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| import functools | |
| from collections import OrderedDict | |
| import gradio as gr | |
| from modules import shared | |
| loaders_and_params = OrderedDict({ | |
| 'Transformers': [ | |
| 'cpu_memory', | |
| 'gpu_memory', | |
| 'load_in_8bit', | |
| 'bf16', | |
| 'cpu', | |
| 'disk', | |
| 'auto_devices', | |
| 'load_in_4bit', | |
| 'use_double_quant', | |
| 'quant_type', | |
| 'compute_dtype', | |
| 'trust_remote_code', | |
| 'no_use_fast', | |
| 'use_flash_attention_2', | |
| 'use_eager_attention', | |
| 'alpha_value', | |
| 'compress_pos_emb', | |
| 'disable_exllama', | |
| 'disable_exllamav2', | |
| 'transformers_info', | |
| ], | |
| 'llama.cpp': [ | |
| 'n_ctx', | |
| 'n_gpu_layers', | |
| 'cache_8bit', | |
| 'cache_4bit', | |
| 'tensor_split', | |
| 'n_batch', | |
| 'threads', | |
| 'threads_batch', | |
| 'no_mmap', | |
| 'mlock', | |
| 'no_mul_mat_q', | |
| 'rope_freq_base', | |
| 'compress_pos_emb', | |
| 'cpu', | |
| 'numa', | |
| 'no_offload_kqv', | |
| 'row_split', | |
| 'tensorcores', | |
| 'flash_attn', | |
| 'streaming_llm', | |
| 'attention_sink_size', | |
| ], | |
| 'llamacpp_HF': [ | |
| 'n_ctx', | |
| 'n_gpu_layers', | |
| 'cache_8bit', | |
| 'cache_4bit', | |
| 'tensor_split', | |
| 'n_batch', | |
| 'threads', | |
| 'threads_batch', | |
| 'no_mmap', | |
| 'mlock', | |
| 'no_mul_mat_q', | |
| 'rope_freq_base', | |
| 'compress_pos_emb', | |
| 'cpu', | |
| 'numa', | |
| 'cfg_cache', | |
| 'trust_remote_code', | |
| 'no_use_fast', | |
| 'logits_all', | |
| 'no_offload_kqv', | |
| 'row_split', | |
| 'tensorcores', | |
| 'flash_attn', | |
| 'streaming_llm', | |
| 'attention_sink_size', | |
| 'llamacpp_HF_info', | |
| ], | |
| 'ExLlamav2_HF': [ | |
| 'gpu_split', | |
| 'max_seq_len', | |
| 'cfg_cache', | |
| 'no_flash_attn', | |
| 'no_xformers', | |
| 'no_sdpa', | |
| 'num_experts_per_token', | |
| 'cache_8bit', | |
| 'cache_4bit', | |
| 'autosplit', | |
| 'alpha_value', | |
| 'compress_pos_emb', | |
| 'trust_remote_code', | |
| 'no_use_fast', | |
| ], | |
| 'ExLlamav2': [ | |
| 'gpu_split', | |
| 'max_seq_len', | |
| 'no_flash_attn', | |
| 'no_xformers', | |
| 'no_sdpa', | |
| 'num_experts_per_token', | |
| 'cache_8bit', | |
| 'cache_4bit', | |
| 'autosplit', | |
| 'alpha_value', | |
| 'compress_pos_emb', | |
| 'exllamav2_info', | |
| ], | |
| 'AutoGPTQ': [ | |
| 'triton', | |
| 'no_inject_fused_mlp', | |
| 'no_use_cuda_fp16', | |
| 'wbits', | |
| 'groupsize', | |
| 'desc_act', | |
| 'disable_exllama', | |
| 'disable_exllamav2', | |
| 'gpu_memory', | |
| 'cpu_memory', | |
| 'cpu', | |
| 'disk', | |
| 'auto_devices', | |
| 'trust_remote_code', | |
| 'no_use_fast', | |
| 'autogptq_info', | |
| ], | |
| 'HQQ': [ | |
| 'hqq_backend', | |
| 'trust_remote_code', | |
| 'no_use_fast', | |
| ], | |
| 'TensorRT-LLM': [ | |
| 'max_seq_len', | |
| 'cpp_runner', | |
| 'tensorrt_llm_info', | |
| ] | |
| }) | |
