Failure to link with MLK_RT under Windows

[maresb]

Description of your problem or feature request

There is a report on Discourse about an issue from a Windows user regarding a linking problem. @lucianopaz believes the issue is related to #947:

@opherdonchin , if it’s anything like the issue that I mentioned, you won’t be able to fix it using ldflags. Those will get a -l prepend and won’t link properly. The PR where I had fixed the old issue did some things to link to the full path of the dynamic link library, but it had to do so in aesara itself. I think that you’ll have to open an issue in aesara to get this fixed. I can help out with this after Monday

Versions and main components

• Aesara version: 2.8.2
• Aesara config (python -c "import aesara; print(aesara.config)")
• Python version: 3.10.6
• Operating system: Windows 10
• How did you install Aesara: mamba

[opherdonchin]

@maresb asked me to post the aesara config here in hopes that it will provide insight. Let me know if any other information will be helpful.

Click for output of:

python -c "import aesara; print(aesara.config)"

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

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

warn_float64 ({'pdb', 'raise', 'ignore', 'warn'})
Doc: Do an action when a tensor variable with float64 dtype is created.
Value: ignore

pickle_test_value (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173BDCE8250>>)
Doc: Dump test values while pickling model. If True, test values will be dumped with model.
Value: True

cast_policy ({'numpy+floatX', 'custom'})
Doc: Rules for implicit type casting
Value: custom

deterministic ({'default', 'more'})
Doc: If more, sometimes we will select some implementation that are more deterministic, but slower. Also see the dnn.conv.algo* flags to cover more cases.
Value: default

device (cpu)
Doc: Default device for computations. only cpu is supported for now
Value: cpu

force_device (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C141A8C0>>)
Doc: Raise an error if we can't use the specified device
Value: False

conv__assert_shape (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C141AE60>>)
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 (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C141AEF0>>)
Doc: Print some global statistics (time spent) at the end
Value: False

assert_no_cpu_op ({'pdb', 'raise', 'ignore', 'warn'})
Doc: Raise an error/warning if there is a CPU op in the computational graph.
Value: ignore

unpickle_function (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5060>>)
Doc: Replace unpickled Aesara functions with None. This is useful to unpickle old graphs that pickled them when it shouldn't
Value: True

<aesara.configparser.ConfigParam object at 0x00000173C15D4E80>
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: "C:\miniconda3\envs\pymc_env_stricter\Library\mingw-w64\bin\g++.exe"

linker ({'cvm_nogc', 'vm', 'py', 'vm_nogc', 'c', 'c|py', 'c|py_nogc', 'cvm'})
Doc: Default linker used if the aesara flags mode is Mode
Value: cvm

allow_gc (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5210>>)
Doc: Do we default to delete intermediate results during Aesara 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_compile', 'merge', 'fast_run', 'o2', 'o3', 'o4', 'None', 'unsafe', 'o1'})
Doc: Default optimizer. If not None, will use this optimizer with the Mode
Value: o4

optimizer_verbose (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D50F0>>)
Doc: If True, we print all optimization being applied
Value: False

on_opt_error ({'pdb', 'raise', 'ignore', 'warn'})
Doc: What to do when an optimization crashes: warn and skip it, raise the exception, or fall into the pdb debugger.
Value: warn

nocleanup (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5000>>)
Doc: Suppress the deletion of code files that did not compile cleanly
Value: False

on_unused_input ({'raise', 'ignore', 'warn'})
Doc: What to do if a variable in the 'inputs' list of aesara.function() is not used in the graph.
Value: raise

gcc__cxxflags (<class 'str'>)
Doc: Extra compiler flags for gcc
Value:

cmodule__warn_no_version (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D50C0>>)
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 (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5150>>)
Doc: If True, will remove the -O* parameter passed to g++.This is useful to debug in gdb modules compiled by Aesara.The parameter -g is passed by default to g++
Value: False

cmodule__compilation_warning (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5270>>)
Doc: If True, will print compilation warnings.
Value: False

cmodule__preload_cache (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5240>>)
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 Aesara won't reuse a compile c module.
Value: 2073600

cmodule__debug (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5330>>)
Doc: If True, define a DEBUG macro (if not exists) for any compiled C code.
Value: False

compile__wait (<class 'int'>)
Doc: Time to wait before retrying to acquire 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

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:

tensor__cmp_sloppy (<class 'int'>)
Doc: Relax aesara.tensor.math._allclose (0) not at all, (1) a bit, (2) more
Value: 0

tensor__local_elemwise_fusion (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D54E0>>)
Doc: Enable or not in fast_run mode(fast_run optimization) the elemwise fusion optimization
Value: True

lib__amblibm (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D55A0>>)
Doc: Use amd's amdlibm numerical library
Value: False

tensor__insert_inplace_optimizer_validate_nb (<class 'int'>)
Doc: -1: auto, if graph have less then 500 nodes 1, else 10
Value: -1

