mirror of
https://github.com/lllyasviel/Fooocus.git
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feat: move censor to extras, optimize safety checker file handling
This commit is contained in:
Manuel Schmid
@@ -0,0 +1,56 @@
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# modified version of https://github.com/AUTOMATIC1111/stable-diffusion-webui-nsfw-censor/blob/master/scripts/censor.py
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import numpy as np
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import os
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from extras.safety_checker.models.safety_checker import StableDiffusionSafetyChecker
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from transformers import CLIPFeatureExtractor, CLIPConfig
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from PIL import Image
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import modules.config
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safety_checker_repo_root = os.path.join(os.path.dirname(__file__), 'safety_checker')
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config_path = os.path.join(safety_checker_repo_root, "configs", "config.json")
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preprocessor_config_path = os.path.join(safety_checker_repo_root, "configs", "preprocessor_config.json")
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safety_feature_extractor = None
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safety_checker = None
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def numpy_to_pil(image):
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image = (image * 255).round().astype("uint8")
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pil_image = Image.fromarray(image)
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return pil_image
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# check and replace nsfw content
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def check_safety(x_image):
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global safety_feature_extractor, safety_checker
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if safety_feature_extractor is None or safety_checker is None:
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safety_checker_model = modules.config.downloading_safety_checker_model()
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safety_feature_extractor = CLIPFeatureExtractor.from_json_file(preprocessor_config_path)
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clip_config = CLIPConfig.from_json_file(config_path)
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safety_checker = StableDiffusionSafetyChecker.from_pretrained(safety_checker_model, config=clip_config)
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safety_checker_input = safety_feature_extractor(numpy_to_pil(x_image), return_tensors="pt")
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x_checked_image, has_nsfw_concept = safety_checker(images=x_image, clip_input=safety_checker_input.pixel_values)
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return x_checked_image, has_nsfw_concept
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def censor_single(x):
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x_checked_image, has_nsfw_concept = check_safety(x)
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# replace image with black pixels, keep dimensions
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# workaround due to different numpy / pytorch image matrix format
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if has_nsfw_concept[0]:
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imageshape = x_checked_image.shape
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x_checked_image = np.zeros((imageshape[0], imageshape[1], 3), dtype = np.uint8)
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return x_checked_image
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def censor_batch(images):
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images = [censor_single(image) for image in images]
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return images
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@@ -0,0 +1,171 @@
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{
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"_name_or_path": "clip-vit-large-patch14/",
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"architectures": [
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"SafetyChecker"
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],
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"initializer_factor": 1.0,
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"logit_scale_init_value": 2.6592,
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"model_type": "clip",
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"projection_dim": 768,
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"text_config": {
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"_name_or_path": "",
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"add_cross_attention": false,
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"architectures": null,
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"attention_dropout": 0.0,
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"bad_words_ids": null,
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"bos_token_id": 0,
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"chunk_size_feed_forward": 0,
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"cross_attention_hidden_size": null,
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"decoder_start_token_id": null,
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"diversity_penalty": 0.0,
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"do_sample": false,
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"dropout": 0.0,
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"early_stopping": false,
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"encoder_no_repeat_ngram_size": 0,
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"eos_token_id": 2,
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"exponential_decay_length_penalty": null,
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"finetuning_task": null,
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"forced_bos_token_id": null,
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"forced_eos_token_id": null,
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"hidden_act": "quick_gelu",
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"hidden_size": 768,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1"
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},
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"initializer_factor": 1.0,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"is_decoder": false,
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"is_encoder_decoder": false,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1
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},
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"layer_norm_eps": 1e-05,
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"length_penalty": 1.0,
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"max_length": 20,
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"max_position_embeddings": 77,
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"min_length": 0,
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"model_type": "clip_text_model",
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"no_repeat_ngram_size": 0,
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"num_attention_heads": 12,
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"num_beam_groups": 1,
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"num_beams": 1,
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"num_hidden_layers": 12,
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"num_return_sequences": 1,
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"output_attentions": false,
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"output_hidden_states": false,
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"output_scores": false,
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"pad_token_id": 1,
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"prefix": null,
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"problem_type": null,
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"pruned_heads": {},
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"remove_invalid_values": false,
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"repetition_penalty": 1.0,
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"return_dict": true,
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"return_dict_in_generate": false,
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"sep_token_id": null,
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"task_specific_params": null,
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"temperature": 1.0,
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"tie_encoder_decoder": false,
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"tie_word_embeddings": true,
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"tokenizer_class": null,
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"top_k": 50,
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"top_p": 1.0,
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"torch_dtype": null,
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"torchscript": false,
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"transformers_version": "4.21.0.dev0",
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"typical_p": 1.0,
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"use_bfloat16": false,
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"vocab_size": 49408
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},
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"text_config_dict": {
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"hidden_size": 768,
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"intermediate_size": 3072,
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"num_attention_heads": 12,
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"num_hidden_layers": 12
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},
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"torch_dtype": "float32",
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"transformers_version": null,
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"vision_config": {
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"_name_or_path": "",
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"add_cross_attention": false,
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"architectures": null,
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"attention_dropout": 0.0,
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"bad_words_ids": null,
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"bos_token_id": null,
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"chunk_size_feed_forward": 0,
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"cross_attention_hidden_size": null,
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"decoder_start_token_id": null,
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"diversity_penalty": 0.0,
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"do_sample": false,
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"dropout": 0.0,
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"early_stopping": false,
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"encoder_no_repeat_ngram_size": 0,
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"eos_token_id": null,
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"exponential_decay_length_penalty": null,
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"finetuning_task": null,
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"forced_bos_token_id": null,
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"forced_eos_token_id": null,
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"hidden_act": "quick_gelu",
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"hidden_size": 1024,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1"
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},
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"image_size": 224,
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"initializer_factor": 1.0,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"is_decoder": false,
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"is_encoder_decoder": false,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1
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},
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"layer_norm_eps": 1e-05,
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"length_penalty": 1.0,
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"max_length": 20,
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"min_length": 0,
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"model_type": "clip_vision_model",
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"no_repeat_ngram_size": 0,
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"num_attention_heads": 16,
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"num_beam_groups": 1,
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"num_beams": 1,
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"num_hidden_layers": 24,
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"num_return_sequences": 1,
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"output_attentions": false,
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"output_hidden_states": false,
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"output_scores": false,
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"pad_token_id": null,
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"patch_size": 14,
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"prefix": null,
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"problem_type": null,
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"pruned_heads": {},
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"remove_invalid_values": false,
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"repetition_penalty": 1.0,
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"return_dict": true,
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"return_dict_in_generate": false,
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"sep_token_id": null,
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"task_specific_params": null,
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"temperature": 1.0,
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"tie_encoder_decoder": false,
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"tie_word_embeddings": true,
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"tokenizer_class": null,
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"top_k": 50,
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"top_p": 1.0,
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"torch_dtype": null,
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"torchscript": false,
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"transformers_version": "4.21.0.dev0",
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"typical_p": 1.0,
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"use_bfloat16": false
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},
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"vision_config_dict": {
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"hidden_size": 1024,
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"intermediate_size": 4096,
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"patch_size": 14
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}
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}
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@@ -0,0 +1,20 @@
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{
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"crop_size": 224,
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"do_center_crop": true,
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"do_convert_rgb": true,
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"do_normalize": true,
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"do_resize": true,
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"feature_extractor_type": "CLIPFeatureExtractor",
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"image_mean": [
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0.48145466,
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0.4578275,
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0.40821073
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],
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"image_std": [
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0.26862954,
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0.26130258,
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0.27577711
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],
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"resample": 3,
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"size": 224
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}
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