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"""Run interactively."""
# pylint: disable=invalid-name, too-many-arguments, unused-argument, redefined-builtin, unused-import, wrong-import-position, too-many-locals, too-many-statements
from typing import Any, Tuple, Optional, Union # noqa
import sys
from pathlib import Path # noqa
import subprocess as sp
import shlex
import platform
import signal
from random import randint
from textwrap import dedent
from itertools import zip_longest
# import socket
from socket import socket, AF_INET, SOCK_STREAM
from sklearn.cluster import DBSCAN # noqa
import joblib
from varname import nameof
from icecream import install as ic_install, ic
import logzero
from logzero import logger
# import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt # noqa
# from tabulate import tabulate
from fastlid import fastlid
# for embeddable python
if "." not in sys.path:
sys.path.insert(0, ".")
import gradio as gr
# from radiobee.error_msg import error_msg
from radiobee.process_upload import process_upload
from radiobee.gradiobee import gradiobee
ic_install()
ic.configureOutput(
includeContext=True,
outputFunction=logger.info,
)
ic.enable()
# ic.disenable() # to turn off
sns.set()
sns.set_style("darkgrid")
fastlid.set_languages = ["en", "zh"]
signal.signal(signal.SIGINT, signal.SIG_DFL)
print("Press Ctrl+C to quit\n")
def savelzma(obj, fileloc: str = None):
"""Aux funciton."""
if fileloc is None:
fileloc = nameof(obj) # this wont work
joblib.dump(obj, f"data/{fileloc}.lzma")
def greet(input):
"""Greet yo."""
return f"'Sup yo! (your input: {input})"
def upfile1(file1, file2=None) -> Tuple[str, str]:
"""Upload file1, file2."""
del file2
return file1.name, f"'Sup yo! (your input: {input})"
def process_2upoads(file1, file2):
"""Process stuff."""
# return f"{process_upload(file1)}\n===***\n{process_upload(file2)}"
text1 = [_.strip() for _ in process_upload(file1).splitlines() if _.strip()]
text2 = [_.strip() for _ in process_upload(file2).splitlines() if _.strip()]
text1, text2 = zip(*zip_longest(text1, text2, fillvalue=""))
df = pd.DataFrame({"text1": text1, "text2": text2})
# return tabulate(df)
# return tabulate(df, tablefmt="grid")
# return tabulate(df, tablefmt='html')
return df
if __name__ == "__main__":
debug = True
# debug = False
uname = platform.uname()
# match = re.search(r'[a-z\d]{10,}', gethostname())
# hf spaces release: '4.14.248-189.473.amzn2.x86_64'
# match = re.search(r'[a-z\d]{10,}', node)
# if match and node.system.lower() in ["linux"]:
if "amzn2" in uname.release:
# likely hf spaces
server_name = "0.0.0.0"
debug = False
debug = True
share = True
# set UTC+8, probably wont work in hf spaces, no permission
try:
sp.check_output(shlex.split("ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime"))
except Exception as exc:
logger.error(" set timezonef failed: %s", exc)
else:
server_name = "127.0.0.1"
share = False
if debug:
logzero.loglevel(10)
logger.debug(" debug ")
logger.info(" info ")
# _ = """
inputs = [
gr.inputs.Textbox(
# placeholder="Input something here",
default="test text"
)
]
inputs = ["file", "file"]
inputs = [
gr.inputs.File(label="file 1"),
# gr.inputs.File(file_count="multiple", label="file 2", optional=True),
gr.inputs.File(label="file 2", optional=True),
]
_ = """
tf_type: Literal[linear, sqrt, log, binary] = 'linear'
idf_type: Optional[Literal[standard, smooth, bm25]] = None
dl_type: Optional[Literal[linear, sqrt, log]] = None
norm: norm: Optional[Literal[l1, l2]] = None
x min_df: int | float = 1
x max_df: int | float = 1.0
# """
input_tf_type = gr.inputs.Dropdown(
["linear", "sqrt", "log", "binary"], default="linear"
)
input_idf_type = gr.inputs.Radio(
["None", "standard", "smooth", "bm25"], default="None"
) # need to convert "None" this to None in fn
input_dl_type = gr.inputs.Radio(
["None", "linear", "sqrt", "log"], default="None"
) # ditto