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 Aesara internal stack trace.
Value: 0

experimental__local_alloc_elemwise (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5720>>)
Doc: DEPRECATED: If True, enable the experimental optimization local_alloc_elemwise. Generates error if not True. Use optimizer_excluding=local_alloc_elemwise to disable.
Value: True

experimental__local_alloc_elemwise_assert (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5750>>)
Doc: When the local_alloc_elemwise is applied, add an assert to highlight shape errors.
Value: True

warn__ignore_bug_before ({'0.8.1', '0.8', '0.6', '1.0.4', '0.9', 'None', '1.0.5', '1.0.3', '0.10', '0.3', '0.4', '1.0.2', 'all', '0.7', '1.0', '1.0.1', '0.4.1', '0.8.2', '0.5'})
Doc: If 'None', we warn about all Aesara bugs found by default. If 'all', we don't warn about Aesara bugs found by default. If a version, we print only the warnings relative to Aesara bugs found after that version. Warning for specific bugs can be configured with specific [warn] flags.
Value: 0.9

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

print_test_value (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D58A0>>)
Doc: If 'True', the eval of an Aesara 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 ({'off', 'raise', 'pdb', 'ignore', 'warn'})
Doc: If 'True', Aesara 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

compute_test_value_opt ({'off', 'raise', 'pdb', 'ignore', 'warn'})
Doc: For debugging Aesara optimization only. Same as compute_test_value, but is used during Aesara optimization
Value: off

check_input (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5900>>)
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

NanGuardMode__nan_is_error (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5930>>)
Doc: Default value for nan_is_error
Value: True

NanGuardMode__inf_is_error (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5990>>)
Doc: Default value for inf_is_error
Value: True

NanGuardMode__big_is_error (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5A20>>)
Doc: Default value for big_is_error
Value: True

NanGuardMode__action ({'pdb', 'raise', 'warn'})
Doc: What NanGuardMode does when it finds a problem
Value: raise

DebugMode__patience (<class 'int'>)
Doc: Optimize graph this many times to detect inconsistency
Value: 10

DebugMode__check_c (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5AB0>>)
Doc: Run C implementations where possible
Value: True

DebugMode__check_py (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5B40>>)
Doc: Run Python implementations where possible
Value: True

DebugMode__check_finite (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5B10>>)
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 (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5BA0>>)
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 (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5C30>>)
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 (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5D80>>)
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 (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5DE0>>)
Doc: Do a debugprint of the profiled functions
Value: False

profiling__ignore_first_call (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5E10>>)
Doc: Do we ignore the first call of an Aesara function.
Value: False

on_shape_error ({'raise', 'warn'})
Doc: warn: print a warning and use the default value. raise: raise an error
Value: warn

openmp (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D5E70>>)
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 Aesara configuration file ~/.aesararc or with the environment variable AESARA_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 Aesara 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

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:

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 EquilibriumGraphRewriter.
Value: 8.0

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 ({'raise', 'warn', 'log', 'off'})
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

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 (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D6140>>)
Doc: If VM should collect profile information
Value: False

profile_optimizer (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D61A0>>)
Doc: If VM should collect optimizer profile information
Value: False

profile_memory (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D61D0>>)
Doc: If VM should collect memory profile information and print it
Value: False

<aesara.configparser.ConfigParam object at 0x00000173C15D6200>
Doc: Useful only for the VM Linkers. When lazy is None, auto detect if lazy evaluation is needed and use the appropriate version. If the C loop isn't being used and lazy is True, use the Stack VM; otherwise, use the Loop VM.
Value: None

unittests__rseed (<class 'str'>)
Doc: Seed to use for randomized unit tests. Special value 'random' means using a seed of None.
Value: 666

warn__round (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D62C0>>)
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

numba__vectorize_target ({'cuda', 'parallel', 'cpu'})
Doc: Default target for numba.vectorize.
Value: cpu

numba__fastmath (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D63B0>>)
Doc: If True, use Numba's fastmath mode.
Value: True

numba__cache (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C15D6440>>)
Doc: If True, use Numba's file based caching.
Value: True

compiledir_format (<class 'str'>)
Doc: Format string for platform-dependent compiled module subdirectory
(relative to base_compiledir). Available keys: aesara_version, device,
gxx_version, hostname, numpy_version, platform, processor,
python_bitwidth, python_int_bitwidth, python_version, short_platform.
Defaults to compiledir_%(short_platform)s-%(processor)s-
%(python_version)s-%(python_bitwidth)s.
Value: compiledir_%(short_platform)s-%(processor)s-%(python_version)s-%(python_bitwidth)s

