Hello, I found the same issue with a git version in local environment. In my case it seems to be a problem with Python 3, since Python 2 does not have the issue. Details below. Thanks, Pablo
---------------------------- Name: Theano Version: 0.9.0b1 Summary: Optimizing compiler for evaluating mathematical expressions on CPUs and GPUs. Home-page: http://deeplearning.net/software/theano/ Author: LISA laboratory, University of Montreal Author-email: [email protected] License: BSD Location: /opt/libs_2017_01_26/python3_env/lib/python3.5/site-packages Requires: numpy, scipy, six ---------------------------- GIT version: Theano 70129ffb66320140275be7f75152e792c4647510 libgpuarray d838f6a43bcc56fb280a8b40fdbc03276b3eb7fd ---------------------------- In Python 3.5.3 or 3.6.0: import os os.environ['THEANO_FLAGS'] = """ device=cuda0, floatX=float32, """ import theano Using cuDNN version 5105 on context None ERROR (theano.gpuarray): Could not initialize pygpu, support disabled Traceback (most recent call last): File "/opt/libs_2017_01_26/python3_env/lib/python3.5/site-packages/theano/gpuarray/__init__.py", line 164, in <module> use(config.device) File "/opt/libs_2017_01_26/python3_env/lib/python3.5/site-packages/theano/gpuarray/__init__.py", line 151, in use init_dev(device) File "/opt/libs_2017_01_26/python3_env/lib/python3.5/site-packages/theano/gpuarray/__init__.py", line 100, in init_dev pygpu.blas.gemm(0, tmp, tmp, 0, tmp, overwrite_c=True) File "pygpu/blas.pyx", line 129, in pygpu.blas.gemm (pygpu/blas.c:3354) File "pygpu/blas.pyx", line 44, in pygpu.blas.pygpu_blas_rgemm (pygpu/blas.c:2011) pygpu.gpuarray.GpuArrayException: (b'Unsupported operation', 5) ---------------------------- In Python 2.7.13: import os os.environ['THEANO_FLAGS'] = """ device=cuda0, floatX=float32, """ import theano Using cuDNN version 5105 on context None Mapped name None to device cuda0: GeForce GTX 960M (0000:01:00.0) On Friday, January 27, 2017 at 10:31:09 PM UTC+8, Tecx Nitrom wrote: > > Sorry my bad.. > > floatX (('float64', 'float32', 'float16')) > Doc: Default floating-point precision for python casts. > > Note: float16 support is experimental, use at your own risk. > Value: float32 > > warn_float64 (('ignore', 'warn', 'raise', 'pdb')) > Doc: Do an action when a tensor variable with float64 dtype is > created. They can't be run on the GPU with the current(old) gpu back-end > and are slow with gamer GPUs. > Value: ignore > > cast_policy (('custom', 'numpy+floatX')) > Doc: Rules for implicit type casting > Value: custom > > int_division (('int', 'raise', 'floatX')) > Doc: What to do when one computes x / y, where both x and y are of > integer types > Value: int > > device (cpu, gpu*, opencl*, cuda*) > Doc: Default device for computations. If cuda* or opencl*, change > thedefault to try to move computation to the GPU. Do not use upper > caseletters, only lower case even if NVIDIA uses capital letters. > Value: opencl0:1 > > init_gpu_device (, gpu*, opencl*, cuda*) > Doc: Initialize the gpu device to use, works only if device=cpu. > Unlike 'device', setting this option will NOT move computations, nor shared > variables, to the specified GPU. It can be used to run GPU-specific tests > on a particular GPU. > Value: > > force_device (<function BoolParam.<locals>.booltype at 0x7f808bfb1840>) > Doc: Raise an error if we can't use the specified device > Value: False > > print_global_stats (<function BoolParam.<locals>.booltype at > 0x7f808bfb19d8>) > Doc: Print some global statistics (time spent) at the end > Value: False > > <theano.configdefaults.ContextsParam object at 0x7f808bfb09b0> > Doc: > Context map for multi-gpu operation. Format is a > semicolon-separated list of names and device names in the > 'name->dev_name' format. An example that would map name 'test' to > device 'cuda0' and name 'test2' to device 'opencl0:0' follows: > "test->cuda0;test2->opencl0:0". > > Invalid context names are 'cpu', 'cuda*' and 'opencl*' > > Value: > > print_active_device (<function BoolParam.<locals>.booltype at > 0x7f808bfb1c80>) > Doc: Print active device at when the GPU device is initialized. > Value: True > > enable_initial_driver_test (<function BoolParam.