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haodongli

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Lotus_Depth

like 60

Running on Zero

Just tried, seems working well now :)

Hi @dasmehdix , thanks so much for your interest! I have just tried the logs (please see below). I am not sure where is wrong...

Traceback (most recent call last):
  File "/usr/local/lib/python3.10/site-packages/spaces/zero/wrappers.py", line 256, in thread_wrapper
    res = future.result()
  File "/usr/local/lib/python3.10/concurrent/futures/_base.py", line 451, in result
    return self.__get_result()
  File "/usr/local/lib/python3.10/concurrent/futures/_base.py", line 403, in __get_result
    raise self._exception
  File "/usr/local/lib/python3.10/concurrent/futures/thread.py", line 58, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/home/user/app/app.py", line 24, in infer
    output_g, output_d = lotus(path_input, 'depth', seed, device)
  File "/home/user/app/infer.py", line 182, in lotus
    output_g = infer_pipe(pipe_g, image_input, task_name, seed, device)
  File "/home/user/app/infer.py", line 44, in infer_pipe
    pred = pipe(
  File "/usr/local/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/home/user/app/pipeline.py", line 1263, in __call__
    image = self.vae.decode(latents / self.vae.config.scaling_factor, return_dict=False, generator=generator)[
  File "/usr/local/lib/python3.10/site-packages/diffusers/utils/accelerate_utils.py", line 46, in wrapper
    return method(self, *args, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/diffusers/models/autoencoders/autoencoder_kl.py", line 303, in decode
    decoded = self._decode(z, return_dict=False)[0]
  File "/usr/local/lib/python3.10/site-packages/diffusers/models/autoencoders/autoencoder_kl.py", line 276, in _decode
    dec = self.decoder(z)
  File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/diffusers/models/autoencoders/vae.py", line 337, in forward
    sample = up_block(sample, latent_embeds)
  File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/diffusers/models/unets/unet_2d_blocks.py", line 2750, in forward
    hidden_states = upsampler(hidden_states)
  File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/diffusers/models/upsampling.py", line 180, in forward
    hidden_states = self.conv(hidden_states)
  File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 460, in forward
    return self._conv_forward(input, self.weight, self.bias)
  File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 456, in _conv_forward
    return F.conv2d(input, weight, bias, self.stride,
RuntimeError: NVML_SUCCESS == r INTERNAL ASSERT FAILED at "../c10/cuda/CUDACachingAllocator.cpp":844, please report a bug to PyTorch. 
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/site-packages/gradio/queueing.py", line 536, in process_events
    response = await route_utils.call_process_api(
  File "/usr/local/lib/python3.10/site-packages/gradio/route_utils.py", line 322, in call_process_api
    output = await app.get_blocks().process_api(
  File "/usr/local/lib/python3.10/site-packages/gradio/blocks.py", line 1935, in process_api
    result = await self.call_function(
  File "/usr/local/lib/python3.10/site-packages/gradio/blocks.py", line 1520, in call_function
    prediction = await anyio.to_thread.run_sync(  # type: ignore
  File "/usr/local/lib/python3.10/site-packages/anyio/to_thread.py", line 56, in run_sync
    return await get_async_backend().run_sync_in_worker_thread(
  File "/usr/local/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 2405, in run_sync_in_worker_thread
    return await future
  File "/usr/local/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 914, in run
    result = context.run(func, *args)
  File "/usr/local/lib/python3.10/site-packages/gradio/utils.py", line 826, in wrapper
    response = f(*args, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/spaces/zero/wrappers.py", line 214, in gradio_handler
    raise res.value
RuntimeError: NVML_SUCCESS == r INTERNAL ASSERT FAILED at "../c10/cuda/CUDACachingAllocator.cpp":844, please report a bug to PyTorch. 

I can not able to pass this image to space because of image resolution. Resolution of provided image is 3024x4032 which cause memory allocation error. I suggest you to append a resize function to prevent this allocation problems.

Got it, it is because that your image is too large, and caused OOM.

You can first resize your image and then you will get the depth/normal maps!