<aesara.configparser.ConfigParam object at 0x00000173C15D6500>
Doc: platform-independent root directory for compiled modules
Value: C:\Users\Opher local\AppData\Local\Aesara

<aesara.configparser.ConfigParam object at 0x00000173C15D6710>
Doc: platform-dependent cache directory for compiled modules
Value: C:\Users\Opher local\AppData\Local\Aesara\compiledir_Windows-10-10.0.19043-SP0-Intel64_Family_6_Model_142_Stepping_12_GenuineIntel-3.10.6-64

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

blas__check_openmp (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C1829B10>>)
Doc: Check for openmp library conflict.
WARNING: Setting this to False leaves you open to wrong results in blas-related operations.
Value: True

scan__allow_gc (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C3FD42B0>>)
Doc: Allow/disallow gc inside of Scan (default: False)
Value: False

scan__allow_output_prealloc (<bound method BoolParam._apply of <aesara.configparser.BoolParam object at 0x00000173C403DC00>>)
Doc: Allow/disallow memory preallocation for outputs inside of scan (default: True)
Value: True

</details>

[maresb]

Thanks @opherdonchin for the extra info! I see that @brandonwillard has added the MWE needed tag. Would it be possible for you to strip your current model to the bare minimum required to reproduce the error, and then post it here? Thanks!

[brandonwillard]

Thanks @opherdonchin for the extra info! I see that @brandonwillard has added the MWE needed tag. Would it be possible for you to strip your current model to the bare minimum required to reproduce the error, and then post it here? Thanks!

We may also need the commands used to build the (virtual) environment in which this issue occurs from scratch.

Also, don't use PyMC in these reproductions.

[opherdonchin]

Hi @brandonwillard ,

I don't know enough about aesara to build an aesara model without pymc. Sorry about that.

I used a minimal environment for testing:

`mamba create --name pymc_env_aesara --channel conda-forge --strict-channel-priority pymc`

expand for output

███████████████/  /██/  /██/  /██/  /████████████████████████
              /  / \   / \   / \   / \  \____
             /  /   \_/   \_/   \_/   \    o \__,
            / _/                       \_____/  `
            |/
        ███╗   ███╗ █████╗ ███╗   ███╗██████╗  █████╗
        ████╗ ████║██╔══██╗████╗ ████║██╔══██╗██╔══██╗
        ██╔████╔██║███████║██╔████╔██║██████╔╝███████║
        ██║╚██╔╝██║██╔══██║██║╚██╔╝██║██╔══██╗██╔══██║
        ██║ ╚═╝ ██║██║  ██║██║ ╚═╝ ██║██████╔╝██║  ██║
        ╚═╝     ╚═╝╚═╝  ╚═╝╚═╝     ╚═╝╚═════╝ ╚═╝  ╚═╝

        mamba (0.24.0) supported by @QuantStack

        GitHub:  https://github.com/mamba-org/mamba
        Twitter: https://twitter.com/QuantStack

█████████████████████████████████████████████████████████████


Looking for: ['pymc']

pkgs/main/noarch                                   816.3kB @ 705.5kB/s  1.2s
pkgs/r/win-64                                      742.8kB @ 599.3kB/s  1.3s
pkgs/msys2/noarch                                  111.0 B @  82.0 B/s  0.2s
pkgs/msys2/win-64                                   39.8kB @  23.1kB/s  0.4s
pkgs/r/noarch                                        1.3MB @ 501.3kB/s  1.5s
pkgs/main/win-64                                     4.3MB @   1.4MB/s  3.3s
conda-forge/noarch                                   9.4MB @   1.6MB/s  6.7s
conda-forge/win-64                                  16.5MB @   1.9MB/s  9.7s
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\msys2-conda-epoch-20160418-1' has invalid size
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\msys2-conda-epoch-20160418-1' has invalid SHA-256 checksum
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-gmp-6.1.0-2' has invalid size
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-gmp-6.1.0-2' has invalid SHA-256 checksum
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-windows-default-manifest-6.4-3' has invalid size
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-windows-default-manifest-6.4-3' has invalid SHA-256 checksum
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-isl-0.16.1-2' has invalid size
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-isl-0.16.1-2' has invalid SHA-256 checksum
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-libiconv-1.14-6' has invalid size
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-libiconv-1.14-6' has invalid SHA-256 checksum
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-make-4.1.2351.a80a8b8-2' has invalid size
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-make-4.1.2351.a80a8b8-2' has invalid SHA-256 checksum
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-libwinpthread-git-5.0.0.4634.697f757-2' has invalid size
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-libwinpthread-git-5.0.0.4634.697f757-2' has invalid SHA-256 checksum
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-libmangle-git-5.0.0.4509.2e5a9a2-2' has invalid size
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-libmangle-git-5.0.0.4509.2e5a9a2-2' has invalid SHA-256 checksum
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-headers-git-5.0.0.4636.c0ad18a-2' has invalid size
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-headers-git-5.0.0.4636.c0ad18a-2' has invalid SHA-256 checksum
warning  libmamba Extracted package cache 'C:\miniconda3\pkgs\m2w64-mpfr-3.1.4-4' has invalid size
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Transaction

