Open zzzl-h opened 5 years ago
@zzzl-h seems your logits output shape does not match with label shape. check ur feeding data part maybe?
@zzzl-h seems your logits output shape does not match with label shape. check ur feeding data part maybe?
I have checked the feeding data. logits is (1,460,460,3), label is (1,460,460) I don't change anything in source code and use the VOC2012 dataset.
Can you tell me what your tensorflow version is? And python2 or python3?
Can you tell me what your tensorflow version is? And python2 or python3?
python 3 refer to the code , i'm not sure the tf version, generally tf1.4/tf1.5 may do the trick.
seg_loss= tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(labels=lab_reform,logits=seg_layer)) InvalidArgumentError (see above for traceback): logits and labels must have the same first dimension, got logits shape [3364,2] and labels shape [423200]
ur errors seems not related to version, but the feeding part. this two numbers doesn't match at all.
Can you tell me what your tensorflow version is? And python2 or python3?
python 3 refer to the code , i'm not sure the tf version, generally tf1.4/tf1.5 may do the trick.
seg_loss= tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(labels=lab_reform,logits=seg_layer)) InvalidArgumentError (see above for traceback): logits and labels must have the same first dimension, got logits shape [3364,2] and labels shape [423200]
ur errors seems not related to version, but the feeding part. this two numbers doesn't match at all.
Can you run the code on your computer? I think there are some mistakes. In train_e2e.py, line 350:reader=data_provider('train.list'), it may be reader=data_reader('train.list')? In train_e2e.py, line 352: One parameter is missing. In train_e2e.py, line 35 will change the data type into float32 so it can't be feed into labels which only accepts data type int32 or int64.
Hi, I don't know what's wrong, I use python2.7 and tensorflow1.2 and VOC2012 dataset 2018-11-18 21:48:15.769563: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. 2018-11-18 21:48:15.769595: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. 2018-11-18 21:48:15.769600: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. 2018-11-18 21:48:15.769604: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations. 2018-11-18 21:48:15.769608: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations. 2018-11-18 21:48:16.205096: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:893] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2018-11-18 21:48:16.205568: I tensorflow/core/common_runtime/gpu/gpu_device.cc:940] Found device 0 with properties: name: GeForce GTX 1080 major: 6 minor: 1 memoryClockRate (GHz) 1.8475 pciBusID 0000:01:00.0 Total memory: 7.93GiB Free memory: 7.12GiB 2018-11-18 21:48:16.205601: I tensorflow/core/common_runtime/gpu/gpu_device.cc:961] DMA: 0 2018-11-18 21:48:16.205615: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0: Y 2018-11-18 21:48:16.205632: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 1080, pci bus id: 0000:01:00.0) ('loading from model:', u'./savings_bgfg/pretrain.ckpt') Traceback (most recent call last): File "train_step1.py", line 146, in
loss = net.train(img_batch,lab_batch)
File "trainstep1.py", line 62, in train
ls, = self.sess.run([self.loss,self.train_op],feed_dict={self.inp_holder:img_batch, self.lab_holder:lab_batch})
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 789, in run
run_metadata_ptr)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 997, in _run
feed_dict_string, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1132, in _do_run
target_list, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1152, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: logits and labels must have the same first dimension, got logits shape [3364,2] and labels shape [423200]
[[Node: bg_fg/SparseSoftmaxCrossEntropyWithLogits/SparseSoftmaxCrossEntropyWithLogits = SparseSoftmaxCrossEntropyWithLogits[T=DT_FLOAT, Tlabels=DT_INT64, _device="/job:localhost/replica:0/task:0/gpu:0"](bg_fg/SparseSoftmaxCrossEntropyWithLogits/Reshape, bg_fg/SparseSoftmaxCrossEntropyWithLogits/Reshape_1)]]
[[Node: bg_fg/Mean/_263 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_8656_bg_fg/Mean", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
Caused by op u'bg_fg/SparseSoftmaxCrossEntropyWithLogits/SparseSoftmaxCrossEntropyWithLogits', defined at: File "train_step1.py", line 140, in
net = network()
File "train_step1.py", line 26, in init
self.build_loss(seg_layer,lab_holder)
File "train_step1.py", line 47, in build_loss
seg_loss = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(labels=lab_reform,logits=seg_layer))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_ops.py", line 1703, in sparse_softmax_cross_entropy_with_logits
precise_logits, labels, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_nn_ops.py", line 2486, in _sparse_softmax_cross_entropy_with_logits
features=features, labels=labels, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2506, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1269, in init
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): logits and labels must have the same first dimension, got logits shape [3364,2] and labels shape [423200] [[Node: bg_fg/SparseSoftmaxCrossEntropyWithLogits/SparseSoftmaxCrossEntropyWithLogits = SparseSoftmaxCrossEntropyWithLogits[T=DT_FLOAT, Tlabels=DT_INT64, _device="/job:localhost/replica:0/task:0/gpu:0"](bg_fg/SparseSoftmaxCrossEntropyWithLogits/Reshape, bg_fg/SparseSoftmaxCrossEntropyWithLogits/Reshape_1)]] [[Node: bg_fg/Mean/_263 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_8656_bg_fg/Mean", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]