| def transformers_samplers(): | |
| return { | |
| 'temperature', | |
| 'temperature_last', | |
| 'dynamic_temperature', | |
| 'dynatemp_low', | |
| 'dynatemp_high', | |
| 'dynatemp_exponent', | |
| 'smoothing_factor', | |
| 'smoothing_curve', | |
| 'top_p', | |
| 'min_p', | |
| 'top_k', | |
| 'typical_p', | |
| 'epsilon_cutoff', | |
| 'eta_cutoff', | |
| 'tfs', | |
| 'top_a', | |
| 'repetition_penalty', | |
| 'presence_penalty', | |
| 'frequency_penalty', | |
| 'repetition_penalty_range', | |
| 'encoder_repetition_penalty', | |
| 'no_repeat_ngram_size', | |
| 'dry_multiplier', | |
| 'dry_base', | |
| 'dry_allowed_length', | |
| 'dry_sequence_breakers', | |
| 'seed', | |
| 'do_sample', | |
| 'penalty_alpha', | |
| 'mirostat_mode', | |
| 'mirostat_tau', | |
| 'mirostat_eta', | |
| 'grammar_file_row', | |
| 'grammar_string', | |
| 'guidance_scale', | |
| 'negative_prompt', | |
| 'ban_eos_token', | |
| 'custom_token_bans', | |
| 'sampler_priority', | |
| 'add_bos_token', | |
| 'skip_special_tokens', | |
| 'auto_max_new_tokens', | |
| 'prompt_lookup_num_tokens' | |
| } | |
| loaders_samplers = { | |
| 'Transformers': transformers_samplers(), | |
| 'AutoGPTQ': transformers_samplers(), | |
| 'HQQ': transformers_samplers(), | |
| 'ExLlamav2': { | |
| 'temperature', | |
| 'temperature_last', | |
| 'top_p', | |
| 'min_p', | |
| 'top_k', | |
| 'typical_p', | |
| 'tfs', | |
| 'top_a', | |
| 'repetition_penalty', | |
| 'presence_penalty', | |
| 'frequency_penalty', | |
| 'repetition_penalty_range', | |
| 'seed', | |
| 'mirostat_mode', | |
| 'mirostat_tau', | |
| 'mirostat_eta', | |
| 'ban_eos_token', | |
| 'add_bos_token', | |
| 'custom_token_bans', | |
| 'skip_special_tokens', | |
| 'auto_max_new_tokens', | |
| }, | |
| 'ExLlamav2_HF': { | |
| 'temperature', | |
| 'temperature_last', | |
| 'dynamic_temperature', | |
| 'dynatemp_low', | |
| 'dynatemp_high', | |
| 'dynatemp_exponent', | |
| 'smoothing_factor', | |
| 'smoothing_curve', | |
| 'top_p', | |
| 'min_p', | |
| 'top_k', | |
| 'typical_p', | |
| 'epsilon_cutoff', | |
| 'eta_cutoff', | |
| 'tfs', | |
| 'top_a', | |
| 'repetition_penalty', | |
| 'presence_penalty', | |
| 'frequency_penalty', | |
| 'repetition_penalty_range', | |
| 'encoder_repetition_penalty', | |
| 'no_repeat_ngram_size', | |
| 'dry_multiplier', | |
| 'dry_base', | |
| 'dry_allowed_length', | |
| 'dry_sequence_breakers', | |
| 'seed', | |
| 'do_sample', | |
| 'mirostat_mode', | |
| 'mirostat_tau', | |
| 'mirostat_eta', | |
| 'grammar_file_row', | |
| 'grammar_string', | |
| 'guidance_scale', | |
| 'negative_prompt', | |
| 'ban_eos_token', | |
| 'custom_token_bans', | |
| 'sampler_priority', | |
| 'add_bos_token', | |
| 'skip_special_tokens', | |
| 'auto_max_new_tokens', | |
| }, | |
| 'llama.cpp': { | |
| 'temperature', | |
| 'top_p', | |
| 'min_p', | |
| 'top_k', | |
| 'typical_p', | |
| 'tfs', | |
| 'repetition_penalty', | |
| 'presence_penalty', | |
