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import functools
import gradio as gr
from modules import shared
loaders_and_params = {
'AutoGPTQ': [
'triton',
'no_inject_fused_attention',
'no_inject_fused_mlp',
'no_use_cuda_fp16',
'wbits',
'groupsize',
'desc_act',
'gpu_memory',
'cpu_memory',
'cpu',
'disk',
'auto_devices',
'trust_remote_code',
'autogptq_info',
],
'GPTQ-for-LLaMa': [
'wbits',
'groupsize',
'model_type',
'pre_layer',
'gptq_for_llama_info',
],
'llama.cpp': [
'n_ctx',
'n_gpu_layers',
'n_batch',
'threads',
'no_mmap',
'mlock',
'llama_cpp_seed',
],
'Transformers': [
'cpu_memory',
'gpu_memory',
'trust_remote_code',
'load_in_8bit',
'bf16',
'cpu',
'disk',
'auto_devices',
'load_in_4bit',
'use_double_quant',
'quant_type',
'compute_dtype',
'trust_remote_code',
'transformers_info'
],
'ExLlama' : [
'gpu_split',
'max_seq_len',
'compress_pos_emb',
'exllama_info',
],
'ExLlama_HF' : [
'gpu_split',
'max_seq_len',
'compress_pos_emb',
'exllama_HF_info',
]
}
def get_gpu_memory_keys():
return [k for k in shared.gradio if k.startswith('gpu_memory')]
@functools.cache
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]
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