<locals>.booltype at > 0x7f808bfb1e18>) > Doc: Tests the nvidia driver when a GPU device is initialized. > Value: True > > cuda.root (<class 'str'>) > Doc: directory with bin/, lib/, include/ for cuda utilities. > This directory is included via -L and -rpath when linking > dynamically compiled modules. If AUTO and nvcc is in the > path, it will use one of nvcc parent directory. Otherwise > /usr/local/cuda will be used. Leave empty to prevent extra > linker directives. Default: environment variable "CUDA_ROOT" > or else "AUTO". > > Value: > > <theano.configparser.ConfigParam object at 0x7f808bfb0b38> > Doc: Extra compiler flags for nvcc > Value: > > nvcc.compiler_bindir (<class 'str'>) > Doc: If defined, nvcc compiler driver will seek g++ and gcc in this > directory > Value: > > nvcc.fastmath (<function BoolParam.<locals>.booltype at 0x7f808bfb7268>) > Doc: > Value: False > > gpuarray.sync (<function BoolParam.<locals>.booltype at 0x7f808bfb7400>) > Doc: If True, every op will make sure its work is done before > returning. Setting this to True will slow down execution, > but give much more accurate results in profiling. > Value: False > > gpuarray.preallocate (<class 'float'>) > Doc: If negative it disables the allocation cache. If > between 0 and 1 it enables the allocation cache and > preallocates that fraction of the total GPU memory. If 1 > or greater it will preallocate that amount of memory (in > megabytes). > Value: 0.0 > > gpuarray.sched (('default', 'multi', 'single')) > Doc: The sched parameter passed for context creation to pygpu. > With CUDA, using "multi" is equivalent to using the > parameter > cudaDeviceScheduleYield. This is useful to lower the > CPU overhead when waiting for GPU. One user found that it > speeds up his other processes that was doing data > augmentation. > > Value: default > > gpuarray.single_stream (<function BoolParam.<locals>.booltype at > 0x7f808bfb76a8>) > Doc: > If your computations are mostly lots of small elements, > using single-stream will avoid the synchronization > overhead and usually be faster. For larger elements it > does not make a difference yet. In the future when true > multi-stream is enabled in libgpuarray, this may change. > If you want to make sure to have optimal performance, > check both options. > > Value: True > > <theano.configparser.ConfigParam object at 0x7f808bfb0e48> > Doc: This flag is deprecated; use dnn.conv.algo_fwd. > Value: True > > <theano.configparser.ConfigParam object at 0x7f808bfb0eb8> > Doc: This flag is deprecated; use `dnn.conv.algo_bwd_filter` and > `dnn.conv.algo_bwd_data` instead. > Value: True > > <theano.configparser.ConfigParam object at 0x7f808bfb9048> > Doc: This flag is deprecated; use dnn.conv.algo_bwd_data and > dnn.conv.algo_bwd_filter. > Value: True > > dnn.conv.algo_fwd (('small', 'none', 'large', 'fft', 'fft_tiling', > 'winograd', 'guess_once', 'guess_on_shape_change', 'time_once', > 'time_on_shape_change')) > Doc: Default implementation to use for cuDNN forward convolution. > Value: small > > dnn.conv.algo_bwd_data (('none', 'deterministic', 'fft', 'fft_tiling', > 'winograd', 'guess_once', 'guess_on_shape_change', 'time_once', > 'time_on_shape_change')) > Doc: Default implementation to use for cuDNN backward convolution to > get the gradients of the convolution with regard to the inputs. > Value: none > > dnn.conv.algo_bwd_filter (('none', 'deterministic', 'fft', 'small', > 'guess_once', 'guess_on_shape_change', 'time_once', > 'time_on_shape_change')) > Doc: Default implementation to use for cuDNN backward convolution to > get the gradients of the convolution with regard to the filters. > Value: none > > dnn.conv.precision (('as_input_f32', 'as_input', 'float16', 'float32', > 'float64')) > Doc: Default data precision to use for the computation in cuDNN > convolutions (defaults to the same dtype as the inputs of the convolutions, > or float32 if inputs are float16). > Value: as_input_f32 > > dnn.include_path (<class 'str'>) > Doc: Location of the cudnn header (defaults to the cuda root) > Value: > > dnn.library_path (<class 'str'>) > Doc: Location of the cudnn header (defaults to the cuda root) > Value: > > dnn.enabled (('auto', 'True', 'False')) > Doc: 'auto', use cuDNN if available, but silently fall back to not > using it if not present. If True and cuDNN can not be used, raise an error. > If False, disable cudnn > Value: auto > > assert_no_cpu_op (('ignore', 'warn', 'raise', 