  Prefix: C:\miniconda3\envs\pymc_env_aesara

  Updating specs:

   - pymc


  Package                                      Version  Build                    Channel                  Size
----------------------------------------------------------------------------------------------------------------
  Install:
----------------------------------------------------------------------------------------------------------------

  + aeppl                                       0.0.36  pyhd8ed1ab_0             conda-forge/noarch        5kB
  + aeppl-base                                  0.0.36  pyhd8ed1ab_0             conda-forge/noarch       44kB
  + aesara                                       2.8.6  py310hfa0c5ed_0          conda-forge/win-64        8kB
  + aesara-base                                  2.8.6  py310h5588dad_0          conda-forge/win-64        2MB
  + arviz                                       0.12.1  pyhd8ed1ab_1             conda-forge/noarch     Cached
  + blas                                         2.116  mkl                      conda-forge/win-64     Cached
  + blas-devel                                   3.9.0  16_win64_mkl             conda-forge/win-64     Cached
  + brotli                                       1.0.9  h8ffe710_7               conda-forge/win-64     Cached
  + brotli-bin                                   1.0.9  h8ffe710_7               conda-forge/win-64     Cached
  + bzip2                                        1.0.8  h8ffe710_4               conda-forge/win-64     Cached
  + ca-certificates                          2022.9.24  h5b45459_0               conda-forge/win-64     Cached
  + cachetools                                   5.2.0  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + certifi                                  2022.9.24  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + cftime                                       1.6.2  py310h9b08ddd_0          conda-forge/win-64     Cached
  + cloudpickle                                  2.2.0  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + cons                                         0.4.5  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + contourpy                                    1.0.5  py310h232114e_0          conda-forge/win-64     Cached
  + curl                                        7.83.1  h789b8ee_0               conda-forge/win-64     Cached
  + cycler                                      0.11.0  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + etuples                                      0.3.8  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + fastprogress                                 1.0.3  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + filelock                                     3.8.0  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + fonttools                                   4.37.4  py310h8d17308_0          conda-forge/win-64     Cached
  + freetype                                    2.12.1  h546665d_0               conda-forge/win-64     Cached
  + hdf4                                        4.2.15  h0e5069d_4               conda-forge/win-64     Cached
  + hdf5                                        1.12.2  nompi_h57737ce_100       conda-forge/win-64     Cached
  + intel-openmp                              2022.1.0  h57928b3_3787            conda-forge/win-64     Cached
  + jpeg                                            9e  h8ffe710_2               conda-forge/win-64     Cached
  + kiwisolver                                   1.4.4  py310h476a331_0          conda-forge/win-64     Cached
  + krb5                                        1.19.3  hc8ab02b_0               conda-forge/win-64     Cached
  + lcms2                                         2.12  h2a16943_0               conda-forge/win-64     Cached
  + lerc                                         4.0.0  h63175ca_0               conda-forge/win-64     Cached
  + libblas                                      3.9.0  16_win64_mkl             conda-forge/win-64     Cached
  + libbrotlicommon                              1.0.9  h8ffe710_7               conda-forge/win-64     Cached
  + libbrotlidec                                 1.0.9  h8ffe710_7               conda-forge/win-64     Cached
  + libbrotlienc                                 1.0.9  h8ffe710_7               conda-forge/win-64     Cached
  + libcblas                                     3.9.0  16_win64_mkl             conda-forge/win-64     Cached
  + libcurl                                     7.83.1  h789b8ee_0               conda-forge/win-64     Cached
  + libdeflate                                    1.14  hcfcfb64_0               conda-forge/win-64     Cached
  + libffi                                       3.4.2  h8ffe710_5               conda-forge/win-64     Cached
  + liblapack                                    3.9.0  16_win64_mkl             conda-forge/win-64     Cached
  + liblapacke                                   3.9.0  16_win64_mkl             conda-forge/win-64     Cached
  + libnetcdf                                    4.8.1  nompi_h85765be_104       conda-forge/win-64     Cached
  + libpng                                      1.6.38  h19919ed_0               conda-forge/win-64     Cached
  + libpython                                      2.2  py310h5588dad_1          conda-forge/win-64     Cached
  + libsqlite                                   3.39.3  hcfcfb64_0               conda-forge/win-64     Cached
  + libssh2                                     1.10.0  h9a1e1f7_3               conda-forge/win-64     Cached
  + libtiff                                      4.4.0  h8e97e67_4               conda-forge/win-64     Cached
  + libwebp-base                                 1.2.4  h8ffe710_0               conda-forge/win-64     Cached
  + libxcb                                        1.13  hcd874cb_1004            conda-forge/win-64     Cached
  + libzip                                       1.9.2  h519de47_1               conda-forge/win-64     Cached
  + libzlib                                     1.2.12  hcfcfb64_3               conda-forge/win-64     Cached
  + logical-unification                          0.4.5  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + m2w64-binutils                              2.25.1  5                        conda-forge/win-64     Cached
  + m2w64-bzip2                                  1.0.6  6                        conda-forge/win-64     Cached
  + m2w64-crt-git                   5.0.0.4636.2595836  2                        conda-forge/win-64     Cached
  + m2w64-gcc                                    5.3.0  6                        conda-forge/win-64     Cached
  + m2w64-gcc-ada                                5.3.0  6                        conda-forge/win-64     Cached
  + m2w64-gcc-fortran                            5.3.0  6                        conda-forge/win-64     Cached
  + m2w64-gcc-libgfortran                        5.3.0  6                        conda-forge/win-64     Cached
