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# coding=utf-8
# author: xusong
# time: 2022/8/23 16:06

"""

plots

table

## related demo
- [](http://text-processing.com/demo/tokenize/)
- [gpt-tokenizer](https://gpt-tokenizer.dev/)
- [llama-tokenizer-js](https://belladoreai.github.io/llama-tokenizer-js/example-demo/build/)
- [](https://huggingface.co/spaces/Xenova/the-tokenizer-playground)

## 可视化

[ The, 2, QUICK, Brown, Foxes, jumped, over, the, lazy, dog's, bone ]
"""

import json
import pandas as pd
import gradio as gr

from vocab import all_tokenizers, load_tokener

# 显示空格:https://blog.csdn.net/liuxiao723846/article/details/118994673
# 隐藏legend:
css = """
.space-show {white-space: pre-wrap;}
.cell-wrap {white-space: pre-wrap;}
.category-legend {display: none !important}
.statistics textarea {min-width: min(50px,100%) !important; font-size: 20px !important; font-weight: 600 !important; text-align: center !important; border: none !important;}
.statistics label {text-align: center !important;}
"""

example_text = """Replace this text in the input field to see how tokenization works
华为智能音箱发布:华为Sound X"""

# llama chatglm_6b gpt_nexo_20b baichuan  baichuan_7b
examples = [
    ["空格测试:  2个空格        8个空格", "llama", "chatglm_6b"],  # chatglm 有blank_n,
    ["标点测试:,。!?;", "baichuan_7b", "llama"],
    ["符号测试:🦙", "baichuan_7b", "llama"],
    ["中文测试:🦙", "baichuan_7b", "llama"],
    ["数字测试:(10086 + 98) = 100184", "baichuan_7b", "llama"],
]



def tokenize(text, tokenizer_type, color_num=5):
    """
    TODO: cache tokenizer
    """
    print(text, tokenizer_type)
    pos_tokens = []
    tokenizer = load_tokener(tokenizer_type)
    encoding = tokenizer.encode(text)

    table = []

    for idx, token_id in enumerate(encoding):
        decode_text = tokenizer.decode([token_id])  # 特殊字符解码后会统一变成 �,对应 "\ufffd"
        pos_tokens.extend([(decode_text, str(idx % color_num))])

        # token  "Byte":  # 这是 utf-8编码吧?
        token = tokenizer.convert_ids_to_tokens([token_id])[0]
        if isinstance(token, bytes):
            try:
                token_str = token.decode("utf-8")
            except:
                token_str = token.decode("utf-8", errors="ignore")
                print("decode_error", token, token_str)

            token_bytes = token
            json_dumps = json.dumps(token_str)
        elif isinstance(token, str):
            token_str = token
            token_bytes = bytes(token_str, "utf-8")
            json_dumps = json.dumps(token_str)
        else:
            return



        table.append(
            {"TokenID": token_id,
             "⭐Token": token_str,  # utf-8解码后的字符串,为什么有些是 <0xE7>,表示什么?比如llama
             "Text": decode_text,  #
             # "Bytes": token_bytes,  # bytes类型在gradio前端页面被解码成字符串,比如   b'\xe4\xb8\xad' 仍然显示成 "中"。因此 str(token_bytes)
             "Bytes": str(token_bytes),
             # "Unicode": json_dumps  # unicode, 如果是ascii码,就直接显示。如果不是ascii码,就显示unicode
             }
        )

    table_df = pd.DataFrame(table)
    print(table)
    # print(table_df)

    return pos_tokens, table_df, len(encoding)


def tokenize_pair(text, tokenizer_type_1, tokenizer_type_2):
    pos_tokens_1, table_df_1, token_size_1 = tokenize(text, tokenizer_type_1)
    pos_tokens_2, table_df_2, token_size_2 = tokenize(text, tokenizer_type_2)
    return pos_tokens_1, table_df_1, token_size_1, pos_tokens_2, table_df_2, token_size_2


def get_vocab_size(tokenizer_type):
    tokenizer = load_tokener(tokenizer_type)
    return tokenizer.vocab_size

def test_coding():
    bytes1 = b'\xe4\xb8\xad'
    print(bytes1)  # b'\xe4\xb8\xad'


with gr.Blocks(css=css) as demo:
    gr.HTML("""<h1 align="center">Tokenizer Arena ⚔️</h1>""")
    # links: https://www.coderstool.com/utf8-encoding-decoding
    # 功能:输入文本,进行分词
    # 分词器:常见的分词器有集中,
    # 背景:方便分词、看词粒度、对比
    #
    # Byte: 表示分词


    gr.Markdown("## Input Text")
    user_input = gr.Textbox(
        value=example_text,
        label="Input Text",
        lines=5,
        show_label=False,
    )  # placeholder="Enter sentence here..."