'pdb')) > Doc: Raise an error/warning if there is a CPU op in the computational > graph. > Value: ignore > > mode (('Mode', 'DebugMode', 'FAST_RUN', 'NanGuardMode', 'FAST_COMPILE', > 'DEBUG_MODE')) > Doc: Default compilation mode > Value: Mode > > cxx (<class 'str'>) > Doc: The C++ compiler to use. Currently only g++ is supported, but > supporting additional compilers should not be too difficult. If it is > empty, no C++ code is compiled. > Value: /usr/bin/g++ > > linker (('cvm', 'c|py', 'py', 'c', 'c|py_nogc', 'vm', 'vm_nogc', > 'cvm_nogc')) > Doc: Default linker used if the theano flags mode is Mode > Value: cvm > > allow_gc (<function BoolParam.<locals>.booltype at 0x7f808bfbbae8>) > Doc: Do we default to delete intermediate results during Theano > function calls? Doing so lowers the memory requirement, but asks that we > reallocate memory at the next function call. This is implemented for the > default linker, but may not work for all linkers. > Value: True > > optimizer (('fast_run', 'merge', 'fast_compile', 'None')) > Doc: Default optimizer. If not None, will use this optimizer with the > Mode > Value: fast_run > > optimizer_verbose (<function BoolParam.<locals>.booltype at > 0x7f808bfbbd08>) > Doc: If True, we print all optimization being applied > Value: False > > on_opt_error (('warn', 'raise', 'pdb', 'ignore')) > Doc: What to do when an optimization crashes: warn and skip it, raise > the exception, or fall into the pdb debugger. > Value: warn > > <theano.configparser.ConfigParam object at 0x7f808bfb9da0> > Doc: This config option was removed in 0.5: do not use it! > Value: True > > nocleanup (<function BoolParam.<locals>.booltype at 0x7f808bf4c048>) > Doc: Suppress the deletion of code files that did not compile cleanly > Value: False > > on_unused_input (('raise', 'warn', 'ignore')) > Doc: What to do if a variable in the 'inputs' list of > theano.function() is not used in the graph. > Value: raise > > tensor.cmp_sloppy (<class 'int'>) > Doc: Relax tensor._allclose (0) not at all, (1) a bit, (2) more > Value: 0 > > tensor.local_elemwise_fusion (<function BoolParam.<locals>.booltype at > 0x7f808bf4c378>) > Doc: Enable or not in fast_run mode(fast_run optimization) the > elemwise fusion optimization > Value: True > > gpu.local_elemwise_fusion (<function BoolParam.<locals>.booltype at > 0x7f808bf4c510>) > Doc: Enable or not in fast_run mode(fast_run optimization) the gpu > elemwise fusion optimization > Value: True > > lib.amdlibm (<function BoolParam.<locals>.booltype at 0x7f808bf4c6a8>) > Doc: Use amd's amdlibm numerical library > Value: False > > gpuelemwise.sync (<function BoolParam.<locals>.booltype at > 0x7f808bf4c840>) > Doc: when true, wait that the gpu fct finished and check it error > code. > Value: True > > traceback.limit (<class 'int'>) > Doc: The number of stack to trace. -1 mean all. > Value: 8 > > traceback.compile_limit (<class 'int'>) > Doc: The number of stack to trace to keep during compilation. -1 mean > all. If greater then 0, will also make us save Theano internal stack trace. > Value: 0 > > experimental.unpickle_gpu_on_cpu (<function BoolParam.<locals>.booltype at > 0x7f808bf4cae8>) > Doc: Allow unpickling of pickled CudaNdarrays as numpy.ndarrays.This > is useful, if you want to open a CudaNdarray without having cuda > installed.If you have cuda installed, this will force unpickling tobe done > on the cpu to numpy.ndarray.Please be aware that this may get you access to > the data,however, trying to unpicke gpu functions will not succeed.This > flag is experimental and may be removed any time, whengpu<>cpu transparency > is solved. > Value: False > > numpy.seterr_all (('ignore', 'warn', 'raise', 'call', 'print', 'log', > 'None')) > Doc: ("Sets numpy's behaviour for floating-point errors, ", "see > numpy.seterr. 'None' means not to change numpy's default, which can be > different for different numpy releases. This flag sets the default > behaviour for all kinds of floating-point errors, its effect can be > overriden for specific errors by the following flags: seterr_divide, > seterr_over, seterr_under and seterr_invalid.") > Value: ignore > > numpy.seterr_divide (('None', 'ignore', 'warn', 'raise', 'call', 'print', > 'log')) > Doc: Sets numpy's behavior for division by zero, see numpy.seterr. > 'None' means using the default, defined by numpy.seterr_all. > Value: None > > numpy.seterr_over (('None', 'ignore', 'warn', 'raise', 'call', 'print', > 'log')) > Doc: Sets numpy's behavior for floating-point overflow, see > numpy.seterr. 