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FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04
#FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu16.04
#FROM nvidia/cuda:8.0-cudnn7-devel-ubuntu16.04
#FROM pytorch/pytorch:1.1.0-cuda10.0-cudnn7.5-devel 

ENV LANG C.UTF-8
ENV NVIDIA_VISIBLE_DEVICES 0
ENV NVIDIA_DRIVER_CAPABILITIES utility,compute
#ENV CUDA_PATH /usr/local/cuda
ENV CUDA_ROOT /usr/local/cuda

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julia> using CuArrays
Internal error: encountered unexpected error in runtime:
BoundsError(a=Array{Core.Compiler.BasicBlock, (32,)}[
  Core.Compiler.BasicBlock(stmts=Core.Compiler.StmtRange(first=1, last=7), preds=Array{Int64, (1,)}[32], succs=Array{Int64, (1,)}[2]),
  Core.Compiler.BasicBlock(stmts=Core.Compiler.StmtRange(first=8, last=14), preds=Array{Int64, (1,)}[1], succs=Array{Int64, (2,)}[5, 3]),
  Core.Compiler.BasicBlock(stmts=Core.Compiler.StmtRange(first=15, last=20), preds=Array{Int64, (1,)}[2], succs=Array{Int64, (1,)}[4]),
  Core.Compiler.BasicBlock(stmts=Core.Compiler.StmtRange(first=21, last=21), preds=Array{Int64, (1,)}[3], succs=Array{Int64, (1,)}[7]),
  Core.Compiler.BasicBlock(stmts=Core.Compiler.StmtRange(first=22, last=28), preds=Array{Int64, (1,)}[2], succs=Array{Int64, (1,)}[6]),
  Core.Compiler.BasicBlock(stmts=Core.Compiler.StmtRange(first=29, last=29), preds=Array{Int64, (1,)}[5], succs=Array{Int64, (1,)}[7]),
  Core.Compiler.BasicBlock(stmts=Core.Compiler.StmtRange(first=30, last=47

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参考: https://cppx.hatenablog.com/entry/2019/01/29/134251
https://qiita.com/tatsuya11bbs/items/70205b070c7afd7dd651

既存のドライバ等を削除

sudo apt --purge remove nvidia-*
sudo apt --purge remove cuda-*

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FROM tensorflow/tensorflow:2.0.0-gpu-py3
WORKDIR /libtopicmodel
COPY . /libtopicmodel/
#RUN pip3 install poetry==1.0.0b8 
#RUN poetry install 

FROM nvidia/cuda:10.1-cudnn7-devel-ubuntu18.04
ARG PYTHON_VERSION=3.7
RUN apt-get update && apt-get install -y --no-install-recommends \
         build-essential \

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import numpy as np
from scipy.special import softmax as np_softmax

def term_score(beta:np.array, dtype=np.float32) -> np.array:
    """reference: http://db-event.jpn.org/deim2011/proceedings/pdf/f4-1.pdf
    """
    β = np.array(beta)
    (K,V) = beta.shape
    if not (K-0.3) < beta.sum() < (K+0.3):
        β = np_softmax(beta, axis=-1)

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2 50
the 0.418 0.24968 -0.41242 0.1217 0.34527 -0.044457 -0.49688 -0.17862 -0.00066023 -0.6566 0.27843 -0.14767 -0.55677 0.14658 -0.0095095 0.011658 0.10204 -0.12792 -0.8443 -0.12181 -0.016801 -0.33279 -0.1552 -0.23131 -0.19181 -1.8823 -0.76746 0.099051 -0.42125 -0.19526 4.0071 -0.18594 -0.52287 -0.31681 0.00059213 0.0074449 0.17778 -0.15897 0.012041 -0.054223 -0.29871 -0.15749 -0.34758 -0.045637 -0.44251 0.18785 0.0027849 -0.18411 -0.11514 -0.78581
, 0.013441 0.23682 -0.16899 0.40951 0.63812 0.47709 -0.42852 -0.55641 -0.364 -0.23938 0.13001 -0.063734 -0.39575 -0.48162 0.23291 0.090201 -0.13324 0.078639 -0.41634 -0.15428 0.10068 0.48891 0.31226 -0.1252 -0.037512 -1.5179 0.12612 -0.02442 -0.042961 -0.28351 3.5416 -0.11956 -0.014533 -0.1499 0.21864 -0.33412 -0.13872 0.31806 0.70358 0.44858 -0.080262 0.63003 0.32111 -0.46765 0.22786 0.36034 -0.37818 -0.56657 0.044691 0.30392

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import io, os, requests
from typing import Callable, Optional,Any
import numpy as np 
import pandas as pd 
import torch
import pytorch_lightning as pl 
import fugashi 
from tqdm.auto import tqdm 
from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer

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[project]
name = "topics"
version = "0.1.0"
description = "Add a short description here"
dependencies = [
    "numpy>=1.24.4",
    "scipy>=1.10.1",
    "pandas>=2.0.3",
    "matplotlib>=3.7.2",
    "plotly>=5.15.0",