mkopecki commited on
Commit
15718d4
1 Parent(s): 180390d

Training in progress, step 500

Browse files
adapter_config.json CHANGED
@@ -20,13 +20,13 @@
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- "down_proj",
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  "gate_proj",
 
 
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  "k_proj",
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- "o_proj"
 
 
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  ],
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  "task_type": "CAUSAL_LM",
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  "use_dora": false,
 
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  "rank_pattern": {},
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  "revision": null,
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  "target_modules": [
 
 
 
 
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  "gate_proj",
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+ "v_proj",
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+ "o_proj",
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  "k_proj",
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+ "down_proj",
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+ "up_proj",
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+ "q_proj"
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  ],
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  "task_type": "CAUSAL_LM",
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  "use_dora": false,
adapter_model.safetensors CHANGED
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language_service.8096406fb6d8.root.log.INFO.20240805-122034.4270 CHANGED
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language_service.INFO CHANGED
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runs/Aug05_12-31-46_8096406fb6d8/events.out.tfevents.1722861112.8096406fb6d8.7300.0 ADDED
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tmp4ugedcwg/__pycache__/_remote_module_non_scriptable.cpython-310.pyc ADDED
Binary file (1.5 kB). View file
 
tmp4ugedcwg/_remote_module_non_scriptable.py ADDED
@@ -0,0 +1,81 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ from typing import *
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+
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+ import torch
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+ import torch.distributed.rpc as rpc
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+ from torch import Tensor
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+ from torch._jit_internal import Future
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+ from torch.distributed.rpc import RRef
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+ from typing import Tuple # pyre-ignore: unused import
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+
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+
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+ module_interface_cls = None
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+
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+
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+ def forward_async(self, *args, **kwargs):
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+ args = (self.module_rref, self.device, self.is_device_map_set, *args)
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+ kwargs = {**kwargs}
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+ return rpc.rpc_async(
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+ self.module_rref.owner(),
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+ _remote_forward,
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+ args,
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+ kwargs,
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+ )
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+
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+
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+ def forward(self, *args, **kwargs):
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+ args = (self.module_rref, self.device, self.is_device_map_set, *args)
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+ kwargs = {**kwargs}
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+ ret_fut = rpc.rpc_async(
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+ self.module_rref.owner(),
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+ _remote_forward,
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+ args,
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+ kwargs,
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+ )
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+ return ret_fut.wait()
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+
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+
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+ _generated_methods = [
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+ forward_async,
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+ forward,
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+ ]
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+
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+
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+
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+
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+ def _remote_forward(
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+ module_rref: RRef[module_interface_cls], device: str, is_device_map_set: bool, *args, **kwargs):
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+ module = module_rref.local_value()
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+ device = torch.device(device)
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+
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+ if device.type != "cuda":
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+ return module.forward(*args, **kwargs)
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+
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+ # If the module is on a cuda device,
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+ # move any CPU tensor in args or kwargs to the same cuda device.
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+ # Since torch script does not support generator expression,
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+ # have to use concatenation instead of
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+ # ``tuple(i.to(device) if isinstance(i, Tensor) else i for i in *args)``.
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+ args = (*args,)
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+ out_args: Tuple[()] = ()
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+ for arg in args:
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+ arg = (arg.to(device),) if isinstance(arg, Tensor) else (arg,)
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+ out_args = out_args + arg
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+
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+ kwargs = {**kwargs}
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+ for k, v in kwargs.items():
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+ if isinstance(v, Tensor):
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+ kwargs[k] = kwargs[k].to(device)
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+
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+ if is_device_map_set:
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+ return module.forward(*out_args, **kwargs)
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+
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+ # If the device map is empty, then only CPU tensors are allowed to send over wire,
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+ # so have to move any GPU tensor to CPU in the output.
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+ # Since torch script does not support generator expression,
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+ # have to use concatenation instead of
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+ # ``tuple(i.cpu() if isinstance(i, Tensor) else i for i in module.forward(*out_args, **kwargs))``.
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+ ret: Tuple[()] = ()
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+ for i in module.forward(*out_args, **kwargs):
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+ i = (i.cpu(),) if isinstance(i, Tensor) else (i,)
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+ ret = ret + i
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+ return ret
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