yangxue0827 / RotationDetection

This is a tensorflow-based rotation detection benchmark, also called AlphaRotate.
https://rotationdetection.readthedocs.io/
Apache License 2.0
1.08k stars 182 forks source link

When i am trying to export pb using exportpb.py file from the checkpoints getting error. Please guide me on this... #51

Open sandhyacs opened 3 years ago

sandhyacs commented 3 years ago

WARNING:tensorflow:From exportPb.py:61: The name tf.reset_default_graph is deprecated. Please use tf.compat.v1.reset_default_graph instead.

WARNING:tensorflow:From exportPb.py:41: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.

WARNING:tensorflow:From ../../libs/models/backbones/mobilenet/mobilenet.py:324: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.

WARNING:tensorflow:From /home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/contrib/layers/python/layers/layers.py:1057: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version. Instructions for updating: Please use layer.__call__ method instead. WARNING:tensorflow:From ../../libs/models/necks/fpn_p3top7.py:24: The name tf.image.resize_bilinear is deprecated. Please use tf.compat.v1.image.resize_bilinear instead.

WARNING:tensorflow:From exportPb.py:65: The name tf.train.Saver is deprecated. Please use tf.compat.v1.train.Saver instead.

WARNING:tensorflow:From exportPb.py:67: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.

2021-10-19 12:17:08.433221: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2021-10-19 12:17:08.456539: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-10-19 12:17:08.456701: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: name: NVIDIA GeForce GTX 1050 major: 6 minor: 1 memoryClockRate(GHz): 1.493 pciBusID: 0000:01:00.0 2021-10-19 12:17:08.456731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 2021-10-19 12:17:08.457562: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 2021-10-19 12:17:08.458291: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0 2021-10-19 12:17:08.458464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0 2021-10-19 12:17:08.459427: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0 2021-10-19 12:17:08.460157: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0 2021-10-19 12:17:08.462534: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2021-10-19 12:17:08.462645: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-10-19 12:17:08.462864: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-10-19 12:17:08.462996: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0 2021-10-19 12:17:08.463220: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA 2021-10-19 12:17:08.484313: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2199995000 Hz 2021-10-19 12:17:08.484748: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x563a907797f0 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2021-10-19 12:17:08.484766: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2021-10-19 12:17:08.484948: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-10-19 12:17:08.485137: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: name: NVIDIA GeForce GTX 1050 major: 6 minor: 1 memoryClockRate(GHz): 1.493 pciBusID: 0000:01:00.0 2021-10-19 12:17:08.485178: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 2021-10-19 12:17:08.485194: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 2021-10-19 12:17:08.485207: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0 2021-10-19 12:17:08.485219: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0 2021-10-19 12:17:08.485232: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0 2021-10-19 12:17:08.485245: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0 2021-10-19 12:17:08.485257: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2021-10-19 12:17:08.485314: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-10-19 12:17:08.485486: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-10-19 12:17:08.485618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0 2021-10-19 12:17:08.485645: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 2021-10-19 12:17:08.586685: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix: 2021-10-19 12:17:08.586707: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0 2021-10-19 12:17:08.586716: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N 2021-10-19 12:17:08.586882: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-10-19 12:17:08.587085: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-10-19 12:17:08.587255: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-10-19 12:17:08.587400: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 84 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1) 2021-10-19 12:17:08.588667: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x563a960139c0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2021-10-19 12:17:08.588680: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce GTX 1050, Compute Capability 6.1 we have restred the weights from =====>> ../../output/trained_weights/RetinaNet_DOTA1.5_2x_20210314/DOTA1.5_1000model.ckpt Traceback (most recent call last): File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1365, in _do_call return fn(*args) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1350, in _run_fn target_list, run_metadata) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1443, in _call_tf_sessionrun run_metadata) tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [105] rhs shape= [84] [[{{node save/Assign_294}}]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saver.py", line 1290, in restore {self.saver_def.filename_tensor_name: save_path}) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 956, in run run_metadata_ptr) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1180, in _run feed_dict_tensor, options, run_metadata) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1359, in _do_run run_metadata) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1384, in _do_call raise type(e)(node_def, op, message) tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [105] rhs shape= [84] [[node save/Assign_294 (defined at /home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py:1748) ]]

Original stack trace for 'save/Assign_294': File "exportPb.py", line 313, in exporter.export_frozenPB() File "exportPb.py", line 65, in export_frozenPB saver = tf.train.Saver() File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saver.py", line 828, in init self.build() File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saver.py", line 840, in build self._build(self._filename, build_save=True, build_restore=True) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saver.py", line 878, in _build build_restore=build_restore) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saver.py", line 508, in _build_internal restore_sequentially, reshape) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saver.py", line 350, in _AddRestoreOps assign_ops.append(saveable.restore(saveable_tensors, shapes)) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saving/saveable_object_util.py", line 73, in restore self.op.get_shape().is_fully_defined()) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/ops/state_ops.py", line 227, in assign validate_shape=validate_shape) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/ops/gen_state_ops.py", line 66, in assign use_locking=use_locking, name=name) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/framework/op_def_library.py", line 794, in _apply_op_helper op_def=op_def) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func return func(*args, **kwargs) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 3357, in create_op attrs, op_def, compute_device) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 3426, in _create_op_internal op_def=op_def) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 1748, in init self._traceback = tf_stack.extract_stack()

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "exportPb.py", line 313, in exporter.export_frozenPB() File "exportPb.py", line 69, in export_frozenPB saver.restore(sess, CKPT_PATH) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saver.py", line 1326, in restore err, "a mismatch between the current graph and the graph") tensorflow.python.framework.errors_impl.InvalidArgumentError: Restoring from checkpoint failed. This is most likely due to a mismatch between the current graph and the graph from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:

Assign requires shapes of both tensors to match. lhs shape= [105] rhs shape= [84] [[node save/Assign_294 (defined at /home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py:1748) ]]

Original stack trace for 'save/Assign_294': File "exportPb.py", line 313, in exporter.export_frozenPB() File "exportPb.py", line 65, in export_frozenPB saver = tf.train.Saver() File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saver.py", line 828, in init self.build() File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saver.py", line 840, in build self._build(self._filename, build_save=True, build_restore=True) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saver.py", line 878, in _build build_restore=build_restore) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saver.py", line 508, in _build_internal restore_sequentially, reshape) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saver.py", line 350, in _AddRestoreOps assign_ops.append(saveable.restore(saveable_tensors, shapes)) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saving/saveable_object_util.py", line 73, in restore self.op.get_shape().is_fully_defined()) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/ops/state_ops.py", line 227, in assign validate_shape=validate_shape) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/ops/gen_state_ops.py", line 66, in assign use_locking=use_locking, name=name) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/framework/op_def_library.py", line 794, in _apply_op_helper op_def=op_def) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func return func(*args, **kwargs) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 3357, in create_op attrs, op_def, compute_device) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 3426, in _create_op_internal op_def=op_def) File "/home/sandhya/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 1748, in init self._traceback = tf_stack.extract_stack()