| 'frequency_penalty', | |
| 'seed', | |
| 'mirostat_mode', | |
| 'mirostat_tau', | |
| 'mirostat_eta', | |
| 'grammar_file_row', | |
| 'grammar_string', | |
| 'ban_eos_token', | |
| 'custom_token_bans', | |
| }, | |
| 'llamacpp_HF': { | |
| 'temperature', | |
| 'temperature_last', | |
| 'dynamic_temperature', | |
| 'dynatemp_low', | |
| 'dynatemp_high', | |
| 'dynatemp_exponent', | |
| 'smoothing_factor', | |
| 'smoothing_curve', | |
| 'top_p', | |
| 'min_p', | |
| 'top_k', | |
| 'typical_p', | |
| 'epsilon_cutoff', | |
| 'eta_cutoff', | |
| 'tfs', | |
| 'top_a', | |
| 'repetition_penalty', | |
| 'presence_penalty', | |
| 'frequency_penalty', | |
| 'repetition_penalty_range', | |
| 'encoder_repetition_penalty', | |
| 'no_repeat_ngram_size', | |
| 'dry_multiplier', | |
| 'dry_base', | |
| 'dry_allowed_length', | |
| 'dry_sequence_breakers', | |
| 'seed', | |
| 'do_sample', | |
| 'mirostat_mode', | |
| 'mirostat_tau', | |
| 'mirostat_eta', | |
| 'grammar_file_row', | |
| 'grammar_string', | |
| 'guidance_scale', | |
| 'negative_prompt', | |
| 'ban_eos_token', | |
| 'custom_token_bans', | |
| 'sampler_priority', | |
| 'add_bos_token', | |
| 'skip_special_tokens', | |
| 'auto_max_new_tokens', | |
| }, | |
| 'TensorRT-LLM': { | |
| 'temperature', | |
| 'top_p', | |
| 'top_k', | |
| 'repetition_penalty', | |
| 'presence_penalty', | |
| 'frequency_penalty', | |
| 'ban_eos_token', | |
| 'auto_max_new_tokens', | |
| } | |
| } | |
| def list_all_samplers(): | |
| all_samplers = set() | |
| for k in loaders_samplers: | |
| for sampler in loaders_samplers[k]: | |
| all_samplers.add(sampler) | |
| return sorted(all_samplers) | |
| def blacklist_samplers(loader, dynamic_temperature): | |
| all_samplers = list_all_samplers() | |
| output = [] | |
| for sampler in all_samplers: | |
| if loader == 'All' or sampler in loaders_samplers[loader]: | |
| if sampler.startswith('dynatemp'): | |
| output.append(gr.update(visible=dynamic_temperature)) | |
| else: | |
| output.append(gr.update(visible=True)) | |
| else: | |
| output.append(gr.update(visible=False)) | |
| return output | |
| def get_gpu_memory_keys(): | |
| return [k for k in shared.gradio if k.startswith('gpu_memory')] | |
| def get_all_params(): | |
| all_params = set() | |
| for k in loaders_and_params: | |
| for el in loaders_and_params[k]: | |
| all_params.add(el) | |
| if 'gpu_memory' in all_params: | |
| all_params.remove('gpu_memory') | |
| for k in get_gpu_memory_keys(): | |
| all_params.add(k) | |
| return sorted(all_params) | |
| def make_loader_params_visible(loader): | |
| params = [] | |
| all_params = get_all_params() | |
| if loader in loaders_and_params: | |
| params = loaders_and_params[loader] | |
| if 'gpu_memory' in params: | |
| params.remove('gpu_memory') | |
| params += get_gpu_memory_keys() | |
| return [gr.update(visible=True) if k in params else gr.update(visible=False) for k in all_params] | |