  + m2w64-gcc-libs                               5.3.0  7                        conda-forge/win-64     Cached
  + m2w64-gcc-libs-core                          5.3.0  7                        conda-forge/win-64     Cached
  + m2w64-gcc-objc                               5.3.0  6                        conda-forge/win-64     Cached
  + m2w64-gmp                                    6.1.0  2                        conda-forge/win-64     Cached
  + m2w64-headers-git               5.0.0.4636.c0ad18a  2                        conda-forge/win-64     Cached
  + m2w64-isl                                   0.16.1  2                        conda-forge/win-64     Cached
  + m2w64-libiconv                                1.14  6                        conda-forge/win-64     Cached
  + m2w64-libmangle-git             5.0.0.4509.2e5a9a2  2                        conda-forge/win-64     Cached
  + m2w64-libwinpthread-git         5.0.0.4634.697f757  2                        conda-forge/win-64     Cached
  + m2w64-make                        4.1.2351.a80a8b8  2                        conda-forge/win-64     Cached
  + m2w64-mpc                                    1.0.3  3                        conda-forge/win-64     Cached
  + m2w64-mpfr                                   3.1.4  4                        conda-forge/win-64     Cached
  + m2w64-pkg-config                            0.29.1  2                        conda-forge/win-64     Cached
  + m2w64-toolchain                              5.3.0  7                        conda-forge/win-64     Cached
  + m2w64-toolchain_win-64                       2.4.0  0                        conda-forge/win-64     Cached
  + m2w64-tools-git                 5.0.0.4592.90b8472  2                        conda-forge/win-64     Cached
  + m2w64-windows-default-manifest                 6.4  3                        conda-forge/win-64     Cached
  + m2w64-winpthreads-git           5.0.0.4634.697f757  2                        conda-forge/win-64     Cached
  + m2w64-zlib                                   1.2.8  10                       conda-forge/win-64     Cached
  + matplotlib-base                              3.6.0  py310h51140c5_0          conda-forge/win-64     Cached
  + minikanren                                   1.0.3  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + mkl                                       2022.1.0  h6a75c08_874             conda-forge/win-64     Cached
  + mkl-devel                                 2022.1.0  h57928b3_875             conda-forge/win-64     Cached
  + mkl-include                               2022.1.0  h6a75c08_874             conda-forge/win-64     Cached
  + mkl-service                                  2.4.0  py310h3d5ec83_0          conda-forge/win-64     Cached
  + msys2-conda-epoch                         20160418  1                        conda-forge/win-64     Cached
  + multipledispatch                             0.6.0  py_0                     conda-forge/noarch     Cached
  + munkres                                      1.1.4  pyh9f0ad1d_0             conda-forge/noarch     Cached
  + netcdf4                                      1.6.1  nompi_py310h459bb5f_100  conda-forge/win-64     Cached
  + numpy                                       1.23.3  py310h4a8f9c9_0          conda-forge/win-64     Cached
  + openjpeg                                     2.5.0  hc9384bd_1               conda-forge/win-64     Cached
  + openssl                                      3.0.5  hcfcfb64_2               conda-forge/win-64     Cached
  + packaging                                     21.3  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + pandas                                       1.5.0  py310h1c4a608_0          conda-forge/win-64     Cached
  + pillow                                       9.2.0  py310h52929f7_2          conda-forge/win-64     Cached
  + pip                                         22.2.2  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + pthread-stubs                                  0.4  hcd874cb_1001            conda-forge/win-64     Cached
  + pymc                                         4.2.1  hd8ed1ab_0               conda-forge/noarch       10kB
  + pymc-base                                    4.2.1  pyhd8ed1ab_0             conda-forge/noarch      408kB
  + pyparsing                                    3.0.9  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + python                                      3.10.6  hcf16a7b_0_cpython       conda-forge/win-64     Cached
  + python-dateutil                              2.8.2  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + python_abi                                    3.10  2_cp310                  conda-forge/win-64     Cached
  + pytz                                      2022.2.1  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + scipy                                        1.9.1  py310h578b7cb_0          conda-forge/win-64     Cached
  + setuptools                                  65.4.0  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + six                                         1.16.0  pyh6c4a22f_0             conda-forge/noarch     Cached
  + tbb                                       2021.6.0  h91493d7_0               conda-forge/win-64     Cached
  + tk                                          8.6.12  h8ffe710_0               conda-forge/win-64     Cached
  + toolz                                       0.12.0  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + typing-extensions                            4.3.0  hd8ed1ab_0               conda-forge/noarch     Cached
  + typing_extensions                            4.3.0  pyha770c72_0             conda-forge/noarch     Cached
  + tzdata                                       2022d  h191b570_0               conda-forge/noarch     Cached
  + ucrt                                  10.0.20348.0  h57928b3_0               conda-forge/win-64     Cached
  + unicodedata2                                14.0.0  py310he2412df_1          conda-forge/win-64     Cached
  + vc                                            14.2  hb210afc_7               conda-forge/win-64     Cached
  + vs2015_runtime                         14.29.30139  h890b9b1_7               conda-forge/win-64     Cached
  + wheel                                       0.37.1  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + xarray                                    2022.9.0  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + xarray-einstats                              0.3.0  pyhd8ed1ab_0             conda-forge/noarch     Cached
  + xorg-libxau                                  1.0.9  hcd874cb_0               conda-forge/win-64     Cached
  + xorg-libxdmcp                                1.1.3  hcd874cb_0               conda-forge/win-64     Cached
  + xz                                           5.2.6  h8d14728_0               conda-forge/win-64     Cached
  + zstd                                         1.5.2  h7755175_4               conda-forge/win-64     Cached