'None' means using the default, defined by numpy.seterr_all. > Value: None > > numpy.seterr_under (('None', 'ignore', 'warn', 'raise', 'call', 'print', > 'log')) > Doc: Sets numpy's behavior for floating-point underflow, see > numpy.seterr. 'None' means using the default, defined by numpy.seterr_all. > Value: None > > numpy.seterr_invalid (('None', 'ignore', 'warn', 'raise', 'call', 'print', > 'log')) > Doc: Sets numpy's behavior for invalid floating-point operation, see > numpy.seterr. 'None' means using the default, defined by numpy.seterr_all. > Value: None > > warn.ignore_bug_before (('0.7', 'None', 'all', '0.3', '0.4', '0.4.1', > '0.5', '0.6', '0.7', '0.8', '0.8.1', '0.8.2', '0.9')) > Doc: If 'None', we warn about all Theano bugs found by default. If > 'all', we don't warn about Theano bugs found by default. If a version, we > print only the warnings relative to Theano bugs found after that version. > Warning for specific bugs can be configured with specific [warn] flags. > Value: 0.7 > > warn.argmax_pushdown_bug (<function BoolParam.<locals>.booltype at > 0x7f808bfc00d0>) > Doc: Warn if in past version of Theano we generated a bug with the > theano.tensor.nnet.nnet.local_argmax_pushdown optimization. Was fixed 27 > may 2010 > Value: False > > warn.gpusum_01_011_0111_bug (<function BoolParam.<locals>.booltype at > 0x7f808bfc0268>) > Doc: Warn if we are in a case where old version of Theano had a > silent bug with GpuSum pattern 01,011 and 0111 when the first dimensions > was bigger then 4096. Was fixed 31 may 2010 > Value: False > > warn.sum_sum_bug (<function BoolParam.<locals>.booltype at > 0x7f808bfc0400>) > Doc: Warn if we are in a case where Theano version between version > 9923a40c7b7a and the 2 august 2010 (fixed date), generated an error in that > case. This happens when there are 2 consecutive sums in the graph, bad code > was generated. Was fixed 2 August 2010 > Value: False > > warn.sum_div_dimshuffle_bug (<function BoolParam.<locals>.booltype at > 0x7f808bfc0598>) > Doc: Warn if previous versions of Theano (between rev. 3bd9b789f5e8, > 2010-06-16, and cfc6322e5ad4, 2010-08-03) would have given incorrect > result. This bug was triggered by sum of division of dimshuffled tensors. > Value: False > > warn.subtensor_merge_bug (<function BoolParam.<locals>.booltype at > 0x7f808bfc0730>) > Doc: Warn if previous versions of Theano (before 0.5rc2) could have > given incorrect results when indexing into a subtensor with negative stride > (for instance, for instance, x[a:b:-1][c]). > Value: False > > warn.gpu_set_subtensor1 (<function BoolParam.<locals>.booltype at > 0x7f808bfc08c8>) > Doc: Warn if previous versions of Theano (before 0.6) could have > given incorrect results when moving to the gpu set_subtensor(x[int vector], > new_value) > Value: False > > warn.vm_gc_bug (<function BoolParam.<locals>.booltype at 0x7f808bfc0a60>) > Doc: There was a bug that existed in the default Theano > configuration, only in the development version between July 5th 2012 and > July 30th 2012. This was not in a released version. If your code was > affected by this bug, a warning will be printed during the code execution > if you use the `linker=vm,vm.lazy=True,warn.vm_gc_bug=True` Theano flags. > This warning is disabled by default as the bug was not released. > Value: False > > warn.signal_conv2d_interface (<function BoolParam.<locals>.booltype at > 0x7f808bfc0bf8>) > Doc: Warn we use the new signal.conv2d() when its interface changed > mid June 2014 > Value: False > > warn.reduce_join (<function BoolParam.<locals>.booltype at > 0x7f808bfc0d90>) > Doc: Your current code is fine, but Theano versions prior to 0.7 (or > this development version) might have given an incorrect result. To disable > this warning, set the Theano flag warn.reduce_join to False. The problem > was an optimization, that modified the pattern > "Reduce{scalar.op}(Join(axis=0, a, b), axis=0)", did not check the > reduction axis. So if the reduction axis was not 0, you got a wrong answer. > Value: False > > warn.inc_set_subtensor1 (<function BoolParam.