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d02c2a6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 | import os
import torch
from safetensors.torch import load_file, save_file
class AdvancedPromptEmbeds:
"""
Flexible container for prompt embedding tensors.
Each value passed in must be a list of tensors, where each item in the
list corresponds to a single item in the batch (list length == batch size).
Do not store more than one tensor per batch item under the same key — if
you need multiple tensors per batch item, give them different key names.
Usage:
pe = AdvancedPromptEmbeds(
prompt_embeds=[t0, t1, t2], # one tensor per batch item
pooled_embeds=[p0, p1, p2],
)
pe.prompt_embeds # -> [t0, t1, t2]
pe['prompt_embeds'] # -> [t0, t1, t2]
pe.keys() # -> ['prompt_embeds', 'pooled_embeds']
# add more after init
pe.extra = [e0, e1, e2]
pe['extra2'] = [e0, e1, e2]
pe.set('extra3', [e0, e1, e2])
pe.update(extra4=[e0, e1, e2])
"""
def __init__(self, **kwargs):
self._store = {}
self._frozen_dtype_keys = []
for key, value in kwargs.items():
if not isinstance(value, list):
value = [value]
self._store[key] = value
@property
def frozen_dtype_keys(self):
return self._frozen_dtype_keys
@frozen_dtype_keys.setter
def frozen_dtype_keys(self, keys):
self._frozen_dtype_keys = list(keys) if keys else []
def __getattr__(self, name):
if name.startswith("_"):
raise AttributeError(name)
store = self.__dict__.get("_store", {})
if name in store:
return store[name]
raise AttributeError(f"{type(self).__name__!s} has no attribute {name!r}")
def __setattr__(self, name, value):
if name.startswith("_"):
super().__setattr__(name, value)
return
cls_attr = getattr(type(self), name, None)
if isinstance(cls_attr, property):
super().__setattr__(name, value)
return
if not isinstance(value, list):
value = [value]
self._store[name] = value
def set(self, key, value):
if not isinstance(value, list):
value = [value]
self._store[key] = value
def update(self, **kwargs):
for key, value in kwargs.items():
if not isinstance(value, list):
value = [value]
self._store[key] = value
def keys(self):
return list(self._store.keys())
def __getitem__(self, key):
return self._store[key]
def __setitem__(self, key, value):
if not isinstance(value, list):
value = [value]
self._store[key] = value
def __contains__(self, key):
return key in self._store
def to(self, *args, **kwargs):
frozen = set(self._frozen_dtype_keys)
if frozen:
no_dtype_args = [a for a in args if not isinstance(a, torch.dtype)]
no_dtype_kwargs = {k: v for k, v in kwargs.items() if k != "dtype"}
new_pe = AdvancedPromptEmbeds()
new_pe._frozen_dtype_keys = list(self._frozen_dtype_keys)
for key, value in self._store.items():
if key in frozen:
new_pe._store[key] = [
v.to(*no_dtype_args, **no_dtype_kwargs) for v in value
]
else:
new_pe._store[key] = [v.to(*args, **kwargs) for v in value]
return new_pe
def detach(self):
new_pe = AdvancedPromptEmbeds()
new_pe._frozen_dtype_keys = list(self._frozen_dtype_keys)
for key, value in self._store.items():
new_pe._store[key] = [v.detach() for v in value]
return new_pe
def clone(self):
new_pe = AdvancedPromptEmbeds()
new_pe._frozen_dtype_keys = list(self._frozen_dtype_keys)
for key, value in self._store.items():
new_pe._store[key] = [v.clone() for v in value]
return new_pe
def expand_to_batch(self, batch_size):
new_pe = AdvancedPromptEmbeds()
new_pe._frozen_dtype_keys = list(self._frozen_dtype_keys)
for key, value in self._store.items():
if len(value) == 1:
new_pe._store[key] = value * batch_size
elif len(value) == batch_size:
new_pe._store[key] = value
else:
raise ValueError(
f"Cannot expand key {key!r}: expected list of length 1 or {batch_size}, got {len(value)}"
)
return new_pe
def save(self, path):
data = {}
metadata = {"class_name": self.__class__.__name__}
for key, value in self._store.items():
if len(value) != 1:
raise ValueError(
f"Cannot save key {key!r}: expected list of length 1, got {len(value)}"
)
data[key] = value[0]
os.makedirs(os.path.dirname(path), exist_ok=True)
save_file(data, path, metadata=metadata)
@classmethod
def load(cls, path=None):
if path is not None:
loaded = load_file(path)
else:
raise ValueError("Must provide a path")
data = {}
for key in loaded.keys():
data[key] = loaded[key]
return cls(**data)
@classmethod
def concat_prompt_embeds(
cls, prompt_embeds: list["AdvancedPromptEmbeds"], padding_side: str = "right"
):
embeds = {}
frozen = []
for pe in prompt_embeds:
for key in pe.keys():
if key not in embeds:
embeds[key] = []
embeds[key].extend(pe[key])
for k in pe.frozen_dtype_keys:
if k not in frozen:
frozen.append(k)
out = cls(**embeds)
out.frozen_dtype_keys = frozen
return out
@classmethod
def split_prompt_embeds(cls, concatenated: "AdvancedPromptEmbeds", num_parts=None):
if num_parts is None:
# use length of first item as num_parts
num_parts = len(concatenated[concatenated.keys()[0]])
split_embeds = [cls() for _ in range(num_parts)]
for pe in split_embeds:
pe.frozen_dtype_keys = list(concatenated.frozen_dtype_keys)
for key in concatenated.keys():
values = concatenated[key]
if len(values) != num_parts:
raise ValueError(
f"Cannot split key {key!r}: expected list of length {num_parts}, got {len(values)}"
)
for i in range(num_parts):
split_embeds[i]._store[key] = [values[i]]
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