  Summary:

  Install: 124 packages

  Total download: 3MB

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

Confirm changes: [Y/n] Y
aeppl-base                                          44.4kB @  97.3kB/s  0.5s
aesara                                               7.6kB @  13.8kB/s  0.6s
aeppl                                                5.1kB @   9.3kB/s  0.5s
pymc                                                 9.8kB @  14.7kB/s  0.2s
pymc-base                                          408.1kB @ 455.2kB/s  0.9s
aesara-base                                          2.1MB @ 900.8kB/s  2.3s
Preparing transaction: done
Verifying transaction: done
Executing transaction: done

To activate this environment, use

     $ mamba activate pymc_env_aesara

To deactivate an active environment, use

     $ mamba deactivate

In response to @maresb request for the miminal model, this post includes the full minimal model (see below). In producing it, it seems to me that the key lines in the model may be:

    beta = pm.Normal('beta', mu=0, sigma=1.5, dims=['process', 'measure'])
    mu_y = pm.Deterministic('mu_y', pm.math.dot(x,beta), dims=['subject', 'measure'])

Because if these lines are replaced by the following:

    beta = pm.Normal('beta', mu=0, sigma=1.5, dims=['measure'])
    mu_y = pm.Deterministic('mu_y', beta, dims=['subject', 'measure'])

This error goes away (and is replaced with a different one).

