and I delete all val and test set, use all_imgs as trian set right away.
The problem is, at a certain point in the first epoch(say 300th iteration), this error comes.
2019-10-19 16:43:33.168527: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at strided_slice_op.cc:106 : Invalid argument: slice index 21 of dimension 1 out of bounds.
2019-10-19 16:43:33.168539: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at strided_slice_op.cc:106 : Invalid argument: slice index 21 of dimension 1 out of bounds.
2019-10-19 16:43:33.168550: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at strided_slice_op.cc:106 : Invalid argument: slice index 22 of dimension 1 out of bounds.
Traceback (most recent call last):
File "rcnn/train_frcnn.py", line 292, in <module>
loss_class = model_classifier.train_on_batch([X, X2[:, sel_samples, :]], [Y1[:, sel_samples, :], Y2[:, sel_samples, :]])
File "/home/palm/miniconda3/envs/main36/lib/python3.6/site-packages/keras/engine/training.py", line 1217, in train_on_batch
outputs = self.train_function(ins)
File "/home/palm/miniconda3/envs/main36/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py", line 2715, in __call__
return self._call(inputs)
File "/home/palm/miniconda3/envs/main36/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py", line 2675, in _call
fetched = self._callable_fn(*array_vals)
File "/home/palm/miniconda3/envs/main36/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1439, in __call__
run_metadata_ptr)
File "/home/palm/miniconda3/envs/main36/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 528, in __exit__
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: slice index 31 of dimension 1 out of bounds.
[[{{node roi_pooling_conv_1/strided_slice_157}} = StridedSlice[Index=DT_INT32, T=DT_FLOAT, begin_mask=0, ellipsis_mask=0, end_mask=0, new_axis_mask=0, shrink_axis_mask=7, _device="/job:localhost/replica:0/task:0/device:GPU:0"](_arg_input_2_0_1/_13699, roi_pooling_conv_1/strided_slice_157/stack, roi_pooling_conv_1/strided_slice_157/stack_1, loss_1/dense_regress_3_loss/strided_slice_2/stack_2)]]
[[{{node loss_1/dense_regress_3_loss/Mean_2/_14305}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_49135_loss_1/dense_regress_3_loss/Mean_2", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
My environment is Ubuntu 18.04 Tensorflow 1.14.0 Keras 2.2.4
I'm using simple parser with some edit from here https://github.com/you359/Keras-FasterRCNN/issues/6
like this
and I delete all
val
andtest
set, useall_imgs
astrian
set right away.The problem is, at a certain point in the first epoch(say 300th iteration), this error comes.
What should I do about this?