<locals>.booltype at > 0x7f808bfc0f28>) > Doc: Warn if previous versions of Theano (before 0.7) could have > given incorrect results for inc_subtensor and set_subtensor when using some > patterns of advanced indexing (indexing with one vector or matrix of ints). > Value: False > > warn.round (<function BoolParam.<locals>.booltype at 0x7f808bf52158>) > Doc: Round changed its default from Seed to use for randomized unit > tests. Special value 'random' means using a seed of None. > Value: True > > compute_test_value (('off', 'ignore', 'warn', 'raise', 'pdb')) > Doc: If 'True', Theano will run each op at graph build time, using > Constants, SharedVariables and the tag 'test_value' as inputs to the > function. This helps the user track down problems in the graph before it > gets optimized. > Value: off > > print_test_value (<function BoolParam.<locals>.booltype at > 0x7f808bf52378>) > Doc: If 'True', the __eval__ of a Theano variable will return its > test_value when this is available. This has the practical conseguence that, > e.g., in debugging `my_var` will print the same as `my_var.tag.test_value` > when a test value is defined. > Value: False > > compute_test_value_opt (('off', 'ignore', 'warn', 'raise', 'pdb')) > Doc: For debugging Theano optimization only. Same as > compute_test_value, but is used during Theano optimization > Value: off > > unpickle_function (<function BoolParam.<locals>.booltype at > 0x7f808bf52598>) > Doc: Replace unpickled Theano functions with None. This is useful to > unpickle old graphs that pickled them when it shouldn't > Value: True > > reoptimize_unpickled_function (<function BoolParam.<locals>.booltype at > 0x7f808bf52730>) > Doc: Re-optimize the graph when a theano function is unpickled from > the disk. > Value: False > > exception_verbosity (('low', 'high')) > Doc: If 'low', the text of exceptions will generally refer to apply > nodes with short names such as Elemwise{add_no_inplace}. If 'high', some > exceptions will also refer to apply nodes with long descriptions like: > A. Elemwise{add_no_inplace} > B. log_likelihood_v_given_h > C. log_likelihood_h > Value: low > > openmp (<function BoolParam.<locals>.booltype at 0x7f808bf52950>) > Doc: Allow (or not) parallel computation on the CPU with OpenMP. This > is the default value used when creating an Op that supports OpenMP > parallelization. It is preferable to define it via the Theano configuration > file ~/.theanorc or with the environment variable THEANO_FLAGS. > Parallelization is only done for some operations that implement it, and > even for operations that implement parallelism, each operation is free to > respect this flag or not. You can control the number of threads used with > the environment variable OMP_NUM_THREADS. If it is set to 1, we disable > openmp in Theano by default. > Value: False > > openmp_elemwise_minsize (<class 'int'>) > Doc: If OpenMP is enabled, this is the minimum size of vectors for > which the openmp parallelization is enabled in element wise ops. > Value: 200000 > > check_input (<function BoolParam.<locals>.booltype at 0x7f808bf52b70>) > Doc: Specify if types should check their input in their C code. It > can be used to speed up compilation, reduce overhead (particularly for > scalars) and reduce the number of generated C files. > Value: True > > cache_optimizations (<function BoolParam.<locals>.booltype at > 0x7f808bf52d08>) > Doc: WARNING: work in progress, does not work yet. Specify if the > optimization cache should be used. This cache will any optimized graph and > its optimization. Actually slow downs a lot the first optimization, and > could possibly still contains some bugs. Use at your own risks. > Value: False > > unittests.rseed (<class 'str'>) > Doc: Seed to use for randomized unit tests. Special value 'random' > means using a seed of None. > Value: 666 > > NanGuardMode.nan_is_error (<function BoolParam.<locals>.booltype at > 0x7f808bf54048>) > Doc: Default value for nan_is_error > Value: True > > NanGuardMode.inf_is_error (<function BoolParam.<locals>.booltype at > 0x7f808bf541e0>) > Doc: Default value for inf_is_error > Value: True > > NanGuardMode.big_is_error (<function BoolParam.