From fdef8253a43ca5135923092ca9b85e878d980869 Mon Sep 17 00:00:00 2001 From: brkirch Date: Fri, 14 Oct 2022 04:42:53 -0400 Subject: Add 'interrogate' and 'all' choices to --use-cpu * Add 'interrogate' and 'all' choices to --use-cpu * Change type for --use-cpu argument to str.lower, so that choices are case insensitive --- modules/interrogate.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) (limited to 'modules/interrogate.py') diff --git a/modules/interrogate.py b/modules/interrogate.py index af858cc0..9263d65a 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -55,7 +55,7 @@ class InterrogateModels: model, preprocess = clip.load(clip_model_name) model.eval() - model = model.to(shared.device) + model = model.to(devices.device_interrogate) return model, preprocess @@ -65,14 +65,14 @@ class InterrogateModels: if not shared.cmd_opts.no_half: self.blip_model = self.blip_model.half() - self.blip_model = self.blip_model.to(shared.device) + self.blip_model = self.blip_model.to(devices.device_interrogate) if self.clip_model is None: self.clip_model, self.clip_preprocess = self.load_clip_model() if not shared.cmd_opts.no_half: self.clip_model = self.clip_model.half() - self.clip_model = self.clip_model.to(shared.device) + self.clip_model = self.clip_model.to(devices.device_interrogate) self.dtype = next(self.clip_model.parameters()).dtype @@ -99,11 +99,11 @@ class InterrogateModels: text_array = text_array[0:int(shared.opts.interrogate_clip_dict_limit)] top_count = min(top_count, len(text_array)) - text_tokens = clip.tokenize([text for text in text_array], truncate=True).to(shared.device) + text_tokens = clip.tokenize([text for text in text_array], truncate=True).to(devices.device_interrogate) text_features = self.clip_model.encode_text(text_tokens).type(self.dtype) text_features /= text_features.norm(dim=-1, keepdim=True) - similarity = torch.zeros((1, len(text_array))).to(shared.device) + similarity = torch.zeros((1, len(text_array))).to(devices.device_interrogate) for i in range(image_features.shape[0]): similarity += (100.0 * image_features[i].unsqueeze(0) @ text_features.T).softmax(dim=-1) similarity /= image_features.shape[0] @@ -116,7 +116,7 @@ class InterrogateModels: transforms.Resize((blip_image_eval_size, blip_image_eval_size), interpolation=InterpolationMode.BICUBIC), transforms.ToTensor(), transforms.Normalize((0.48145466, 0.4578275, 0.40821073), (0.26862954, 0.26130258, 0.27577711)) - ])(pil_image).unsqueeze(0).type(self.dtype).to(shared.device) + ])(pil_image).unsqueeze(0).type(self.dtype).to(devices.device_interrogate) with torch.no_grad(): caption = self.blip_model.generate(gpu_image, sample=False, num_beams=shared.opts.interrogate_clip_num_beams, min_length=shared.opts.interrogate_clip_min_length, max_length=shared.opts.interrogate_clip_max_length) @@ -140,7 +140,7 @@ class InterrogateModels: res = caption - clip_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(shared.device) + clip_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(devices.device_interrogate) precision_scope = torch.autocast if shared.cmd_opts.precision == "autocast" else contextlib.nullcontext with torch.no_grad(), precision_scope("cuda"): -- cgit v1.2.3