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import json
from functools import lru_cache
from typing import Any
import gradio as gr
import pandas as pd
from loguru import logger
from playground_examples import (
default_tokenizer_name_1,
default_tokenizer_name_2,
default_user_input,
examples,
)
from playground_tokenizers import TokenizerFactory
@lru_cache
def run_tokenization(
text: str, tokenizer_name: str, color_num: int = 5, add_special_token: bool = False
) -> tuple[list[tuple[str, str]], int, pd.DataFrame]:
"""Tokenize an input text and return the tokens with their positions."""
logger.info(
"param="
+ json.dumps(
{"text": text, "tokenizer_type": tokenizer_name}, ensure_ascii=False
)
)
pos_tokens = []
tokenizer = TokenizerFactory().get_tokenizer(tokenizer_name)
encoding = tokenizer.encode(text) if add_special_token else tokenizer.encode(text)
table = []
for idx, token_id in enumerate(encoding):
decoded_text = tokenizer.decode([token_id])
decoded_text = decoded_text.replace(
" ", "⋅"
) # replace space with ⋅ for better visualization
pos_tokens.extend([(decoded_text, str(idx % color_num))])
try:
token = tokenizer.decode([token_id])[0]
except:
token = {v: k for k, v in tokenizer.get_vocab().items()}[token_id]
if isinstance(token, bytes):
try:
token_str = token.decode("utf-8")
except:
token_str = token.decode("utf-8", errors="ignore")
logger.error(
f"{idx}: decode_error: {tokenizer_name}, {token} {token_str}"
)
elif isinstance(token, str):
token_str = token
else:
logger.error(
f"{idx}: wrong type for token {token_id} {type(token)} "
+ json.dumps(
{"text": text, "tokenizer_type": tokenizer_name}, ensure_ascii=False
)
)
token_str = token
table.append({"TokenID": token_id, "Text": decoded_text})
table_df = pd.DataFrame(table)
logger.info(f"tokenizer_type={tokenizer_name}, Tokens={table[:4]}")
return pos_tokens, len(encoding), table_df
def tokenize(
text: str, tokenizer_name: str, color_num: int = 5
) -> tuple[dict[Any, Any], pd.DataFrame]:
"""Tokenize an input text."""
pos_tokens, num_tokens, table_df = run_tokenization(text, tokenizer_name, color_num)
return gr.update(value=pos_tokens, label=f"Tokens: {num_tokens}"), table_df
def tokenize_pair(
text: str, tokenizer_name_1: str, tokenizer_name_2: str, color_num: int = 5
):
"""input_text.change."""
pos_tokens_1, table_df_1 = tokenize(
text=text, tokenizer_name=tokenizer_name_1, color_num=color_num
)
pos_tokens_2, table_df_2 = tokenize(
text=text, tokenizer_name=tokenizer_name_2, color_num=color_num
)
return pos_tokens_1, table_df_1, pos_tokens_2, table_df_2
def on_load(url_params: str, request: gr.Request | None = None) -> tuple[str, str, str]:
"""Function triggered on page load to get URL parameters."""
text = default_user_input
tokenizer_type_1 = default_tokenizer_name_1
tokenizer_type_2 = default_tokenizer_name_2
return text, tokenizer_type_1, tokenizer_type_2
get_window_url_params = """
function(url_params) {
const params = new URLSearchParams(window.location.search);
url_params = JSON.stringify(Object.fromEntries(params));
return url_params;
}
"""
all_tokenizer_name = [
(config.name_display, config.name_or_path)
for config in TokenizerFactory().all_tokenizer_configs
]
with gr.Blocks() as demo:
with gr.Row():
gr.Markdown("## Input Text")
dropdown_examples = gr.Dropdown(
sorted(examples.keys()),
value="Examples",
type="index",
allow_custom_value=True,
show_label=False,
container=False,
scale=0,
elem_classes="example-style",
)
user_input = gr.Textbox(
label="Input Text",
lines=5,
show_label=False,
)
with gr.Row():
with gr.Column(scale=6), gr.Group():
tokenizer_name_1 = gr.Dropdown(all_tokenizer_name, label="Tokenizer 1")
with gr.Column(scale=6), gr.Group():
tokenizer_name_2 = gr.Dropdown(all_tokenizer_name, label="Tokenizer 2")
with gr.Row():
with gr.Column():
output_text_1 = gr.Highlightedtext(
show_legend=False, show_inline_category=False
)
with gr.Column():
output_text_2 = gr.Highlightedtext(
show_legend=False, show_inline_category=False
)
with gr.Row():
output_table_1 = gr.Dataframe()
output_table_2 = gr.Dataframe()
tokenizer_name_1.change(
tokenize, [user_input, tokenizer_name_1], [output_text_1, output_table_1]
)
tokenizer_name_2.change(
tokenize, [user_input, tokenizer_name_2], [output_text_2, output_table_2]
)
user_input.change(
tokenize_pair,
[user_input, tokenizer_name_1, tokenizer_name_2],
[output_text_1, output_table_1, output_text_2, output_table_2],
show_api=False,
)
dropdown_examples.change(
lambda example_idx: (
examples[sorted(examples.keys())[example_idx]]["text"],
examples[sorted(examples.keys())[example_idx]]["tokenizer_1"],
examples[sorted(examples.keys())[example_idx]]["tokenizer_2"],
),
dropdown_examples,
[user_input, tokenizer_name_1, tokenizer_name_2],
show_api=False,
)
demo.load(
fn=on_load,
inputs=[user_input],
outputs=[user_input, tokenizer_name_1, tokenizer_name_2],
js=get_window_url_params,
show_api=False,
)
if __name__ == "__main__":
demo.launch(share=True)
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