Method not defined I0e.c_code

[Sayam753]

If you have any questions, please ask the theano-user mailing list or stackoverflow (using the "theano" tag) first.

I was on the way to merge fix_mv_random branch from PR pymc-devs/pymc3#4207 with @michaelosthege's PR pymc-devs/pymc3#4214 branch. Then, there arises a theano issue while running the test suite locally.

Description of your problem or feature request

Please provide a minimal, self-contained, and reproducible example.
Here is a reproducible snippet

$ mkvirtualenv test_pymc3
(test_pymc3)$ git clone https://github.com/pymc-devs/pymc3.git
(test_pymc3)$ cd pymc3; pip install -e .
(test_pymc3)$ pip install --upgrade git+https://github.com/pymc-devs/Theano-PyMC.git@master pytest
(test_pymc3)$ gh pr checkout 4218
(test_pymc3)$ git rebase master
(test_pymc3)$ pytest -v pymc3/tests/test_distributions.py::TestMatchesScipy::test_rice

Please provide the full traceback of any errors.

Method not defined `I0e.c_code`

=================================================== test session starts ===================================================
platform darwin -- Python 3.8.5, pytest-6.1.1, py-1.9.0, pluggy-0.13.1 -- /Users/user/Env/test_pymc3/bin/python
cachedir: .pytest_cache
rootdir: /Users/user/pymc3, configfile: setup.cfg
collected 1 item                                                                                                          

pymc3/tests/test_distributions.py::TestMatchesScipy::test_rice FAILED                                               [100%]

======================================================== FAILURES =========================================================
_______________________________________________ TestMatchesScipy.test_rice ________________________________________________

self = <pymc3.tests.test_distributions.TestMatchesScipy object at 0x12016fbe0>

    def test_rice(self):
>       self.pymc3_matches_scipy(
            Rice,
            Rplus,
            {"nu": Rplus, "sigma": Rplusbig},
            lambda value, nu, sigma: sp.rice.logpdf(value, b=nu / sigma, loc=0, scale=sigma),
        )

pymc3/tests/test_distributions.py:1630: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
pymc3/tests/test_distributions.py:527: in pymc3_matches_scipy
    self.check_logp(model, value, domain, paramdomains, logp, decimal=decimal)
pymc3/tests/test_distributions.py:532: in check_logp
    logp = model.fastlogp
pymc3/model.py:438: in fastlogp
    return self.model.fastfn(self.logpt)
pymc3/model.py:1277: in fastfn
    f = self.makefn(outs, mode, *args, **kwargs)
pymc3/model.py:1238: in makefn
    return theano.function(
/usr/local/lib/python3.8/site-packages/theano/compile/function/__init__.py:337: in function
    fn = pfunc(
/usr/local/lib/python3.8/site-packages/theano/compile/function/pfunc.py:538: in pfunc
    return orig_function(
/usr/local/lib/python3.8/site-packages/theano/compile/function/types.py:1997: in orig_function
    fn = m.create(defaults)
/usr/local/lib/python3.8/site-packages/theano/compile/function/types.py:1850: in create
    _fn, _i, _o = self.linker.make_thunk(
/usr/local/lib/python3.8/site-packages/theano/gof/link.py:738: in make_thunk
    return self.make_all(
/usr/local/lib/python3.8/site-packages/theano/gof/vm.py:1202: in make_all
    vm = self.make_vm(
/usr/local/lib/python3.8/site-packages/theano/gof/vm.py:978: in make_vm
    dependency_map_list = [
/usr/local/lib/python3.8/site-packages/theano/gof/vm.py:979: in <listcomp>
    [vars_idx[d] for d in dependency_map[vars_idx_inv[i]]]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

.0 = <list_iterator object at 0x124ca6460>

>       [vars_idx[d] for d in dependency_map[vars_idx_inv[i]]]
        for i in range(len(vars_idx_inv))
    ]
E   KeyError: Elemwise{Composite{i0e((i0 * i1))}}.0

