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]> 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]> 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]> 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]>
>>> 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)
>>>>
>>>> --
>>>>
>>>> ---
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>>>> 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.
>>>>
>>>
>>> --
>>>
>>> ---
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>>>
>>
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>>
>> ---
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>>
>
> --
>
> ---
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> Google Groups "theano-users" group.
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> topic/theano-users/GQJ8yojgJo4/unsubscribe.
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