    # submitBtn = gr.Button("生成回复", variant="primary")

    gr.Markdown("## Tokenization")

    with gr.Row():
        with gr.Column(scale=6):
            with gr.Group():
                tokenizer_type_1 = gr.Dropdown(
                    all_tokenizers,
                    value="llama",
                    label="Tokenizer 1",
                )
                with gr.Group():
                    """
                    <div class="stat"><div class="stat-value">69</div><div class="stat-label">Characters</div></div>
                    """
                    with gr.Row():
                        stats_vocab_size_1 = gr.TextArea(
                            label="VocabSize",
                            lines=1,
                            elem_classes="statistics"
                        )
                        stats_token_size_1 = gr.TextArea(
                            label="Tokens",
                            lines=1,
                            elem_classes="statistics"
                        )
                        stats_3 = gr.TextArea(
                            label="Compress Rate",
                            lines=1,
                            elem_classes="statistics"
                        )
        # https://www.onlinewebfonts.com/icon/418591
        gr.Image("images/VS.svg", scale=1, show_label=False, show_download_button=False, container=False) # height=10,
        with gr.Column(scale=6):
            with gr.Group():
                tokenizer_type_2 = gr.Dropdown(
                    all_tokenizers,
                    value="baichuan_7b",
                    label="Tokenizer 2",
                )
                with gr.Group():
                    with gr.Row():
                        stats_vocab_size_2 = gr.TextArea(
                            label="VocabSize",
                            lines=1,
                            elem_classes="statistics"
                        )
                        stats_token_size_2 = gr.TextArea(
                            label="Tokens",
                            lines=1,
                            elem_classes="statistics"
                        )
                        stats_6 = gr.TextArea(
                            label="Compress Rate",
                            lines=1,
                            elem_classes="statistics"
                        )



    # TODO: 图 表 压缩率
    with gr.Row():
        with gr.Column():
            output_text_1 = gr.Highlightedtext(
                label="Tokens 1",
                show_legend=True,
                elem_classes="space-show"
            )
        with gr.Column():
            output_text_2 = gr.Highlightedtext(
                label="Tokens 2",
                show_legend=True,
                elem_classes="space-show"
            )

    with gr.Row():
        output_table_1 = gr.Dataframe(
            headers=["TokenID", "Byte", "Text"],
            datatype=["str", "str", "str"],
            # elem_classes="space-show",   # 给整个Dataframe加这个css不起作用,因此直接修改cell-wrap
        )
        output_table_2 = gr.Dataframe(
            headers=["TokenID", "Token", "Text"],
            datatype=["str", "str", "str"],
        )

    tokenizer_type_1.change(tokenize, [user_input, tokenizer_type_1], [output_text_1, output_table_1, stats_token_size_1])
    tokenizer_type_1.change(get_vocab_size, [tokenizer_type_1], [stats_vocab_size_1])

    user_input.change(tokenize_pair,
                      [user_input, tokenizer_type_1, tokenizer_type_2],
                      [output_text_1, output_table_1, stats_token_size_1, output_text_2, output_table_2, stats_token_size_2])

    tokenizer_type_2.change(tokenize, [user_input, tokenizer_type_2], [output_text_2, output_table_2, stats_token_size_2])
    tokenizer_type_2.change(get_vocab_size, [tokenizer_type_2], [stats_vocab_size_2])

    gr.Examples(
        examples,
        [user_input, tokenizer_type_1, tokenizer_type_2],
        [output_text_1, output_table_1, stats_token_size_1, output_text_2, output_table_2, stats_token_size_2],
        tokenize_pair,
        cache_examples=True,
    )

    # submitBtn.click(tokenize, [user_input, tokenizer_type], outputs,
    #                 show_progress=True)

    # examples=[
    #     ["What a beautiful morning for a walk!"],
    #     ["It was the best of times, it was the worst of times."],
    #     ["多个空格    It  ss  was the best of times, it was the worst of times."],
    # ]

if __name__ == "__main__":
    demo.launch()