/usr/local/lib/python3.8/site-packages/theano/gof/vm.py:979: KeyError
-------------------------------------------------- Captured stderr call ---------------------------------------------------
WARNING (theano.tensor.opt): i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING (theano.tensor.opt): i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING (theano.tensor.opt): i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING (theano.tensor.opt): i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING (theano.tensor.opt): i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING (theano.tensor.opt): i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING (theano.tensor.opt): i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING (theano.tensor.opt): i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING (theano.tensor.opt): i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING (theano.tensor.opt): i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING (theano.tensor.opt): Composite{i0e((i0 * i1))} does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
ERROR (theano.gof.opt): Optimization failure due to: LocalOptGroup(local_inplace_gemm,local_inplace_gemv,local_inplace_ger)
ERROR (theano.gof.opt): node: Elemwise{Composite{i0e((i0 * i1))}}(Elemwise{true_div,no_inplace}.0, Elemwise{true_div,no_inplace}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 2129, in process_node
    replacements = lopt.transform(node)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 1428, in transform
    + self.track_map[node.op]
  File "/usr/local/lib/python3.8/site-packages/theano/gof/utils.py", line 204, in __hash__
    return hash((type(self), tuple(getattr(self, a) for a in props)))
  File "/usr/local/lib/python3.8/site-packages/theano/scalar/basic.py", line 4442, in __hash__
    self.init_c_code()  # self._c_code and self.nodenames
  File "/usr/local/lib/python3.8/site-packages/theano/scalar/basic.py", line 4164, in init_c_code
    s = node.op.c_code(
  File "/usr/local/lib/python3.8/site-packages/theano/gof/op.py", line 364, in c_code
    raise MethodNotDefined("%s.c_code" % self.__class__.__name__)
theano.gof.utils.MethodNotDefined: I0e.c_code

ERROR (theano.gof.opt): Optimization failure due to: LocalOptGroup(make_c_ger_destructive,make_c_gemv_destructive)
ERROR (theano.gof.opt): node: Elemwise{Composite{i0e((i0 * i1))}}(Elemwise{true_div,no_inplace}.0, Elemwise{true_div,no_inplace}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 2129, in process_node
    replacements = lopt.transform(node)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 1428, in transform
    + self.track_map[node.op]
  File "/usr/local/lib/python3.8/site-packages/theano/gof/utils.py", line 204, in __hash__
    return hash((type(self), tuple(getattr(self, a) for a in props)))
  File "/usr/local/lib/python3.8/site-packages/theano/scalar/basic.py", line 4442, in __hash__
    self.init_c_code()  # self._c_code and self.nodenames
  File "/usr/local/lib/python3.8/site-packages/theano/scalar/basic.py", line 4164, in init_c_code
    s = node.op.c_code(
  File "/usr/local/lib/python3.8/site-packages/theano/gof/op.py", line 364, in c_code
    raise MethodNotDefined("%s.c_code" % self.__class__.__name__)
theano.gof.utils.MethodNotDefined: I0e.c_code

ERROR (theano.gof.opt): SeqOptimizer apply <theano.tensor.opt.InplaceElemwiseOptimizer object at 0x11acde6a0>
ERROR (theano.gof.opt): Traceback:
ERROR (theano.gof.opt): Traceback (most recent call last):
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 249, in apply
    sub_prof = optimizer.optimize(fgraph)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 89, in optimize
    ret = self.apply(fgraph, *args, **kwargs)
  File "/usr/local/lib/python3.8/site-packages/theano/tensor/opt.py", line 472, in apply
    fgraph.replace(
  File "/usr/local/lib/python3.8/site-packages/theano/gof/fg.py", line 528, in replace
    self.change_input(node, i, new_r, reason=reason)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/fg.py", line 440, in change_input
    self.__import_r__(new_r, reason=reason)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/fg.py", line 326, in __import_r__
    self.__import__(variable.owner, reason=reason)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/fg.py", line 396, in __import__
    self.execute_callbacks("on_import", node, reason)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/fg.py", line 608, in execute_callbacks
    fn(self, *args, **kwargs)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 606, in on_import
    self.process_node(fgraph, node)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 738, in process_node
    if inputs_match and node.op == candidate.op:
  File "/usr/local/lib/python3.8/site-packages/theano/gof/utils.py", line 211, in __eq__
    return type(self) == type(other) and tuple(
  File "/usr/local/lib/python3.8/site-packages/theano/scalar/basic.py", line 4437, in __eq__
    self.init_c_code()  # self._c_code and self.nodenames
  File "/usr/local/lib/python3.8/site-packages/theano/scalar/basic.py", line 4164, in init_c_code
    s = node.op.c_code(
  File "/usr/local/lib/python3.8/site-packages/theano/gof/op.py", line 364, in c_code
    raise MethodNotDefined("%s.c_code" % self.__class__.__name__)
theano.gof.utils.MethodNotDefined: I0e.c_code