Here is the full model:

Expand for the minimal model that generates the error.

import numpy as np
import pandas as pd
import pymc as pm


def latent_variable_model(y,x,P):
  s_idx, subject_list = pd.factorize(y.index)
  m_idx, measure_list = pd.factorize(y.columns)

  coords = {'subject': subject_list, 'measure': measure_list, 'process': range(P)}
  with pm.Model(coords=coords) as model:
    # Minimal model that generates the missing mkl_rt error
    beta = pm.Normal('beta', mu=0, sigma=1.5, dims=['process', 'measure'])
    mu_y = pm.Deterministic('mu_y', pm.math.dot(x,beta), dims=['subject', 'measure'])
    # Even more minimal model that does not generate the mkl_rt error. 
    # This model generates a pymc error that may be easy to fix.
    # beta = pm.Normal('beta', mu=0, sigma=1.5, dims=['measure'])
    # mu_y = pm.Deterministic('mu_y', beta, dims=['subject', 'measure'])

    obs_y = pm.Normal('obs_y', mu=mu_y, sigma=0.1, observed=y, dims=['subject', 'measure'])
  return model

y = pd.DataFrame(np.random.normal(loc=0.8, scale=0.3, size=(420,6)))
x = np.random.normal(loc=0.5, scale=0.1, size=(420,2))

model = latent_variable_model(y, x, 2)

with model:
  fit = pm.sample()

Expand for the output:

PS C:\Opher\GitHub\bsf_donchin_jordan_2022> conda activate C:\miniconda3\envs\pymc_env_aesara
PS C:\Opher\GitHub\bsf_donchin_jordan_2022> & C:/miniconda3/envs/pymc_env_aesara/python.exe c:/Opher/GitHub/bsf_donchin_jordan_2022/mkl_rt_test_stripped.py

You can find the C code in this temporary file: C:\Users\OPHERL~1\AppData\Local\Temp\aesara_compilation_error_xgfvafb_
library mkl_rt is not found.
Traceback (most recent call last):
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\vm.py", line 1246, in make_all       
    node.op.make_thunk(node, storage_map, compute_map, [], impl=impl)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\op.py", line 131, in make_thunk    
    return self.make_c_thunk(node, storage_map, compute_map, no_recycling)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\op.py", line 96, in make_c_thunk   
    outputs = cl.make_thunk(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\basic.py", line 1202, in make_thunk
    cthunk, module, in_storage, out_storage, error_storage = self.__compile__(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\basic.py", line 1122, in __compile__
    thunk, module = self.cthunk_factory(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\basic.py", line 1647, in cthunk_factory
    module = cache.module_from_key(key=key, lnk=self)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\cmodule.py", line 1229, in module_from_key
    module = lnk.compile_cmodule(location)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\basic.py", line 1546, in compile_cmodule
    module = c_compiler.compile_str(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\cmodule.py", line 2640, in compile_str
    raise CompileError(
aesara.link.c.exceptions.CompileError: Compilation failed (return status=1):
"C:\miniconda3\envs\pymc_env_strict\Library\mingw-w64\bin\g++.exe" -shared -g -O3 -fno-math-errno -Wno-unused-label -Wno-unused-variable -Wno-write-strings -Wno-c++11-narrowing -fno-exceptions -fno-unwind-tables -fno-asynchronous-unwind-tables -march=broadwell -mmmx -mno-3dnow -msse -msse2 -msse3 -mssse3 -mno-sse4a -mcx16 -msahf -mmovbe -maes -mno-sha -mpclmul -mpopcnt -mabm -mno-lwp -mfma -mno-fma4 -mno-xop -mbmi -mbmi2 -mno-tbm -mavx -mavx2 -msse4.2 -msse4.1 -mlzcnt -mno-rtm -mno-hle -mrdrnd -mf16c -mfsgsbase -mrdseed -mprfchw -madx -mfxsr -mxsave -mxsaveopt -mno-avx512f -mno-avx512er -mno-avx512cd -mno-avx512pf -mno-prefetchwt1 -mclflushopt -mxsavec -mxsaves -mno-avx512dq -mno-avx512bw -mno-avx512vl -mno-avx512ifma -mno-avx512vbmi -mno-clwb -mno-pcommit -mno-mwaitx --param l1-cache-size=32 --param l1-cache-line-size=64 --param l2-cache-size=8192 -mtune=generic -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -m64 -DMS_WIN64 -I"C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\numpy\core\include" -I"C:\miniconda3\envs\pymc_env_aesara\include" -I"C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\c_code" -L"C:\miniconda3\envs\pymc_env_aesara\libs" -L"C:\miniconda3\envs\pymc_env_aesara" -o "C:\Users\Opher local\AppData\Local\Aesara\compiledir_Windows-10-10.0.19043-SP0-Intel64_Family_6_Model_142_Stepping_12_GenuineIntel-3.10.6-64\tmp78frcsc_\mebd8dae10522ca0870e1a82f1ea908002d7232440c31ecf6eadb09903ee4931b.pyd" "C:\Users\Opher local\AppData\Local\Aesara\compiledir_Windows-10-10.0.19043-SP0-Intel64_Family_6_Model_142_Stepping_12_GenuineIntel-3.10.6-64\tmp78frcsc_\mod.cpp" -lmkl_rt "C:\miniconda3\envs\pymc_env_aesara\python310.dll"
C:/miniconda3/envs/pymc_env_strict/Library/mingw-w64/bin/../lib/gcc/x86_64-w64-mingw32/5.3.0/../../../../x86_64-w64-mingw32/bin/ld.exe: cannot find -lmkl_rt
collect2.exe: error: ld returned 1 exit status


