Commit 5034f7d7 authored by Liam's avatar Liam
Browse files

added token counter next to txt2img and img2img prompts

parent ca3e5519

javascript/helpers.js

0 → 100644
+13 −0
Original line number Diff line number Diff line 
// helper functions



function debounce(func, wait_time) {

	let timeout;

	return function wrapped(...args) {

		let call_function = () => {

			clearTimeout(timeout);

			func(...args)

		}

		clearTimeout(timeout);

		timeout = setTimeout(call_function, wait_time);

	};

}
 
 No newline at end of file

javascript/ui.js

+47 −0
Original line number Diff line number Diff line
@@ -183,4 +183,51 @@ onUiUpdate(function(){ 
    });



    json_elem.parentElement.style.display="none"



	let debounce_time = 800

	if (!txt2img_textarea) {

		txt2img_textarea = gradioApp().querySelector("#txt2img_prompt > label > textarea")

		txt2img_textarea?.addEventListener("input", debounce(submit_prompt_text.bind(null, "txt2img"), debounce_time))

	}

	if (!img2img_textarea) {

		img2img_textarea = gradioApp().querySelector("#img2img_prompt > label > textarea")

		img2img_textarea?.addEventListener("input", debounce(submit_prompt_text.bind(null, "img2img"), debounce_time))

    }

})





let txt2img_textarea, img2img_textarea = undefined;

function submit_prompt_text(source, e) {

	let prompt_text;

	if (source == "txt2img")

		prompt_text = txt2img_textarea.value;

	else if (source == "img2img")

		prompt_text = img2img_textarea.value;

	if (!prompt_text)

		return;

	params = {

		method: "POST",

		headers: {

			"Accept": "application/json",

			"Content-type": "application/json"

		},

		body: JSON.stringify({data:[prompt_text]})

	}

	fetch('http://127.0.0.1:7860/api/tokenize/', params)

	.then((response) => response.json())

	.then((data) => {

		if (data?.data.length) {

			let response_json = data.data[0]

			if (elem = gradioApp().getElementById(source+"_token_counter")) {

				if (response_json.token_count > response_json.max_length)

					elem.classList.add("red");

				else

					elem.classList.remove("red");

				elem.innerText = response_json.token_count + "/" + response_json.max_length;

			}

		}

	})

	.catch((error) => {

		console.error('Error:', error);

	});

}
 
 No newline at end of file

modules/sd_hijack.py

+22 −8
Original line number Diff line number Diff line
@@ -180,6 +180,7 @@ class StableDiffusionModelHijack: 
    dir_mtime = None

    layers = None

    circular_enabled = False

    clip = None



    def load_textual_inversion_embeddings(self, dirname, model):

        mt = os.path.getmtime(dirname)
@@ -242,6 +243,7 @@ class StableDiffusionModelHijack: 


        model_embeddings.token_embedding = EmbeddingsWithFixes(model_embeddings.token_embedding, self)

        m.cond_stage_model = FrozenCLIPEmbedderWithCustomWords(m.cond_stage_model, self)

        self.clip = m.cond_stage_model



        if cmd_opts.opt_split_attention_v1:

            ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward_v1
@@ -268,6 +270,11 @@ class StableDiffusionModelHijack: 
        for layer in [layer for layer in self.layers if type(layer) == torch.nn.Conv2d]:

            layer.padding_mode = 'circular' if enable else 'zeros'



    def tokenize(self, text):

        max_length = self.clip.max_length - 2

        _, remade_batch_tokens, _, _, _, token_count = self.clip.process_text([text])

        return {"tokens": remade_batch_tokens[0], "token_count":token_count, "max_length":max_length}

        



class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):

    def __init__(self, wrapped, hijack):
@@ -294,14 +301,16 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): 
            if mult != 1.0:

                self.token_mults[ident] = mult



    def forward(self, text):

        self.hijack.fixes = []

        self.hijack.comments = []

        remade_batch_tokens = []

    def process_text(self, text):

        id_start = self.wrapped.tokenizer.bos_token_id

        id_end = self.wrapped.tokenizer.eos_token_id

        maxlen = self.wrapped.max_length

        used_custom_terms = []

        remade_batch_tokens = []

        overflowing_words = []

        hijack_comments = []

        hijack_fixes = []

        token_count = 0



        cache = {}

        batch_tokens = self.wrapped.tokenizer(text, truncation=False, add_special_tokens=False)["input_ids"]
@@ -353,9 +362,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): 
                    ovf = remade_tokens[maxlen - 2:]

                    overflowing_words = [vocab.get(int(x), "") for x in ovf]

                    overflowing_text = self.wrapped.tokenizer.convert_tokens_to_string(''.join(overflowing_words))



                    self.hijack.comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n")



                    hijack_comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n")

                token_count = len(remade_tokens)

                remade_tokens = remade_tokens + [id_end] * (maxlen - 2 - len(remade_tokens))

                remade_tokens = [id_start] + remade_tokens[0:maxlen-2] + [id_end]

                cache[tuple_tokens] = (remade_tokens, fixes, multipliers)
@@ -364,8 +372,14 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): 
            multipliers = [1.0] + multipliers[0:maxlen - 2] + [1.0]



            remade_batch_tokens.append(remade_tokens)

            self.hijack.fixes.append(fixes)

            hijack_fixes.append(fixes)

            batch_multipliers.append(multipliers)

        return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count



    def forward(self, text):

        batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text(text)

        self.hijack.fixes = hijack_fixes

        self.hijack.comments = hijack_comments



        if len(used_custom_terms) > 0:

            self.hijack.comments.append("Used custom terms: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms]))

modules/ui.py

+6 −1
Original line number Diff line number Diff line
@@ -22,6 +22,7 @@ from modules.paths import script_path 
from modules.shared import opts, cmd_opts

import modules.shared as shared

from modules.sd_samplers import samplers, samplers_for_img2img

from modules.sd_hijack import model_hijack

import modules.ldsr_model

import modules.scripts

import modules.gfpgan_model
@@ -337,11 +338,15 @@ def create_toprow(is_img2img): 
            with gr.Row():

                with gr.Column(scale=80):

                    with gr.Row():

                        prompt = gr.Textbox(label="Prompt", elem_id="prompt", show_label=False, placeholder="Prompt", lines=2)

                        prompt = gr.Textbox(label="Prompt", elem_id=id_part+"_prompt", show_label=False, placeholder="Prompt", lines=2)



                with gr.Column(scale=1, elem_id="roll_col"):

                    roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0)

                    paste = gr.Button(value=paste_symbol, elem_id="paste")

                    token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")

                    token_output = gr.JSON(visible=False)

                    if is_img2img:  # only define the api function ONCE

                        token_counter.change(fn=model_hijack.tokenize, api_name="tokenize", inputs=[token_counter], outputs=[token_output])



                with gr.Column(scale=10, elem_id="style_pos_col"):

                    prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1)

style.css

+4 −0
Original line number Diff line number Diff line
@@ -389,3 +389,7 @@ input[type="range"]{ 
  border-radius: 8px;

  display: none;

}



.red {

	color: red;

}

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