IndexError: too many indices for array

[libaosir2]

When I run the run.sh , error occurs as follow: /home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/h5py/init.py:36: FutureWarning: Conversion of the second argument of issubdtype from float to np.floating is deprecated. In future, it will be treated as np.float64 == np.dtype(float).type. from ._conv import register_converters as _register_converters Parameters

--------------------------------------------------------------------------------------

Be careful as we do not use sophisticated parsing

The parser will read until the semicolon

types are defined as below

ss: multiple strings separated with commas

s: string

b: boolean

f: float

d: int

--------------------------------------------------------------------------------------

--------------------------------------------------------------------------------------

Dataset parameters

ss: dataset.trainSetList = ECCV/piccadilly/; # All the first images of oxford dataset is used for training s: dataset.dataType = ECCV; # the dataset type

--------------------------------------------------------------------------------------

Model parameters

s: model.modelType = Combined; # the network type b: model.bNormalizeInput = 1; # Normalize input to have zero mean and 1 std f: model.fScaleList = np.array([1.0]); # list of scale spaces (small means larger scale)

GHH related

f: model.max_strength = -1; # GHH softmax strength (-1 for hard)

Keypoints

s: model.sDetector = tilde; # network architecture for kp d: model.nFilterSize = 25; # Let's keep the number odd d: model.nPatchSizeKp = 48; # patch size for kp including moving

regions we use something smaller

s: model.sKpNonlinearity = None; # use nonlinearity at end f: model.fScaleList = np.array([1.0]); # list of scale spaces (small means larger scale) f: model.bias_rnd = 0.0; # random noise added to bias f: model.epsilon = 1e-8; # epsilon for tilde

Orientation

s: model.sOrientation = cvpr16; # network architecture for orientation

Descriptor

s: model.sDescriptor = descriptor_imported; # network architecture for desc d: model.nDescInputSize = 64; # Input size to be fed to the descriptor

s: model.descriptor_export_folder = /cvlabdata1/home/trulls-data/kpdesc/torch/export/;

L-> skipped s: model.descriptor_model = new-CNN3-picc-iter-56k.h5; # network configuration s: model.descriptor_input = desc-input; # Descriptor input

--------------------------------------------------------------------------------------

Parameters for patch extraction

automatically determined

f: patch.fMaxScale = np.max(self.model.fScaleList); # asserts make sure this is stored properly f: patch.fRatioScale = (self.model.nPatchSizeKp / 2.0) / 2.0; # to not resize when scale is 2 d: patch.nPatchSize = np.round(self.model.nDescInputSize * self.patch.fRatioScale / 6.0); # the large patch size for data. the desc will look at ratio scale of 6.0

--------------------------------------------------------------------------------------

Validation and test time parameters

d: validation.batch_size = 100; # batch size of the implementation

d: validation.nScaleInterval = 4;

L-> skipped

d: validation.nNMSInterval = 2; # number of intervals we look for

L-> skipped

NMS (3 would mean it goes up one

octave in case of

nScaleInterval=2)

---------------------------------------------------------------------------------

Time taken to read and prepare the image is 20.172 ms INFO: Testing double scale resize to test is [1.95833333 1.70482819 1.48413914 1.29201816 1.12476714 0.97916667 0.85241409 0.74206957 0.64600908 0.56238357 0.48958333 0.42620705 0.37103478 0.32300454 0.28119178 0.24479167 0.21310352 0.18551739 0.16150227 0.14059589 0.12239583] scales to test is [ 1. 1.14869835 1.31950791 1.51571657 1.74110113 2. 2.29739671 2.63901582 3.03143313 3.48220225 4. 4.59479342 5.27803164 6.06286627 6.96440451 8. 9.18958684 10.55606329 12.12573253 13.92880901 16. ] Time taken to resize image is 19.927ms WARNING (theano.sandbox.cuda): The cuda backend is deprecated and will be removed in the next release (v0.10). Please switch to the gpuarray backend. You can get more information about how to switch at this URL: https://github.com/Theano/Theano/wiki/Converting-to-the-new-gpu-back-end%28gpuarray%29