---------------------------------------------------- Captured log call ----------------------------------------------------
WARNING  theano.tensor.opt:opt.py:7625 i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING  theano.tensor.opt:opt.py:7625 i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING  theano.tensor.opt:opt.py:7625 i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING  theano.tensor.opt:opt.py:7625 i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING  theano.tensor.opt:opt.py:7625 i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING  theano.tensor.opt:opt.py:7625 i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING  theano.tensor.opt:opt.py:7625 i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING  theano.tensor.opt:opt.py:7625 i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING  theano.tensor.opt:opt.py:7625 i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING  theano.tensor.opt:opt.py:7694 i0e does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
WARNING  theano.tensor.opt:opt.py:7625 Composite{i0e((i0 * i1))} does not implement the c_code function. As well as being potentially slow, this disables loop fusion of this op.
ERROR    theano.gof.opt:opt.py:2007 Optimization failure due to: LocalOptGroup(local_inplace_gemm,local_inplace_gemv,local_inplace_ger)
ERROR    theano.gof.opt:opt.py:2008 node: Elemwise{Composite{i0e((i0 * i1))}}(Elemwise{true_div,no_inplace}.0, Elemwise{true_div,no_inplace}.0)
ERROR    theano.gof.opt:opt.py:2009 TRACEBACK:
ERROR    theano.gof.opt:opt.py:2010 Traceback (most recent call last):
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 2129, in process_node
    replacements = lopt.transform(node)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 1428, in transform
    + self.track_map[node.op]
  File "/usr/local/lib/python3.8/site-packages/theano/gof/utils.py", line 204, in __hash__
    return hash((type(self), tuple(getattr(self, a) for a in props)))
  File "/usr/local/lib/python3.8/site-packages/theano/scalar/basic.py", line 4442, in __hash__
    self.init_c_code()  # self._c_code and self.nodenames
  File "/usr/local/lib/python3.8/site-packages/theano/scalar/basic.py", line 4164, in init_c_code
    s = node.op.c_code(
  File "/usr/local/lib/python3.8/site-packages/theano/gof/op.py", line 364, in c_code
    raise MethodNotDefined("%s.c_code" % self.__class__.__name__)
theano.gof.utils.MethodNotDefined: I0e.c_code

ERROR    theano.gof.opt:opt.py:2007 Optimization failure due to: LocalOptGroup(make_c_ger_destructive,make_c_gemv_destructive)
ERROR    theano.gof.opt:opt.py:2008 node: Elemwise{Composite{i0e((i0 * i1))}}(Elemwise{true_div,no_inplace}.0, Elemwise{true_div,no_inplace}.0)
ERROR    theano.gof.opt:opt.py:2009 TRACEBACK:
ERROR    theano.gof.opt:opt.py:2010 Traceback (most recent call last):
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 2129, in process_node
    replacements = lopt.transform(node)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 1428, in transform
    + self.track_map[node.op]
  File "/usr/local/lib/python3.8/site-packages/theano/gof/utils.py", line 204, in __hash__
    return hash((type(self), tuple(getattr(self, a) for a in props)))
  File "/usr/local/lib/python3.8/site-packages/theano/scalar/basic.py", line 4442, in __hash__
    self.init_c_code()  # self._c_code and self.nodenames
  File "/usr/local/lib/python3.8/site-packages/theano/scalar/basic.py", line 4164, in init_c_code
    s = node.op.c_code(
  File "/usr/local/lib/python3.8/site-packages/theano/gof/op.py", line 364, in c_code
    raise MethodNotDefined("%s.c_code" % self.__class__.__name__)
theano.gof.utils.MethodNotDefined: I0e.c_code

