From 95b7cf9bbe0d1c0de34c630cf5209840b273d37c Mon Sep 17 00:00:00 2001 From: svdc Date: Mon, 14 Oct 2024 21:12:20 -0300 Subject: [PATCH 1/2] Fix Transformers FutureWarning (#5140) * Update sd1_clip.py Fix Transformers FutureWarning * Update sd1_clip.py Fix comment --- comfy/sd1_clip.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/comfy/sd1_clip.py b/comfy/sd1_clip.py index bb240526f..6f574900f 100644 --- a/comfy/sd1_clip.py +++ b/comfy/sd1_clip.py @@ -405,7 +405,7 @@ class SDTokenizer: def __init__(self, tokenizer_path=None, max_length=77, pad_with_end=True, embedding_directory=None, embedding_size=768, embedding_key='clip_l', tokenizer_class=CLIPTokenizer, has_start_token=True, pad_to_max_length=True, min_length=None, pad_token=None, tokenizer_data={}): if tokenizer_path is None: tokenizer_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "sd1_tokenizer") - self.tokenizer = tokenizer_class.from_pretrained(tokenizer_path) + self.tokenizer = tokenizer_class.from_pretrained(tokenizer_path, clean_up_tokenization_spaces=True) # Fix Transformers FutureWarning by explicitly setting clean_up_tokenization_spaces to True self.max_length = max_length self.min_length = min_length From f58475827150c2ac610cbb113019276efcd1a733 Mon Sep 17 00:00:00 2001 From: comfyanonymous Date: Mon, 14 Oct 2024 21:02:29 -0400 Subject: [PATCH 2/2] Cleanup some useless lines. --- comfy/k_diffusion/sampling.py | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/comfy/k_diffusion/sampling.py b/comfy/k_diffusion/sampling.py index 70273d9d5..7b54d8c5a 100644 --- a/comfy/k_diffusion/sampling.py +++ b/comfy/k_diffusion/sampling.py @@ -1080,7 +1080,6 @@ def sample_euler_cfg_pp(model, x, sigmas, extra_args=None, callback=None, disabl d = to_d(x, sigma_hat, temp[0]) if callback is not None: callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigma_hat, 'denoised': denoised}) - dt = sigmas[i + 1] - sigma_hat # Euler method x = denoised + d * sigmas[i + 1] return x @@ -1107,7 +1106,6 @@ def sample_euler_ancestral_cfg_pp(model, x, sigmas, extra_args=None, callback=No callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigmas[i], 'denoised': denoised}) d = to_d(x, sigmas[i], temp[0]) # Euler method - dt = sigma_down - sigmas[i] x = denoised + d * sigma_down if sigmas[i + 1] > 0: x = x + noise_sampler(sigmas[i], sigmas[i + 1]) * s_noise * sigma_up @@ -1138,7 +1136,6 @@ def sample_dpmpp_2s_ancestral_cfg_pp(model, x, sigmas, extra_args=None, callback if sigma_down == 0: # Euler method d = to_d(x, sigmas[i], temp[0]) - dt = sigma_down - sigmas[i] x = denoised + d * sigma_down else: # DPM-Solver++(2S) @@ -1186,4 +1183,4 @@ def sample_dpmpp_2m_cfg_pp(model, x, sigmas, extra_args=None, callback=None, dis denoised_mix = -torch.exp(-h) * uncond_denoised - torch.expm1(-h) * (1 / (2 * r)) * (denoised - old_uncond_denoised) x = denoised + denoised_mix + torch.exp(-h) * x old_uncond_denoised = uncond_denoised - return x \ No newline at end of file + return x