jina-ai / dalle-flow

๐ŸŒŠ A Human-in-the-Loop workflow for creating HD images from text
grpcs://dalle-flow.dev.jina.ai
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Docker build ERROR: ResolutionImpossible and docker image FAILED to run. #149

Open dadmaan opened 1 year ago

dadmaan commented 1 year ago

Hi, I'm trying to build the docker image, running on 5.15.93-1-MANJARO with RTX 3090 24gb.

I got the following error:

ERROR: Cannot install -r requirements.txt (line 8), -r requirements.txt (line 9) and transformers 4.27.0.dev0 (from git+https://github.com/huggingface/transformers.git) because these package versions have conflicting dependencies.

The conflict is caused by: The user requested transformers 4.27.0.dev0 (from git+https://github.com/huggingface/transformers.git) vqgan-jax 0.0.1 depends on transformers dalle-mini 0.1.4 depends on transformers==4.25.1

To fix this you could try to:

  1. loosen the range of package versions you've specified
  2. remove package versions to allow pip attempt to solve the dependency conflict

ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts The command '/bin/sh -c if [ -n "${APT_PACKAGES}" ]; then apt-get update && apt-get install --no-install-recommends -y ${APT_PACKAGES}; fi && git clone --depth=1 https://github.com/jina-ai/SwinIR.git && git clone --depth=1 https://github.com/CompVis/latent-diffusion.git && git clone --depth=1 https://github.com/jina-ai/glid-3-xl.git && git clone --depth=1 --branch v0.0.15 https://github.com/AmericanPresidentJimmyCarter/stable-diffusion.git && cd dalle-flow && python3 -m virtualenv --python=/usr/bin/python3.10 env && . env/bin/activate && cd - && pip install --upgrade cython && pip install --upgrade pyyaml && git clone --depth=1 https://github.com/timojl/clipseg.git && pip install jax[cuda11_cudnn82]~=0.3.24 -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html && pip uninstall -y torch torchvision torchaudio && pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116 && pip install PyYAML numpy tqdm pytorch_lightning einops numpy omegaconf && pip install https://github.com/crowsonkb/k-diffusion/archive/master.zip && pip install basicsr facexlib gfpgan && pip install realesrgan && pip install https://github.com/AmericanPresidentJimmyCarter/xformers-builds/raw/master/cu116/xformers-0.0.14.dev0-cp310-cp310-linux_x86_64.whl && cd latent-diffusion && pip install --timeout=1000 -e . && cd - && cd glid-3-xl && pip install --timeout=1000 -e . && cd - && cd dalle-flow && pip install --timeout=1000 --compile -r requirements.txt && cd - && cd stable-diffusion && pip install --timeout=1000 -e . && cd - && cd SwinIR && pip install --timeout=1000 -e . && cd - && cd clipseg && pip install --timeout=1000 -e . && cd - && cd glid-3-xl && if [ -n "${APT_PACKAGES}" ]; then apt-get remove -y --auto-remove ${APTPACKAGES} && apt-get autoremove && apt-get clean && rm -rf /var/lib/apt/lists/*; fi' returned a non-zero code: 1**

Based on the above output, I resolved the issue and built the image by updating the "requirement.txt" file with the following line : git+https://github.com/huggingface/transformers.git@v4.25.1#egg=transformers

However, the docker failed to run. It gives me the following output:

/dalle/dalle-flow/env/bin/jina flow --uses
flow.tmp.yml
โ•ญโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ•ฎ โ”‚ Argument โ”‚ Value โ”‚ โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค โ”‚ cli โ”‚ flow โ”‚ โ”‚ env โ”‚ None โ”‚ โ”‚ inspect โ”‚ COLLECT โ”‚ โ”‚ log-config โ”‚ default โ”‚ โ”‚ name โ”‚ None โ”‚ โ”‚ quiet โ”‚ False โ”‚ โ”‚ quiet-error โ”‚ False โ”‚ โ”‚ reload โ”‚ False โ”‚ โ”‚ uses โ”‚ flow.tmp.yml โ”‚ โ”‚ workspace โ”‚ None โ”‚ โ”‚ workspace-id โ”‚ b8c9cfe07098400ba5e9883942d18ce4 โ”‚ โ•ฐโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ•ฏ Docker daemon doesn't seem to be running. Please run the Docker daemon and try again. DEBUG dalle/rep-0@13 waiting for ready or shutdown signal from runtime [02/13/23 13:30:57] DEBUG dalle/rep-0@13 Runtime was never started. Runtime will end gracefully on its own
DEBUG dalle/rep-0@13 terminating the runtime process
DEBUG dalle/rep-0@13 runtime process properly terminated
DEBUG dalle/rep-0@13 terminated
DEBUG dalle/rep-0@13 joining the process
wandb: Appending key for api.wandb.ai to your netrc file: /home/dalle/.netrc wandb: Tracking run with wandb version 0.13.10 wandb: Run data is saved locally in /dalle/dalle-flow/wandb/run-20230213_133101-2mjmuoyo wandb: Run wandb offline to turn off syncing. wandb: Syncing run wise-lion-1 wandb: โญ View project at https://wandb.ai/anony-mouse-493605/uncategorized?apiKey=1c10c31e4c9ad97a71028cd53ca3b5bd4d60d776 wandb: ๐Ÿš€ View run at https://wandb.ai/anony-mouse-493605/uncategorized/runs/2mjmuoyo?apiKey=1c10c31e4c9ad97a71028cd53ca3b5bd4d60d776 wandb: WARNING Do NOT share these links with anyone. They can be used to claim your runs. wandb: Downloading large artifact mega-1-fp16:latest, 4938.53MB. 7 files... wandb: 7 of 7 files downloaded.
Done. 0:0:1.6 DeprecationWarning: the load_module() method is deprecated and slated for removal in Python 3.12; use exec_module() instead (raised from :283) Some of the weights of DalleBart were initialized in float16 precision from the model checkpoint at /tmp/tmph4lddlm0: [('lm_head', 'kernel'), ('model', 'decoder', 'embed_positions', 'embedding'), ('model', 'decoder', 'embed_tokens', 'embedding'), ('model', 'decoder', 'final_ln', 'bias'), ('model', 'decoder', 'layernorm_embedding', 'bias'), ('model', 'decoder', 'layernorm_embedding', 'scale'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'FlaxBartAttention_0', 'k_proj', 'kernel'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'FlaxBartAttention_0', 'out_proj', 'kernel'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'FlaxBartAttention_0', 'q_proj', 'kernel'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'FlaxBartAttention_0', 'v_proj', 'kernel'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'FlaxBartAttention_1', 'k_proj', 'kernel'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'FlaxBartAttention_1', 'out_proj', 'kernel'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'FlaxBartAttention_1', 'q_proj', 'kernel'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'FlaxBartAttention_1', 'v_proj', 'kernel'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'GLU_0', 'Dense_0', 'kernel'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'GLU_0', 'Dense_1', 'kernel'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'GLU_0', 'Dense_2', 'kernel'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'GLU_0', 'LayerNorm_0', 'bias'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'GLU_0', 'LayerNorm_1', 'bias'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'LayerNorm_0', 'bias'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'LayerNorm_1', 'bias'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'LayerNorm_1', 'scale'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'LayerNorm_2', 'bias'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'LayerNorm_3', 'bias'), ('model', 'decoder', 'layers', 'FlaxBartDecoderLayers', 'LayerNorm_3', 'scale'), ('model', 'encoder', 'embed_positions', 'embedding'), ('model', 'encoder', 'embed_tokens', 'embedding'), ('model', 'encoder', 'final_ln', 'bias'), ('model', 'encoder', 'layernorm_embedding', 'bias'), ('model', 'encoder', 'layernorm_embedding', 'scale'), ('model', 'encoder', 'layers', 'FlaxBartEncoderLayers', 'FlaxBartAttention_0', 'k_proj', 'kernel'), ('model', 'encoder', 'layers', 'FlaxBartEncoderLayers', 'FlaxBartAttention_0', 'out_proj', 'kernel'), ('model', 'encoder', 'layers', 'FlaxBartEncoderLayers', 'FlaxBartAttention_0', 'q_proj', 'kernel'), ('model', 'encoder', 'layers', 'FlaxBartEncoderLayers', 'FlaxBartAttention_0', 'v_proj', 'kernel'), ('model', 'encoder', 'layers', 'FlaxBartEncoderLayers', 'GLU_0', 'Dense_0', 'kernel'), ('model', 'encoder', 'layers', 'FlaxBartEncoderLayers', 'GLU_0', 'Dense_1', 'kernel'), ('model', 'encoder', 'layers', 'FlaxBartEncoderLayers', 'GLU_0', 'Dense_2', 'kernel'), ('model', 'encoder', 'layers', 'FlaxBartEncoderLayers', 'GLU_0', 'LayerNorm_0', 'bias'), ('model', 'encoder', 'layers', 'FlaxBartEncoderLayers', 'GLU_0', 'LayerNorm_1', 'bias'), ('model', 'encoder', 'layers', 'FlaxBartEncoderLayers', 'LayerNorm_0', 'bias'), ('model', 'encoder', 'layers', 'FlaxBartEncoderLayers', 'LayerNorm_1', 'bias'), ('model', 'encoder', 'layers', 'FlaxBartEncoderLayers', 'LayerNorm_1', 'scale')] You should probably UPCAST the model weights to float32 if this was not intended. See [~FlaxPreTrainedModel.to_fp32] for further information on how to do this. device count: 1 wandb: Downloading large artifact mega-1-fp16:latest, 4938.53MB. 7 files... wandb: 7 of 7 files downloaded.
Done. 0:0:1.6 DEBUG dalle/rep-0@38 <user_module.dalle.DalleGenerator object at 0x7f4d9c55d480> is successfully loaded! [02/13/23 13:31:20] DEBUG dalle/rep-0@38 start listening on 0.0.0.0:64757
DEBUG dalle/rep-0@38 Received signal SIGTERM
DEBUG dalle/rep-0@38 process terminated
DEBUG dalle/rep-0@13 successfully joined the process

Any ideas?