小白求助卡在启动中没有跳出预览图

Dewner

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=============================模型概要==============================

                  模型名字: luola_SAEHD

                  当前迭代: 7198670

---------------------------模型选项----------------------------

            resolution: 192
             face_type: wf
     models_opt_on_gpu: True
                 archi: liae
               ae_dims: 256
                e_dims: 64
                d_dims: 64
           d_mask_dims: 22
       masked_training: True
           uniform_yaw: True
            lr_dropout: n
           random_warp: True
             gan_power: 0.0
       true_face_power: 0.0
      face_style_power: 0.0
        bg_style_power: 0.0
               ct_mode: lct
              clipgrad: False
              pretrain: False
       autobackup_hour: 2
write_preview_history: False
           target_iter: 0
           random_flip: True
            batch_size: 4
       eyes_mouth_prio: True
         blur_out_mask: False
             adabelief: True
      random_hsv_power: 0.0
       random_src_flip: True
       random_dst_flip: False
        gan_patch_size: 24
              gan_dims: 16

---------------------------运行信息----------------------------

                  设备编号: 0
                  设备名称: NVIDIA GeForce RTX 3060 Laptop GPU
                  显存大小: 3.41GB

===========================================================
猫之汉化
出售模型、商业换脸程序开发、商业换脸视频定制
QQ\微信:564646676
淘宝店地址：http://t.hk.uy/4ks
=============================================

启动中. 按回车键停止训练并保存进度。

保存时间|迭代次数|单次时间|SRC损失|DST损失

Dewner

等了很久出现这个
Error: 2 root error(s) found.
  (0) Resource exhausted: failed to allocate memory
         [[node mul_123 (defined at D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\optimizers\AdaBelief.py:64) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

         [[concat_3/concat/_295]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

  (1) Resource exhausted: failed to allocate memory
         [[node mul_123 (defined at D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\optimizers\AdaBelief.py:64) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

0 successful operations.
0 derived errors ignored.

Errors may have originated from an input operation.
Input Source operations connected to node mul_123:
src_dst_opt/vs_inter_B/upscale1/conv1/weight_0/read (defined at D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\optimizers\AdaBelief.py:38)

Input Source operations connected to node mul_123:
src_dst_opt/vs_inter_B/upscale1/conv1/weight_0/read (defined at D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\optimizers\AdaBelief.py:38)

Original stack trace for 'mul_123':
  File "threading.py", line 884, in _bootstrap
  File "threading.py", line 916, in _bootstrap_inner
  File "threading.py", line 864, in run
  File "D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
    debug=debug)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
    self.on_initialize()
  File "D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 564, in on_initialize
    src_dst_loss_gv_op = self.src_dst_opt.get_update_op (nn.average_gv_list (gpu_G_loss_gvs))
  File "D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\optimizers\AdaBelief.py", line 64, in get_update_op
    v_t = self.beta_2*vs + (1.0-self.beta_2) * tf.square(g-m_t)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\variables.py", line 1076, in _run_op
    return tensor_oper(a.value(), *args, **kwargs)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\math_ops.py", line 1400, in r_binary_op_wrapper
    return func(x, y, name=name)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\math_ops.py", line 1710, in _mul_dispatch
    return multiply(x, y, name=name)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\util\dispatch.py", line 206, in wrapper
    return target(*args, **kwargs)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\math_ops.py", line 530, in multiply
    return gen_math_ops.mul(x, y, name)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 6245, in mul
    "Mul", x=x, y=y, name=name)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 750, in _apply_op_helper
    attrs=attr_protos, op_def=op_def)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 3569, in _create_op_internal
    op_def=op_def)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 2045, in __init__
    self._traceback = tf_stack.extract_stack_for_node(self._c_op)

Traceback (most recent call last):
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1375, in _do_call
    return fn(*args)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1360, in _run_fn
    target_list, run_metadata)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1453, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: 2 root error(s) found.
  (0) Resource exhausted: failed to allocate memory
         [[{{node mul_123}}]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

         [[concat_3/concat/_295]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

  (1) Resource exhausted: failed to allocate memory
         [[{{node mul_123}}]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

0 successful operations.
0 derived errors ignored.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\mainscripts\Trainer.py", line 131, in trainerThread
    iter, iter_time = model.train_one_iter()
  File "D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 480, in train_one_iter
    losses = self.onTrainOneIter()
  File "D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 774, in onTrainOneIter
    src_loss, dst_loss = self.src_dst_train (warped_src, target_src, target_srcm, target_srcm_em, warped_dst, target_dst, target_dstm, target_dstm_em)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 584, in src_dst_train
    self.target_dstm_em:target_dstm_em,
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 968, in run
    run_metadata_ptr)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1191, in _run
    feed_dict_tensor, options, run_metadata)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1369, in _do_run
    run_metadata)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1394, in _do_call
    raise type(e)(node_def, op, message)  # pylint: disable=no-value-for-parameter
tensorflow.python.framework.errors_impl.ResourceExhaustedError: 2 root error(s) found.
  (0) Resource exhausted: failed to allocate memory
         [[node mul_123 (defined at D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\optimizers\AdaBelief.py:64) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

         [[concat_3/concat/_295]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

  (1) Resource exhausted: failed to allocate memory
         [[node mul_123 (defined at D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\optimizers\AdaBelief.py:64) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

0 successful operations.
0 derived errors ignored.

Errors may have originated from an input operation.
Input Source operations connected to node mul_123:
src_dst_opt/vs_inter_B/upscale1/conv1/weight_0/read (defined at D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\optimizers\AdaBelief.py:38)

Input Source operations connected to node mul_123:
src_dst_opt/vs_inter_B/upscale1/conv1/weight_0/read (defined at D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\optimizers\AdaBelief.py:38)

Original stack trace for 'mul_123':
  File "threading.py", line 884, in _bootstrap
  File "threading.py", line 916, in _bootstrap_inner
  File "threading.py", line 864, in run
  File "D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
    debug=debug)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
    self.on_initialize()
  File "D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 564, in on_initialize
    src_dst_loss_gv_op = self.src_dst_opt.get_update_op (nn.average_gv_list (gpu_G_loss_gvs))
  File "D:\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\optimizers\AdaBelief.py", line 64, in get_update_op
    v_t = self.beta_2*vs + (1.0-self.beta_2) * tf.square(g-m_t)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\variables.py", line 1076, in _run_op
    return tensor_oper(a.value(), *args, **kwargs)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\math_ops.py", line 1400, in r_binary_op_wrapper
    return func(x, y, name=name)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\math_ops.py", line 1710, in _mul_dispatch
    return multiply(x, y, name=name)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\util\dispatch.py", line 206, in wrapper
    return target(*args, **kwargs)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\math_ops.py", line 530, in multiply
    return gen_math_ops.mul(x, y, name)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 6245, in mul
    "Mul", x=x, y=y, name=name)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 750, in _apply_op_helper
    attrs=attr_protos, op_def=op_def)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 3569, in _create_op_internal
    op_def=op_def)
  File "D:\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 2045, in __init__
    self._traceback = tf_stack.extract_stack_for_node(self._c_op)

anazyz

显存太小了吧，我笔记本1060的显示是4.74G，你才3.多呢，我的另一个笔记本3060L显卡的，也是一直卡着，没有研究了

Dewner

anazyz 发表于 2022-12-17 18:21
显存太小了吧，我笔记本1060的显示是4.74G，你才3.多呢，我的另一个笔记本3060L显卡的，也是一直卡着，没有 ...

我想知道怎么调高显存，我是3060的，不知道为什么这么低