input_norm_type = gr.inputs.Radio(["None", "l1", "l2"], default="None") # ditto
# modi inputs 1, definitions
sent_ali_algo = gr.inputs.Radio(["None", "fast", "slow"], default="None")
inputs = [ # tot. 9, meed to modify input of gradio & examples
gr.inputs.File(label="file 1"),
gr.inputs.File(label="file 2", optional=True),
input_tf_type, # modi inputs 2
input_idf_type,
input_dl_type,
input_norm_type,
gr.inputs.Slider(
minimum=1,
maximum=20,
step=0.1,
default=10,
),
gr.inputs.Slider(
minimum=1,
maximum=20,
step=1,
default=6,
),
sent_ali_algo,
]
examples = [
[
"data/test_zh.txt",
"data/test_en.txt",
"linear",
"None",
"None",
"None",
10,
6,
"None",
],
[
"data/test_zh.txt",
"data/test_en.txt",
"linear",
"None",
"None",
"None",
10,
6,
"fast",
],
[
"data/test_zh.txt",
"data/test_en.txt",
"linear",
"None",
"None",
"None",
10,
6,
"slow",
],
[
"data/test_en.txt",
"data/test_zh.txt",
"linear",
"None",
"None",
"None",
10,
6,
"None",
],
[
"data/shakespeare_zh500.txt",
"data/shakespeare_en500.txt",
"linear",
"None",
"None",
"None",
10,
6,
"None",
],
[
"data/shakespeare_en500.txt",
"data/shakespeare_zh500.txt",
"linear",
"None",
"None",
"None",
10,
6,
"None",
],
[
"data/hlm-ch1-zh.txt",
"data/hlm-ch1-en.txt",
"linear",
"None",
"None",
"None",
10,
6,
"None",
],
[
"data/hlm-ch1-en.txt",
"data/hlm-ch1-zh.txt",
"linear",
"None",
"None",
"None",
10,
6,
"None",
],
[
"data/ps-cn.txt",
"data/ps-en.txt",
"linear",
"None",
"None",
"None",
10,
4,
"None",
],
[
"data/test-dual.txt",
"data/empty.txt",
"linear",
"None",
"None",
"None",
10,
6,
"None",
],
[
"data/英译中国现代散文选1(汉外对照丛书).txt",
"data/empty.txt",
"linear",
"None",
"None",
"None",
10,
6,
"None",
],
[
"data/test-zh-ja.txt",
"data/empty.txt",
"linear",
"None",
"None",
"None",
10,
6,
"None",
],
[
"data/xiyouji-ch1-zh.txt",
"data/xiyouji-ch1-de.txt",
"linear",
"None",
"None",
"None",
10,
6,
"None",
],
[
"data/demian-hesse-de.txt",
"data/demian-hesse-en.txt",
"linear",
"None",
"None",
"None",
10,
6,
"None",
],
[
"data/catcher-in-the-rye-shixianrong-zh.txt",
"data/catcher-in-the-rye-boll-de.txt",
"linear",
"None",
"None",
"None",
10,
6,
"None",
],
]
# modi examples setup
outputs = ["dataframe", "plot"]
outputs = ["plot"]
outputs = ["dataframe", "plot"]
out_df = gr.outputs.Dataframe(
headers=None,
max_rows=12, # 20
max_cols=None,
overflow_row_behaviour="paginate",
type="auto",
label="To be aligned",
)
out_df_aligned = gr.outputs.Dataframe(
headers=None,
# max_rows=12, # 20
max_cols=3,
overflow_row_behaviour="paginate",
type="auto",
label="aligned pairs",
)
out_file_dl = gr.outputs.File(
label="Click to download csv",
)
out_file_dl_excel = gr.outputs.File(
label="Click to download xlsx",
)
out_sents_dl = gr.outputs.File(
label="Click to download sents csv",
)
out_sents_dl_excel = gr.outputs.File(
label="Click to download sents xlsx",
)
# modi outputs 1, definitions
# modi outputs 2, need to modify gradio error_msg
outputs = [ # tot. 8
out_df,
gr.outputs.Image(label="plot"),
out_file_dl,
out_file_dl_excel,
out_sents_dl,
out_sents_dl_excel,
out_df_aligned,
gr.outputs.HTML(),
]
# outputs = ["dataframe", "plot", "plot"] # wont work
# outputs = ["dataframe"]
# outputs = ["dataframe", "dataframe", ]
server_port = 7860
with socket(AF_INET, SOCK_STREAM) as sock:
sock.settimeout(0.01) # 10ms
# try numb times before giving up
numb = 5
for _ in range(numb):
if sock.connect_ex(("127.0.0.1", server_port)) != 0: # port idle
break
server_port = server_port + randint(0, 50)
else:
raise SystemExit(f"Tried {numb} times to no avail, giving up...")
description = "WIP showcasing a blazing fast dualtext aligner, currrently supported language pairs: en-zh/zh-en for fast-track, other language pairs are handled by slow-track"
# moved to userguide.rst in docs
article = dedent(
"""
## NB
* `radiobee aligner` is a sibling of `bumblebee aligner`. To know more about these aligners, please join qq group `316287378`.