/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/sandbox/cuda/init.py:556: UserWarning: Theano flag device=gpu (old gpu back-end) only support floatX=float32. You have floatX=float64. Use the new gpu back-end with device=cuda for that value of floatX. warnings.warn(msg) Using gpu device 0: GeForce GTX 1060 3GB (CNMeM is disabled, cuDNN 5103) 1 #include 2 #include 3 #include "theano_mod_helper.h" 4 #include "cuda_ndarray.cuh" 5 ////////////////////// 6 //// Support Code 7 ////////////////////// 8 9 static global void kernel_reduce_ccontig_node_544270fe7a21a748315f83abfe0913cc_0( 10 const unsigned int d0, 11 const float A, 12 float Z) 13 { 14 const int threadCount = blockDim.x; 15 const int threadNum = threadIdx.x; 16 extern shared float buf[]; 17 float myresult = 0; 18 19 if (warpSize != 32) 20 { 21 return; //TODO: set error code 22 } 23 24 for (int i0 = threadIdx.x; i0 < d0; i0 += blockDim.x) 25 { 26 myresult = myresult + A[i0]; 27 } 28
29 syncthreads(); // some kernel do multiple reduction. 30 buf[threadNum] = myresult; 31 syncthreads(); 32 33 // rest of function is handled by one warp 34 if (threadNum < warpSize) 35 { 36 //round up all the partial sums into the first warpSize elements 37 for (int i = threadNum + warpSize; i < threadCount; i += warpSize) 38 { 39 myresult = myresult + buf[i]; 40 } 41 buf[threadNum] = myresult; 42 /*Comment this optimization as it don't work on Fermi GPU. 43 TODO: find why it don't work or put the GPU compute capability into the version 44 // no sync because only one warp is running 45 if(threadCount >32) 46 {buf[threadNum] = buf[threadNum] + buf[threadNum+16];buf[threadNum] = buf[threadNum] + buf[threadNum+8];buf[threadNum] = buf[threadNum] + buf[threadNum+4];buf[threadNum] = buf[threadNum] + buf[threadNum+2];buf[threadNum] = buf[threadNum] + buf[threadNum+1]; .......

nvcc fatal : Value 'sm_61' is not defined for option 'gpu-architecture'

