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ZhaoJ9014 / Multi-Human-Parsing

🔥🔥Official Repository for Multi-Human-Parsing (MHP)🔥🔥
http://lv-mhp.github.io/
MIT License
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error #11

Open zzzl-h opened 5 years ago

zzzl-h commented 5 years ago

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"]()]]

Anguliachao commented 5 years ago

@zzzl-h seems your logits output shape does not match with label shape. check ur feeding data part maybe?

zzzl-h commented 5 years ago

@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.

zzzl-h commented 5 years ago

Can you tell me what your tensorflow version is? And python2 or python3?

Anguliachao commented 5 years ago

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.

ur errors seems not related to version, but the feeding part. this two numbers doesn't match at all.

zzzl-h commented 5 years ago

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.