* Uploaded files should be in pure text format (txt, md, csv etc). `docx`, `pdf`, `srt`, `html` etc may be supported later on.
* Click "Clear" first for subsequent submits when uploading files.
* `tf_type` `idf_type` `dl_type` `norm`: Normally there is no need to touch these unless you know what you are doing.
* Suggested `esp` and `min_samples` values -- `esp` (minimum epsilon): 8-12, `min_samples`: 4-8.
- Smaller larger `esp` or `min_samples` will result in more aligned pairs but also more **false positives** (pairs
falsely identified as candidates). On the other hand,
larger smaller `esp` or `min_samples` values tend to miss
'good' pairs.
* If you need to have a better look at the image, you can right-click on the image and select copy-image-address and open a new tab in the browser with the copied image address.
* `Flag`: Should something go wrong, you can click Flag to save the output and inform the developer.
"""
).strip()
article = dedent(
""" <p style="text-align: center">readiobee docs:
<a href="https://radiobee.readthedocs.io/" target="_blank">readthedocs</a>
or in Chinese but rather short <a href="https://radiobee.readthedocs.io/en/latest/userguide-zh.html#" target="_blank">中文使用说明</a>
</p>
"""
).strip()
css_image = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
# css = ".output_image, .input_image {height: 20rem !important; width: 100% !important;}"
css_input_file = ".input_file {height: 8rem !important; width: 100% !important;}"
css_output_file = ".output_file {height: 4rem !important; width: 100% !important;}"
logger.info("running at port %s", server_port)
_ = """
inputs = ...
outputs = ...
# properly
# define gradiobee to take inputs and spil out outputs
iface = gr.Interface(
fn=gradiobee,
inputs,
outputs,
)
# """
iface = gr.Interface(
# fn=greet,
# inputs="text",
# fn=process_upload,
# fn=process_2upoads,
# inputs=["file", "file"],
# outputs="text",
# outputs="html",
# fn=fn,
fn=gradiobee,
inputs=inputs,
outputs=outputs,
title="radiobee-aligner🔠",
description=description,
article=article,
examples=examples,
examples_per_page=4,
# theme="darkgrass",
theme="grass",
layout="vertical", # horizontal unaligned
allow_flagging="manual", # "auto"
flagging_options=[
"fatal",
"bug",
"brainstorm",
"excelsior",
], # "paragon"],
css=f"{css_image} {css_input_file} {css_output_file}",
enable_queue=True,
)
iface.launch(
share=share,
debug=debug,
show_error=True,
server_name=server_name,
# server_name="127.0.0.1",
server_port=server_port,
# show_tips=True,
enable_queue=True,
# height=150, # 500
width=900, # 900
)
_ = """
ax = sns.heatmap(cmat, cmap="viridis_r")
ax.invert_yaxis()
ax.set_xlabel(fastlid(df.text1)[0])
ax.set_xlabel(fastlid(df.text2)[0])
# return df, plt
return plt.gca()
https://colab.research.google.com/drive/1Gz9624VeAQLT7wlETgjOjPVURzQckXI0#scrollTo=qibtTvwecgsL colab gradio-file-inputs-upload.ipynb
iface = gr.Interface(plot_text, "file", "image")
def is_port_in_use(port):
import socket
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
return s.connect_ex(('localhost', port)) == 0
socket.socket(socket.AF_INET, socket.SOCK_STREAM).connect_ex(('127.0.0.1', 7911))
---
css https://huggingface.co/spaces/nielsr/LayoutLMv2-FUNSD/blob/main/app.py#L83
css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
#css = "@media screen and (max-width: 600px) { .output_image, .input_image {height:20rem !important; width: 100% !important;} }"
# css = ".output_image, .input_image {height: 600px !important}"
mod = 'en2zh'
packname = packx.__name__
globals()[mod] = getattr(importlib.import_module(f"{packname}.{mod}"), mod)
"""
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