colab notebook. I am still experiencing issues after changing the line to your suggestion... Thanks a lot for the help! :)

@saunair
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saunair commented Apr 22, 2022

Hey @corlangerak, did you remove the pip install hypernerf line in the collab notebook? Because changing the line locally wouldn't reflect the change(You'll be loading the hypernerf pip install instead).
I suggest

  1. Copying the notebook out of the notebook folder (basically into the project's root folder i.e. hypernerf/my_notebook.ipynb instead of hypernerf/notebooks/my_notebook.ipynb).
  2. Apply the fix I suggested, and then run the notebook/collab.

@hsauod
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hsauod commented Jun 17, 2022

@saunair Hi Nair, I faced the same issue. I tried to changed the line you suggested above though. Is it possible for you that giving me a little bit more specific instructions ?
Thank you in advance, Nair.

@saunair
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saunair commented Jun 18, 2022

@hsauod
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hsauod commented Jun 18, 2022

@hsauod check these two changes: ae29d1d#diff-433be35a4beb7eeee9224dcbe28ec97d53330cd175060905cd5217863674003cR114

and check the second cell in my notebook here: https://github.com/saunair/hypernerf/blob/main/notebooks/HyperNeRF_Training.ipynb

@corlangerak here you go. Sorry about the delay

@saunair Hi Nair, thank you very much for your kindly explanation

@silvercondor
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Hi, incase anyone run into error, quick fix for colab is to install @saunair version of hypernerf

in cell 1 replace
!pip install git+https://github.com/google/hypernerf

with
!pip install git+https://github.com/saunair/hypernerf

Thanks again to @saunair for fixing error

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