<locals>.booltype at > 0x7f808bf54378>) > Doc: Default value for big_is_error > Value: True > > NanGuardMode.action (('raise', 'warn', 'pdb')) > Doc: What NanGuardMode does when it finds a problem > Value: raise > > optimizer_excluding (<class 'str'>) > Doc: When using the default mode, we will remove optimizer with these > tags. Separate tags with ':'. > Value: > > optimizer_including (<class 'str'>) > Doc: When using the default mode, we will add optimizer with these > tags. Separate tags with ':'. > Value: > > optimizer_requiring (<class 'str'>) > Doc: When using the default mode, we will require optimizer with > these tags. Separate tags with ':'. > Value: > > DebugMode.patience (<class 'int'>) > Doc: Optimize graph this many times to detect inconsistency > Value: 10 > > DebugMode.check_c (<function BoolParam.<locals>.booltype at > 0x7f808bf548c8>) > Doc: Run C implementations where possible > Value: True > > DebugMode.check_py (<function BoolParam.<locals>.booltype at > 0x7f808bf54a60>) > Doc: Run Python implementations where possible > Value: True > > DebugMode.check_finite (<function BoolParam.<locals>.booltype at > 0x7f808bf54bf8>) > Doc: True -> complain about NaN/Inf results > Value: True > > DebugMode.check_strides (<class 'int'>) > Doc: Check that Python- and C-produced ndarrays have same strides. On > difference: (0) - ignore, (1) warn, or (2) raise error > Value: 0 > > DebugMode.warn_input_not_reused (<function BoolParam.<locals>.booltype at > 0x7f808bf54ea0>) > Doc: Generate a warning when destroy_map or view_map says that an op > works inplace, but the op did not reuse the input for its output. > Value: True > > DebugMode.check_preallocated_output (<class 'str'>) > Doc: Test thunks with pre-allocated memory as output storage. This is > a list of strings separated by ":". Valid values are: "initial" (initial > storage in storage map, happens with Scan),"previous" (previously-returned > memory), "c_contiguous", "f_contiguous", "strided" (positive and negative > strides), "wrong_size" (larger and smaller dimensions), and "ALL" (all of > the above). > Value: > > DebugMode.check_preallocated_output_ndim (<class 'int'>) > Doc: When testing with "strided" preallocated output memory, test all > combinations of strides over that number of (inner-most) dimensions. You > may want to reduce that number to reduce memory or time usage, but it is > advised to keep a minimum of 2. > Value: 4 > > profiling.time_thunks (<function BoolParam.<locals>.booltype at > 0x7f808bf582f0>) > Doc: Time individual thunks when profiling > Value: True > > profiling.n_apply (<class 'int'>) > Doc: Number of Apply instances to print by default > Value: 20 > > profiling.n_ops (<class 'int'>) > Doc: Number of Ops to print by default > Value: 20 > > profiling.output_line_width (<class 'int'>) > Doc: Max line width for the profiling output > Value: 512 > > profiling.min_memory_size (<class 'int'>) > Doc: For the memory profile, do not print Apply nodes if the size > of their outputs (in bytes) is lower than this threshold > Value: 1024 > > profiling.min_peak_memory (<function BoolParam.<locals>.booltype at > 0x7f808bf588c8>) > Doc: The min peak memory usage of the order > Value: False > > profiling.destination (<class 'str'>) > Doc: > File destination of the profiling output > > Value: stderr > > profiling.debugprint (<function BoolParam.<locals>.booltype at > 0x7f808bf58ae8>) > Doc: > Do a debugprint of the profiled functions > > Value: False > > profiling.ignore_first_call (<function BoolParam.<locals>.booltype at > 0x7f808bf58c80>) > Doc: > Do we ignore the first call of a Theano function. > > Value: False > > optdb.position_cutoff (<class 'float'>) > Doc: Where to stop eariler during optimization. It represent the > position of the optimizer where to stop. > Value: inf > > optdb.max_use_ratio (<class 'float'>) > Doc: A ratio that prevent infinite loop in EquilibriumOptimizer. > Value: 8.0 > > gcc.cxxflags (<class 'str'>) > Doc: Extra compiler flags for gcc > Value: > > cmodule.warn_no_version (<function BoolParam.<locals>.booltype at > 0x7f808bf5c048>) > Doc: If True, will print a warning when compiling one or more Op with > C code that can't be cached because there is no c_code_cache_version() > function associated to at least one of those Ops. > Value: False > > cmodule.remove_gxx_opt (<function BoolParam.