ERROR    theano.gof.opt:opt.py:188 SeqOptimizer apply <theano.tensor.opt.InplaceElemwiseOptimizer object at 0x11acde6a0>
ERROR    theano.gof.opt:opt.py:189 Traceback:
ERROR    theano.gof.opt:opt.py:190 Traceback (most recent call last):
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 249, in apply
    sub_prof = optimizer.optimize(fgraph)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 89, in optimize
    ret = self.apply(fgraph, *args, **kwargs)
  File "/usr/local/lib/python3.8/site-packages/theano/tensor/opt.py", line 472, in apply
    fgraph.replace(
  File "/usr/local/lib/python3.8/site-packages/theano/gof/fg.py", line 528, in replace
    self.change_input(node, i, new_r, reason=reason)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/fg.py", line 440, in change_input
    self.__import_r__(new_r, reason=reason)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/fg.py", line 326, in __import_r__
    self.__import__(variable.owner, reason=reason)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/fg.py", line 396, in __import__
    self.execute_callbacks("on_import", node, reason)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/fg.py", line 608, in execute_callbacks
    fn(self, *args, **kwargs)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 606, in on_import
    self.process_node(fgraph, node)
  File "/usr/local/lib/python3.8/site-packages/theano/gof/opt.py", line 738, in process_node
    if inputs_match and node.op == candidate.op:
  File "/usr/local/lib/python3.8/site-packages/theano/gof/utils.py", line 211, in __eq__
    return type(self) == type(other) and tuple(
  File "/usr/local/lib/python3.8/site-packages/theano/scalar/basic.py", line 4437, in __eq__
    self.init_c_code()  # self._c_code and self.nodenames
  File "/usr/local/lib/python3.8/site-packages/theano/scalar/basic.py", line 4164, in init_c_code
    s = node.op.c_code(
  File "/usr/local/lib/python3.8/site-packages/theano/gof/op.py", line 364, in c_code
    raise MethodNotDefined("%s.c_code" % self.__class__.__name__)
theano.gof.utils.MethodNotDefined: I0e.c_code
================================================= short test summary info =================================================
FAILED pymc3/tests/test_distributions.py::TestMatchesScipy::test_rice - KeyError: Elemwise{Composite{i0e((i0 * i1))}}.0
==================================================== 1 failed in 9.58s ====================================================

Versions and main components

• Theano version: Theano-PyMC@master
• Theano config (python -c "import theano; print(theano.config)")

floatX (('float64', 'float32', 'float16')) 
    Doc:  Default floating-point precision for python casts.

Note: float16 support is experimental, use at your own risk.
    Value:  float64

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

pickle_test_value (<function BoolParam.<locals>.booltype at 0x114a380d0>) 
    Doc:  Dump test values while pickling model. If True, test values will be dumped with model.
    Value:  True

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

deterministic (('default', 'more')) 
    Doc:  If `more`, sometimes we will select some implementation that are more deterministic, but slower. In particular, on the GPU, we will avoid using AtomicAdd. Sometimes we will still use non-deterministic implementaion, e.g. when we do not have a GPU implementation that is deterministic. Also see the dnn.conv.algo* flags to cover more cases.
    Value:  default

device (cpu, 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:  cpu

init_gpu_device (, 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 0x114a38670>) 
    Doc:  Raise an error if we can't use the specified device
    Value:  False

conv.assert_shape (<function BoolParam.<locals>.booltype at 0x114a38820>) 
    Doc:  If True, AbstractConv* ops will verify that user-provided shapes match the runtime shapes (debugging option, may slow down compilation)
    Value:  False

print_global_stats (<function BoolParam.<locals>.booltype at 0x114a389d0>) 
    Doc:  Print some global statistics (time spent) at the end
    Value:  False

<theano.configdefaults.ContextsParam object at 0x114a32a60>
    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 0x114a38ca0>) 
    Doc:  Print active device at when the GPU device is initialized.
    Value:  True

<theano.configparser.ConfigParam object at 0x114a32b80>
    Doc:  This flag is deprecated and will be removed in next Theano release.
    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
                cudaDeviceScheduleBlockingSync. 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 0x114a3a040>) 
    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

cuda.root (<class 'str'>) 
    Doc:  Location of the cuda installation
    Value:  

cuda.include_path (<class 'str'>) 
    Doc:  Location of the cuda includes
    Value:  

<theano.configparser.ConfigParam object at 0x114a3c040>
    Doc:  This flag is deprecated; use dnn.conv.algo_fwd.
    Value:  True

