# ran into memory issues with safetensors. this code moves by them. import contextlib, json, mmap, os, warnings import torch from _bighash import hash class WritingSafeTensors: def __init__(self, name, file_size=16*1024*1024*1024, deduplicate=False, save_on_crash=False, **metadata): self.name = name.removesuffix('.safetensors') self.metadata = metadata self.file = self.File(self.name + '.safetensors') self.files = {self.file.filename:self.file} self.file_size = file_size self.weight_map = {} if deduplicate: warnings.warn('Safetensors deduplication enabled. The file will not be readable with the official library without https://github.com/huggingface/safetensors/pull/586', stacklevel=2) self.hash_map = {} if deduplicate else None self.save_on_crash = save_on_crash def add(self, name, tensor): if self.hash_map is None: self.file.add(name, tensor, return_hash=False) image_of = name else: tensor_hash = self.file.add(name, tensor, return_hash=True) image_of = self.hash_map.setdefault(tensor_hash, name) if image_of is not name: self.file.undo(name, tensor) image_file = self.weight_map[image_of] image_file.add(name, tensor, return_hash=False, image_of=image_of) self.weight_map[name] = image_file else: print(name, '...') if self.file.size >= self.file_size: self.file.undo(name, tensor) ct = len(self.files) if len(self.files) == 1: self.file.rename(f'{self.name}-{ct:05}.safetensors') self.file.set_metadata(index = str(ct)) self.files = {self.file.filename:self.file} ct += 1 self.file = self.File(f'{self.name}-{ct:05}.safetensors', index = ct) self.files[self.file.filename] = self.file self.file.add(name, tensor, return_hash=False) self.weight_map[name] = self.file def finalize(self): if len(self.files) == 1: self.file.set_metadata(**self.metadata) self.file.finalize() else: index_name = self.name + '.safetensors.index.json' print(index_name, '...') total_size = 0 tot = len(self.files) for ct, file in enumerate(self.files.values()): ct += 1 file.rename(f'{self.name}-{ct:05}-of-{tot:06}.safetensors') file.finalize() total_size += file.size with open(index_name, 'w') as fh: json.dump( { 'metadata': { **{ k: v if type(v) in [int, float, str, list, tuple, dict] else str(v) for k, v in self.metadata.items() }, 'total_size': total_size, }, 'weight_map': { name: file.filename for name, file in self.weight_map.items() }, }, fh, indent = '\t', ) del self.file del self.files del self.metadata def delete(self): for file in self.files.values(): file.delete() del self.file del self.files del self.metadata def __enter__(self): return self def __exit__(self, Exc, exc, tb): throw = None if Exc is None or self.save_on_crash: try: self.finalize() except: self.delete() raise else: self.delete() class File: def __init__(self, filename, **metadata): print(filename, '...') self.filename = filename self.fd = os.open(self.filename, os.O_RDWR | os.O_CREAT) self.size = 0 self.capacity = 0 self.mmapview = None self.header = {'__metadata__': {k:str(v) for k,v in metadata.items()}} self.finalized = False def _reserve(self, length): if self.size + length > self.capacity: new_capacity = self.size * 2 if new_capacity < self.size + length: new_capacity = (((self.size + length)*2 - 1) // mmap.PAGESIZE + 1) * mmap.PAGESIZE os.truncate(self.filename, new_capacity) self.mmapview = memoryview(mmap.mmap(self.fd, new_capacity)) self.capacity = new_capacity def add(self, name, tensor, return_hash, image_of=None): length = tensor.numel() * tensor.dtype.itemsize if image_of is None: self._reserve(length) start, end = self.size, self.size + length torch.frombuffer( self.mmapview[start : end], dtype=tensor.dtype, count=tensor.numel(), ).view(tensor.shape or [1])[:] = tensor #assert len(self.header)<2 or max(list(self.header.items())[1:], key=lambda item:item[1]['data_offsets'])[1]['data_offsets'][-1] == self.size assert end >= self.size self.size = end else: image = self.header[image_of] start, end = image['data_offsets'] assert end - start == length assert (tensor == torch.frombuffer( self.mmapview[start : end], dtype=tensor.dtype, count=tensor.numel(), ).view(tensor.shape)).all() tensor.flatten() if return_hash: tensor_hash = hash(self.mmapview[start : end]) else: tensor_hash = None self.header[name] = { 'dtype': str(tensor.dtype).rsplit('.',1)[-1] .replace('float','F') .replace('uint','U') .replace('int','I') .removesuffix('uz') .removesuffix('fn') .upper(), 'shape': list(tensor.shape), 'data_offsets': [start, end], } return tensor_hash def undo(self, name, tensor): last_name = None last_header = None #max_name, max_header = max(list(self.header.items())[1:], key = lambda item: item[1]['data_offsets'][-1]) #assert max_name == name #assert max_header['data_offsets'][-1] == self.size length = tensor.numel() * tensor.dtype.itemsize assert [self.size - length, self.size] == self.header[name]['data_offsets'] self.size -= length del self.header[name] #max_name, max_header = max(list(self.header.items())[1:], key = lambda item: item[1]['data_offsets'][-1]) #assert max_header['data_offsets'][-1] == self.size def set_metadata(self, **metadata): m = self.header['__metadata__'] for k, v in metadata.items(): m[k] = str(v) def rename(self, filename): os.rename(self.filename, filename) self.filename = filename return filename def finalize(self): print(self.filename, '...') header = json.dumps(self.header, separators=[',',':']).encode() insert = len(header) + 8 self._reserve(insert) self.mmapview[insert:insert+self.size] = self.mmapview[:self.size] self.size += insert self.mmapview[:8] = len(header).to_bytes(8, 'little') self.mmapview[8:insert] = header del self.header del self.mmapview os.close(self.fd) os.truncate(self.filename, self.size) self.finalized = True def delete(self): if not self.finalized: print('deleting', self.filename, '...') del self.header del self.mmapview os.close(self.fd) self.finalized = True os.unlink(self.filename)