['nvcc', '-shared', '-O3', '-arch=sm_61', '-m64', '-Xcompiler', '-fno-math-errno,-Wno-unused-label,-Wno-unused-variable,-Wno-write-strings,-DCUDA_NDARRAY_CUH=c72d035fdf91890f3b36710688069b2e,-DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION,-fPIC,-fvisibility=hidden', '-Xlinker', '-rpath,/home/lbg/.theano/compiledir_Linux-4.4--generic-x86_64-with-debian-jessie-sid-x86_64-2.7.13-64/cuda_ndarray', '-I/home/lbg/.theano/compiledir_Linux-4.4--generic-x86_64-with-debian-jessie-sid-x86_64-2.7.13-64/cuda_ndarray', '-I/usr/local/cuda-7.5/include', '-I/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/numpy/core/include', '-I/home/lbg/devdata/anaconda2/envs/py2/include/python2.7', '-I/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/gof', '-I/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/sandbox/cuda', '-L/home/lbg/.theano/compiledir_Linux-4.4--generic-x86_64-with-debian-jessie-sid-x86_64-2.7.13-64/cuda_ndarray', '-L/home/lbg/devdata/anaconda2/envs/py2/lib', '-o', '/home/lbg/.theano/compiledir_Linux-4.4--generic-x86_64-with-debian-jessie-sid-x86_64-2.7.13-64/tmp7Txrh9/544270fe7a21a748315f83abfe0913cc.so', 'mod.cu', '-lcudart', '-lcublas', '-lcuda_ndarray', '-lpython2.7'] Traceback (most recent call last): File "computedetector.py", line 215, in image, verbose=False) File "/home/lbg/devdata/LIFT/python-code/Utils/solvers.py", line 148, in TestImage myNet = CreateNetwork4Image(pathconf, param, image, verbose=verbose) File "/home/lbg/devdata/LIFT/python-code/Utils/solvers.py", line 93, in CreateNetwork4Image ) + '' + param.model.modelType.lower()) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/importlib/init.py", line 37, in import_module import(name) File "/home/lbg/devdata/LIFT/python-code/Utils/networks/eccv_combined.py", line 45, in import theano File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/init.py", line 116, in theano.sandbox.cuda.tests.test_driver.test_nvidia_driver1() File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/sandbox/cuda/tests/test_driver.py", line 32, in test_nvidia_driver1 profile=False) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/compile/function.py", line 326, in function output_keys=output_keys) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/compile/pfunc.py", line 486, in pfunc output_keys=output_keys) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/compile/function_module.py", line 1795, in orig_function defaults) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/compile/function_module.py", line 1661, in create input_storage=input_storage_lists, storage_map=storage_map) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/gof/link.py", line 699, in make_thunk storage_map=storage_map)[:3] File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/gof/vm.py", line 1063, in make_all impl=impl)) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/gof/op.py", line 924, in make_thunk no_recycling) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/gof/op.py", line 828, in make_c_thunk output_storage=node_output_storage) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/gof/cc.py", line 1190, in make_thunk keep_lock=keep_lock) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/gof/cc.py", line 1131, in compile keep_lock=keep_lock) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/gof/cc.py", line 1586, in cthunk_factory key=key, lnk=self, keep_lock=keep_lock) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/gof/cmodule.py", line 1155, in module_from_key module = lnk.compile_cmodule(location) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/gof/cc.py", line 1489, in compile_cmodule preargs=preargs) File "/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/sandbox/cuda/nvcc_compiler.py", line 393, in compile_str 'for cmd', ' '.join(cmd)) Exception: ('The following error happened while compiling the node', GpuCAReduce{add}{1}(<CudaNdarrayType(float32, vector)>), '\n', 'nvcc return status', 1, 'for cmd', 'nvcc -shared -O3 -arch=sm_61 -m64 -Xcompiler -fno-math-errno,-Wno-unused-label,-Wno-unused-variable,-Wno-write-strings,-DCUDA_NDARRAY_CUH=c72d035fdf91890f3b36710688069b2e,-DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION,-fPIC,-fvisibility=hidden -Xlinker -rpath,/home/lbg/.theano/compiledir_Linux-4.4--generic-x86_64-with-debian-jessie-sid-x86_64-2.7.13-64/cuda_ndarray -I/home/lbg/.theano/compiledir_Linux-4.4--generic-x86_64-with-debian-jessie-sid-x86_64-2.7.13-64/cuda_ndarray -I/usr/local/cuda-7.5/include -I/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/numpy/core/include -I/home/lbg/devdata/anaconda2/envs/py2/include/python2.7 -I/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/gof -I/home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/Theano-0.9.0rc1-py2.7.egg/theano/sandbox/cuda -L/home/lbg/.theano/compiledir_Linux-4.4--generic-x86_64-with-debian-jessie-sid-x86_64-2.7.13-64/cuda_ndarray -L/home/lbg/devdata/anaconda2/envs/py2/lib -o /home/lbg/.theano/compiledir_Linux-4.4--generic-x86_64-with-debian-jessie-sid-x86_64-2.7.13-64/tmp7Txrh9/544270fe7a21a748315f83abfe0913cc.so mod.cu -lcudart -lcublas -lcuda_ndarray -lpython2.7', '[GpuCAReduce{add}{1}(<CudaNdarrayType(float32, vector)>)]') /home/lbg/devdata/anaconda2/envs/py2/lib/python2.7/site-packages/h5py/init.py:36: FutureWarning: Conversion of the second argument of issubdtype from float to np.floating is deprecated. In future, it will be treated as np.float64 == np.dtype(float).type. from ._conv import register_converters as _register_converters

---

Traceback (most recent call last): File "compute_descriptor.py", line 111, in test_data_in = data_module.data_obj(param, image_file_name, kp_file_name) File "/home/lbg/devdata/LIFT/python-code/Utils/dataset_tools/test.py", line 64, in init self.load_data(param, image_file_name, kp_file_name) File "/home/lbg/devdata/LIFT/python-code/Utils/dataset_tools/test.py", line 82, in load_data pathconf, param, image_file_name, kp_file_name) File "/home/lbg/devdata/LIFT/python-code/Utils/dataset_tools/test.py", line 136, in load_data_for_set angle = np.pi / 180.0 * kp[:, IDX_ANGLE] # store angle in radians IndexError: too many indices for array

I have no idea about it .what should i do with this error?

[kmyi]

Sorry, but

nvcc fatal : Value 'sm_61' is not defined for option 'gpu-architecture'

Is a related to Theano. Can't help you much with that one.