<theano.configparser.ConfigParam object at 0x114a3c190>
    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 0x114a3c1f0>
    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', 'winograd_non_fused', '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', 'winograd_non_fused', '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', 'winograd_non_fused', 'fft_tiling', '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.base_path (<class 'str'>) 
    Doc:  Install location of cuDNN.
    Value:  

dnn.include_path (<class 'str'>) 
    Doc:  Location of the cudnn header
    Value:  

dnn.library_path (<class 'str'>) 
    Doc:  Location of the cudnn link library.
    Value:  

dnn.bin_path (<class 'str'>) 
    Doc:  Location of the cuDNN load library (on non-windows platforms, this is the same as dnn.library_path)
    Value:  

dnn.enabled (('auto', 'True', 'False', 'no_check')) 
    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 even if present. If no_check, assume present and the version between header and library match (so less compilation at context init)
    Value:  auto

magma.include_path (<class 'str'>) 
    Doc:  Location of the magma header
    Value:  

magma.library_path (<class 'str'>) 
    Doc:  Location of the magma library
    Value:  

magma.enabled (<function BoolParam.<locals>.booltype at 0x114a3ae50>) 
    Doc:   If True, use magma for matrix computation. If False, disable magma
    Value:  False

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

<theano.configparser.ConfigParam object at 0x114a3cac0>
    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/clang++

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 0x114a3ed30>) 
    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 (('o4', 'o3', 'o2', 'o1', 'unsafe', 'fast_run', 'fast_compile', 'merge', 'None')) 
    Doc:  Default optimizer. If not None, will use this optimizer with the Mode
    Value:  o4

optimizer_verbose (<function BoolParam.<locals>.booltype at 0x114a3ef70>) 
    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

nocleanup (<function BoolParam.<locals>.booltype at 0x114a4e1f0>) 
    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 0x114a4e550>) 
    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 0x114a4e700>) 
    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 0x114a4e8b0>) 
    Doc:  Use amd's amdlibm numerical library
    Value:  False

gpuelemwise.sync (<function BoolParam.<locals>.booltype at 0x114a4ea60>) 
    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 0x114a4ed30>) 
    Doc:  Allow unpickling of pickled GpuArrays as numpy.ndarrays.This is useful, if you want to open a GpuArray 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 (('0.9', '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', '0.10', '1.0', '1.0.1', '1.0.2', '1.0.3', '1.0.4', '1.0.5')) 
    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:  0.9

warn.argmax_pushdown_bug (<function BoolParam.<locals>.booltype at 0x114a523a0>) 
    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 0x114a52550>) 
    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 0x114a52700>) 
    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 0x114a528b0>) 
    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 0x114a52a60>) 
    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 0x114a52c10>) 
    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 0x114a52dc0>) 
    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 0x114a52f70>) 
    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 0x114a54160>) 
    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 0x114a54310>) 
    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 0x114a544c0>) 
    Doc:  Warn when using `tensor.round` with the default mode. Round changed its default from `half_away_from_zero` to `half_to_even` to have the same default as NumPy.
    Value:  False

warn.inc_subtensor1_opt (<function BoolParam.<locals>.booltype at 0x114a54670>) 
    Doc:  Warn if previous versions of Theano (before 0.10) could have given incorrect results when computing inc_subtensor(zeros[idx], x)[idx], when idx is an array of integers with duplicated values.
    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 0x114a548b0>) 
    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 0x114a54af0>) 
    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 0x114a54ca0>) 
    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 0x114a54ee0>) 
    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 0x114a57160>) 
    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 0x114a57310>) 
    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 0x114a575e0>) 
    Doc:  Default value for nan_is_error
    Value:  True

NanGuardMode.inf_is_error (<function BoolParam.<locals>.booltype at 0x114a57790>) 
    Doc:  Default value for inf_is_error
    Value:  True

NanGuardMode.big_is_error (<function BoolParam.<locals>.booltype at 0x114a57940>) 
    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 0x114a57ee0>) 
    Doc:  Run C implementations where possible
    Value:  True

DebugMode.check_py (<function BoolParam.<locals>.booltype at 0x114a5c0d0>) 
    Doc:  Run Python implementations where possible
    Value:  True

DebugMode.check_finite (<function BoolParam.<locals>.booltype at 0x114a5c280>) 
    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 0x114a5c550>) 
    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 0x114a5c940>) 
    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 0x114a5cf70>) 
    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 0x114a5f1f0>) 
    Doc:  
             Do a debugprint of the profiled functions
             
