aceLab\core\leras\ops\__init__.py:55) ]]
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.
Errors may have originated from an input operation.
Input Source operations connected to node gradients/Conv2D_18_grad/Conv2DBackpropInput:
decoder_src/res2/conv2/weight/read (defined at E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:61)
Original stack trace for 'gradients/Conv2D_18_grad/Conv2DBackpropInput':
File "threading.py", line 884, in _bootstrap
File "threading.py", line 916, in _bootstrap_inner
File "threading.py", line 864, in run
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
debug=debug)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
self.on_initialize()
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 547, in on_initialize
gpu_G_loss_gvs += [ nn.gradients ( gpu_G_loss, self.src_dst_trainable_weights )]
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\ops\__init__.py", line 55, in tf_gradients
grads = gradients.gradients(loss, vars, colocate_gradients_with_ops=True )
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 172, in gradients
unconnected_gradients)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 682, in _GradientsHelper
lambda: grad_fn(op, *out_grads))
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 338, in _MaybeCompile
return grad_fn() # Exit early
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 682, in <lambda>
lambda: grad_fn(op, *out_grads))
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_grad.py", line 590, in _Conv2DGrad
data_format=data_format),
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 1291, in conv2d_backprop_input
name=name)
File "E:\RTX30\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 "E:\RTX30\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 "E:\RTX30\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)
...which was originally created as op 'Conv2D_18', defined at:
File "threading.py", line 884, in _bootstrap
[elided 3 identical lines from previous traceback]
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
self.on_initialize()
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 409, in on_initialize
gpu_pred_src_src, gpu_pred_src_srcm = self.decoder_src(gpu_src_code)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
return self.forward(*args, **kwargs)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 226, in forward
x = self.res2(x)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
return self.forward(*args, **kwargs)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 84, in forward
x = self.conv2(x)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\layers\LayerBase.py", line 14, in __call__
return self.forward(*args, **kwargs)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\layers\Conv2D.py", line 101, in forward
x = tf.nn.conv2d(x, weight, strides, 'VALID', dilations=dilations, data_format=nn.data_format)
File "E:\RTX30\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 "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 2397, in conv2d
name=name)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 972, in conv2d
data_format=data_format, dilations=dilations, name=name)
File "E:\RTX30\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)
Traceback (most recent call last):
File "E:\RTX30\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 "E:\RTX30\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 "E:\RTX30\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: OOM when allocating tensor with shape[8,144,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[{{node gradients/Conv2D_18_grad/Conv2DBackpropInput}}]]
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.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\mainscripts\Trainer.py", line 131, in trainerThread
iter, iter_time = model.train_one_iter()
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 480, in train_one_iter
losses = self.onTrainOneIter()
File "E:\RTX30\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 "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 584, in src_dst_train
self.target_dstm_em:target_dstm_em,
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 968, in run
run_metadata_ptr)
File "E:\RTX30\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 "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1369, in _do_run
run_metadata)
File "E:\RTX30\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: OOM when allocating tensor with shape[8,144,194,194] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[node gradients/Conv2D_18_grad/Conv2DBackpropInput (defined at E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\ops\__init__.py:55) ]]
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.
Errors may have originated from an input operation.
Input Source operations connected to node gradients/Conv2D_18_grad/Conv2DBackpropInput:
decoder_src/res2/conv2/weight/read (defined at E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\layers\Conv2D.py:61)
Original stack trace for 'gradients/Conv2D_18_grad/Conv2DBackpropInput':
File "threading.py", line 884, in _bootstrap
File "threading.py", line 916, in _bootstrap_inner
File "threading.py", line 864, in run
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread
debug=debug)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
self.on_initialize()
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 547, in on_initialize
gpu_G_loss_gvs += [ nn.gradients ( gpu_G_loss, self.src_dst_trainable_weights )]
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\ops\__init__.py", line 55, in tf_gradients
grads = gradients.gradients(loss, vars, colocate_gradients_with_ops=True )
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 172, in gradients
unconnected_gradients)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 682, in _GradientsHelper
lambda: grad_fn(op, *out_grads))
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 338, in _MaybeCompile
return grad_fn() # Exit early
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 682, in <lambda>
lambda: grad_fn(op, *out_grads))
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_grad.py", line 590, in _Conv2DGrad
data_format=data_format),
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 1291, in conv2d_backprop_input
name=name)
File "E:\RTX30\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 "E:\RTX30\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 "E:\RTX30\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)
...which was originally created as op 'Conv2D_18', defined at:
File "threading.py", line 884, in _bootstrap
[elided 3 identical lines from previous traceback]
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\ModelBase.py", line 199, in __init__
self.on_initialize()
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 409, in on_initialize
gpu_pred_src_src, gpu_pred_src_srcm = self.decoder_src(gpu_src_code)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
return self.forward(*args, **kwargs)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 226, in forward
x = self.res2(x)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__
return self.forward(*args, **kwargs)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 84, in forward
x = self.conv2(x)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\layers\LayerBase.py", line 14, in __call__
return self.forward(*args, **kwargs)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\DeepFaceLab\core\leras\layers\Conv2D.py", line 101, in forward
x = tf.nn.conv2d(x, weight, strides, 'VALID', dilations=dilations, data_format=nn.data_format)
File "E:\RTX30\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 "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 2397, in conv2d
name=name)
File "E:\RTX30\DFL_maozhihanhua_RTX3000\_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 972, in conv2d
data_format=data_format, dilations=dilations, name=name)
File "E:\RTX30\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)