<locals>.booltype at > 0x7f808bf5c1e0>) > Doc: If True, will remove the -O* parameter passed to g++.This is > useful to debug in gdb modules compiled by Theano.The parameter -g is > passed by default to g++ > Value: False > > cmodule.compilation_warning (<function BoolParam.<locals>.booltype at > 0x7f808bf5c378>) > Doc: If True, will print compilation warnings. > Value: False > > cmodule.preload_cache (<function BoolParam.<locals>.booltype at > 0x7f808bf5c510>) > Doc: If set to True, will preload the C module cache at import time > Value: False > > cmodule.age_thresh_use (<class 'int'>) > Doc: In seconds. The time after which Theano won't reuse a compile c > module. > Value: 2073600 > > blas.ldflags (<class 'str'>) > Doc: lib[s] to include for [Fortran] level-3 blas implementation > Value: > > metaopt.verbose (<function BoolParam.<locals>.booltype at 0x7f808bf5c8c8>) > Doc: Enable verbose output for meta optimizers > Value: False > > profile (<function BoolParam.<locals>.booltype at 0x7f808bf5ca60>) > Doc: If VM should collect profile information > Value: False > > profile_optimizer (<function BoolParam.<locals>.booltype at > 0x7f808bf5cbf8>) > Doc: If VM should collect optimizer profile information > Value: False > > profile_memory (<function BoolParam.<locals>.booltype at 0x7f808bf5cd90>) > Doc: If VM should collect memory profile information and print it > Value: False > > <theano.configparser.ConfigParam object at 0x7f808bf5e2e8> > Doc: Useful only for the vm linkers. When lazy is None, auto detect > if lazy evaluation is needed and use the apropriate version. If lazy is > True/False, force the version used between Loop/LoopGC and Stack. > Value: None > > warn.identify_1pexp_bug (<function BoolParam.<locals>.booltype at > 0x7f808bf5f048>) > Doc: Warn if Theano versions prior to 7987b51 (2011-12-18) could have > yielded a wrong result due to a bug in the is_1pexp function > Value: False > > on_shape_error (('warn', 'raise')) > Doc: warn: print a warning and use the default value. raise: raise an > error > Value: warn > > tensor.insert_inplace_optimizer_validate_nb (<class 'int'>) > Doc: -1: auto, if graph have less then 500 nodes 1, else 10 > Value: -1 > > experimental.local_alloc_elemwise (<function BoolParam.<locals>.booltype > at 0x7f808bf5f378>) > Doc: DEPRECATED: If True, enable the experimental optimization > local_alloc_elemwise. Generates error if not True. Use > optimizer_excluding=local_alloc_elemwise to dsiable. > Value: True > > experimental.local_alloc_elemwise_assert (<function > BoolParam.<locals>.booltype at 0x7f808bf5f400>) > Doc: When the local_alloc_elemwise is applied, add an assert to > highlight shape errors. > Value: True > > scan.allow_gc (<function BoolParam.<locals>.booltype at 0x7f808bf5f620>) > Doc: Allow/disallow gc inside of Scan (default: False) > Value: False > > scan.allow_output_prealloc (<function BoolParam.<locals>.booltype at > 0x7f808bf5f7b8>) > Doc: Allow/disallow memory preallocation for outputs inside of scan > (default: True) > Value: True > > scan.debug (<function BoolParam.<locals>.booltype at 0x7f808bf5f950>) > Doc: If True, enable extra verbose output related to scan > Value: False > > pycuda.init (<function BoolParam.<locals>.booltype at 0x7f808bf5fae8>) > Doc: If True, always initialize PyCUDA when Theano want to > initilize the GPU. Currently, we must always initialize > PyCUDA before Theano do it. Setting this flag to True, > ensure that, but always import PyCUDA. It can be done > manually by importing theano.misc.pycuda_init before theano > initialize the GPU device. > > Value: False > > cublas.lib (<class 'str'>) > Doc: Name of the cuda blas library for the linker. > Value: cublas > > lib.cnmem (<class 'float'>) > Doc: Do we enable CNMeM or not (a faster CUDA memory allocator). > > The parameter represent the start size (in MB or % of > total GPU memory) of the memory pool. > > 0: not enabled. > 0 < N <= 1: % of the total GPU memory (clipped to .985 for > driver memory) > > 0: use that number of MB of memory. > > > Value: 0.0 > > compile.wait (<class 'int'>) > Doc: Time to wait before retrying to aquire the compile lock. > Value: 5 > > compile.timeout (<class 'int'>) > Doc: In seconds, time that a process will wait before deciding to > override an existing lock. An override only happens when the existing > lock is held by the same owner *and* has not been 'refreshed' by this > owner for more