    Value:  False

profiling.ignore_first_call (<function BoolParam.<locals>.booltype at 0x114a5f3a0>) 
    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 0x114a5f700>) 
    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 0x114a5f8b0>) 
    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 0x114a5fa60>) 
    Doc:  If True, will print compilation warnings.
    Value:  False

cmodule.preload_cache (<function BoolParam.<locals>.booltype at 0x114a5fc10>) 
    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

cmodule.debug (<function BoolParam.<locals>.booltype at 0x114a5fe50>) 
    Doc:  If True, define a DEBUG macro (if not exists) for any compiled C code.
    Value:  False

blas.ldflags (<class 'str'>) 
    Doc:  lib[s] to include for [Fortran] level-3 blas implementation
    Value:  -lblas

blas.check_openmp (<function BoolParam.<locals>.booltype at 0x114a62280>) 
    Doc:  Check for openmp library conflict.
WARNING: Setting this to False leaves you open to wrong results in blas-related operations.
    Value:  True

metaopt.verbose (<class 'int'>) 
    Doc:  0 for silent, 1 for only warnings, 2 for full output withtimings and selected implementation
    Value:  0

metaopt.optimizer_excluding (<class 'str'>) 
    Doc:  exclude optimizers with these tags. Separate tags with ':'.
    Value:  

metaopt.optimizer_including (<class 'str'>) 
    Doc:  include optimizers with these tags. Separate tags with ':'.
    Value:  

profile (<function BoolParam.<locals>.booltype at 0x114a625e0>) 
    Doc:  If VM should collect profile information
    Value:  False

profile_optimizer (<function BoolParam.<locals>.booltype at 0x114a62790>) 
    Doc:  If VM should collect optimizer profile information
    Value:  False

profile_memory (<function BoolParam.<locals>.booltype at 0x114a62940>) 
    Doc:  If VM should collect memory profile information and print it
    Value:  False

<theano.configparser.ConfigParam object at 0x114a61cd0>
    Doc:  Useful only for the vm linkers. When lazy is None, auto detect if lazy evaluation is needed and use the appropriate 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 0x114a62b80>) 
    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 0x114a62ee0>) 
    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 0x114a62f70>) 
    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 0x114a6b1f0>) 
    Doc:  Allow/disallow gc inside of Scan (default: False)
    Value:  False

scan.allow_output_prealloc (<function BoolParam.<locals>.booltype at 0x114a6b3a0>) 
    Doc:  Allow/disallow memory preallocation for outputs inside of scan (default: True)
    Value:  True

scan.debug (<function BoolParam.<locals>.booltype at 0x114a6b550>) 
    Doc:  If True, enable extra verbose output related to scan
    Value:  False

compile.wait (<class 'int'>) 
    Doc:  Time to wait before retrying to acquire the compile lock.
    Value:  5

cycle_detection (('regular', 'fast')) 
    Doc:  If cycle_detection is set to regular, most inplaces are allowed,but it is slower. If cycle_detection is set to faster, less inplacesare allowed, but it makes the compilation faster.The interaction of which one give the lower peak memory usage iscomplicated and not predictable, so if you are close to the peakmemory usage, triyng both could give you a small gain.
    Value:  regular

check_stack_trace (('off', 'log', 'warn', 'raise')) 
    Doc:  A flag for checking the stack trace during the optimization process. default (off): does not check the stack trace of any optimization log: inserts a dummy stack trace that identifies the optimizationthat inserted the variable that had an empty stack trace.warn: prints a warning if a stack trace is missing and also a dummystack trace is inserted that indicates which optimization insertedthe variable that had an empty stack trace.raise: raises an exception if a stack trace is missing
    Value:  off

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 0x114a69e80>
    Doc:  platform-independent root directory for compiled modules
    Value:  /Users/user/.theano

<theano.configparser.ConfigParam object at 0x114a73be0>
    Doc:  platform-dependent cache directory for compiled modules
    Value:  /Users/user/.theano/compiledir_macOS-10.15.7-x86_64-i386-64bit-i386-3.8.5-64

<theano.configparser.ConfigParam object at 0x114a803a0>
    Doc:  Directory to cache pre-compiled kernels for the gpuarray backend.
    Value:  /Users/user/.theano/compiledir_macOS-10.15.7-x86_64-i386-64bit-i386-3.8.5-64/gpuarray_kernels

ctc.root (<class 'str'>) 
    Doc:  Directory which contains the root of Baidu CTC library. It is assumed     that the compiled library is either inside the build, lib or lib64     subdirectory, and the header inside the include directory.
    Value:  

• Python version: 3.8.5
• Operating system: Macos
• How did you install Theano: (conda/pip) pip

[brandonwillard]

This is an interesting one. It looks like the problem was introduced between 1.0.9 and 1.0.10.

My initial guess is that there is an optimization that's forcing this operator into a situation in which an Op.c_code implementation must be present and that some refactoring caused the relevant optimizations to be registered in a slightly different order.