than this period. Refreshes are done every half timeout > period for running processes. > Value: 120 > > compiledir_format (<class 'str'>) > Doc: Format string for platform-dependent compiled module subdirectory > (relative to base_compiledir). Available keys: device, gxx_version, > hostname, numpy_version, platform, processor, python_bitwidth, > python_int_bitwidth, python_version, short_platform, theano_version. > Defaults to 'compiledir_%(short_platform)s-%(processor)s-%(python_vers > ion)s-%(python_bitwidth)s'. > Value: > compiledir_%(short_platform)s-%(processor)s-%(python_version)s-%(python_bitwidth)s > > <theano.configparser.ConfigParam object at 0x7f808bf5eda0> > Doc: platform-independent root directory for compiled modules > Value: /home/alishan/.theano > > <theano.configparser.ConfigParam object at 0x7f808bf5ef60> > Doc: platform-dependent cache directory for compiled modules > Value: > /home/alishan/.theano/compiledir_Linux-4.4--MANJARO-x86_64-with-glibc2.3.4--3.6.0-64 > > > > > > On Fri, Jan 27, 2017 at 7:46 PM, Frédéric Bastien <[email protected] > <javascript:>> wrote: > >> Try to answer all the questions in my email. Otherwise it will delay the >> help we can offer. >> >> What are your Theano flag? >> >> On Fri, Jan 27, 2017 at 9:08 AM, Tecx Nitrom <[email protected] >> <javascript:>> wrote: >> >>> I do not know theano version. But it is latest pull made from theano >>> git repo >>> >>> On Fri, Jan 27, 2017 at 7:15 PM, Frédéric Bastien <[email protected] >>> <javascript:>> wrote: >>> >>>> Hi, >>>> >>>> To be sure, you use the development version of Theano, not Theano >>>> 0.8.2? And you also installed the development version of libgpuarray? >>>> >>>> What are your Theano flag? >>>> >>>> Fred >>>> >>>> On Fri, Jan 27, 2017 at 6:21 AM, Tecx Nitrom <[email protected] >>>> <javascript:>> wrote: >>>> >>>>> >>>>> I am trying to set theano to use gpu but getting Gpu Array Exception. >>>>> >>>>> >>>>> Using Theano backend. >>>>> ERROR (theano.gpuarray): Could not initialize pygpu, support disabled >>>>> Traceback (most recent call last): >>>>> File "/usr/lib/python3.6/site-packages/theano/gpuarray/__init__.py", >>>>> line 164, in <module> >>>>> use(config.device) >>>>> File "/usr/lib/python3.6/site-packages/theano/gpuarray/__init__.py", >>>>> line 151, in use >>>>> init_dev(device) >>>>> File "/usr/lib/python3.6/site-packages/theano/gpuarray/__init__.py", >>>>> line 100, in init_dev >>>>> pygpu.blas.gemm(0, tmp, tmp, 0, tmp, overwrite_c=True) >>>>> File "pygpu/blas.pyx", line 129, in pygpu.blas.gemm >>>>> (pygpu/blas.c:3354) >>>>> File "pygpu/blas.pyx", line 44, in pygpu.blas.pygpu_blas_rgemm >>>>> (pygpu/blas.c:2011) >>>>> pygpu.gpuarray.GpuArrayException: (b'Unsupported operation', 5) >>>>> >>>>> -- >>>>> >>>>> --- >>>>> You received this message because you are subscribed to the Google >>>>> Groups "theano-users" group. >>>>> To unsubscribe from this group and stop receiving emails from it, send >>>>> an email to [email protected] <javascript:>. >>>>> For more options, visit https://groups.google.com/d/optout. >>>>> >>>> >>>> -- >>>> >>>> --- >>>> You received this message because you are subscribed to a topic in the >>>> Google Groups "theano-users" group. >>>> To unsubscribe from this topic, visit >>>> https://groups.google.com/d/topic/theano-users/GQJ8yojgJo4/unsubscribe. >>>> To unsubscribe from this group and all its topics, send an email to >>>> [email protected] <javascript:>. >>>> For more options, visit https://groups.google.com/d/optout. >>>> >>> >>> -- >>> >>> --- >>> You received this message because you are subscribed to the Google >>> Groups "theano-users" group. >>> To unsubscribe from this group and stop receiving emails from it, send >>> an email to [email protected] <javascript:>. >>> For more options, visit https://groups.google.com/d/optout. >>> >> >> -- >> >> --- >> You received this message because you are subscribed to a topic in the >> Google Groups "theano-users" group. >> To unsubscribe from this topic, visit >> https://groups.google.com/d/topic/theano-users/GQJ8yojgJo4/unsubscribe. >> To unsubscribe from this group and all its topics, send an email to >> [email protected] <javascript:>. >> For more options, visit https://groups.google.com/d/optout. >> > > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