During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "c:\Opher\GitHub\bsf_donchin_jordan_2022\mkl_rt_test_stripped.py", line 29, in <module>
    fit = pm.sample()
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\sampling.py", line 530, in sample
    step = assign_step_methods(model, step, methods=pm.STEP_METHODS, step_kwargs=kwargs)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\sampling.py", line 228, in assign_step_methods
    return instantiate_steppers(model, steps, selected_steps, step_kwargs)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\sampling.py", line 146, in instantiate_steppers
    step = step_class(vars=vars, model=model, **args)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\step_methods\hmc\nuts.py", line 178, in __init__
    super().__init__(vars, **kwargs)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\step_methods\hmc\base_hmc.py", line 95, in __init__
    super().__init__(vars, blocked=blocked, model=self._model, dtype=dtype, **aesara_kwargs)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\step_methods\arraystep.py", line 276, in __init__
    func = model.logp_dlogp_function(vars, dtype=dtype, **aesara_kwargs)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\model.py", line 642, in logp_dlogp_function
    return ValueGradFunction(costs, grad_vars, extra_vars_and_values, **kwargs)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\model.py", line 382, in __init__
    self._aesara_function = compile_pymc(inputs, outputs, givens=givens, **kwargs)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\aesaraf.py", line 970, in compile_pymc
    aesara_function = aesara.function(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\compile\function\__init__.py", line 317, in function
    fn = pfunc(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\compile\function\pfunc.py", line 371, in pfunc
    return orig_function(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\compile\function\types.py", line 1759, in orig_function
    fn = m.create(defaults)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\compile\function\types.py", line 1652, in create
    _fn, _i, _o = self.linker.make_thunk(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\basic.py", line 254, in make_thunk
    return self.make_all(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\vm.py", line 1255, in make_all
    raise_with_op(fgraph, node)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\utils.py", line 534, in raise_with_op
    raise exc_value.with_traceback(exc_trace)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\vm.py", line 1246, in make_all
    node.op.make_thunk(node, storage_map, compute_map, [], impl=impl)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\op.py", line 131, in make_thunk
    return self.make_c_thunk(node, storage_map, compute_map, no_recycling)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\op.py", line 96, in make_c_thunk
    outputs = cl.make_thunk(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\basic.py", line 1202, in make_thunk
    cthunk, module, in_storage, out_storage, error_storage = self.__compile__(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\basic.py", line 1122, in __compile__
    thunk, module = self.cthunk_factory(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\basic.py", line 1647, in cthunk_factory
    module = cache.module_from_key(key=key, lnk=self)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\cmodule.py", line 1229, in module_from_key
    module = lnk.compile_cmodule(location)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\basic.py", line 1546, in compile_cmodule
    module = c_compiler.compile_str(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\cmodule.py", line 2640, in compile_str
    raise CompileError(
aesara.link.c.exceptions.CompileError: Compilation failed (return status=1):
"C:\miniconda3\envs\pymc_env_strict\Library\mingw-w64\bin\g++.exe" -shared -g -O3 -fno-math-errno -Wno-unused-label -Wno-unused-variable -Wno-write-strings -Wno-c++11-narrowing -fno-exceptions -fno-unwind-tables -fno-asynchronous-unwind-tables -march=broadwell -mmmx -mno-3dnow -msse -msse2 -msse3 -mssse3 -mno-sse4a -mcx16 -msahf -mmovbe -maes -mno-sha -mpclmul -mpopcnt -mabm -mno-lwp -mfma -mno-fma4 -mno-xop -mbmi -mbmi2 -mno-tbm -mram l2-cache-size=8192 -mtune=generic -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -m64 -DMS_WIN64 -I"C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\numpy\core\include" -I"C:\miniconda3\envs\pymc_1 -mclflushopt -menv_aesara\include" -I"C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\aesara\link\c\c_code" -L"C:\miniconda3\envs\pymc_env_aesara\libs" -L"C:\miniconda3\envs\pymc_env_aesara" -o "C:\Users\Opher l=8192 -mtune=geneocal\AppData\Local\Aesara\compiledir_Windows-10-10.0.19043-SP0-Intel64_Family_6_Model_142_Stepping_12_GenuineIntel-3.10.6-64\tmp78frcsc_\mebd8dae10522ca0870e1a82f1ea908002d7232440c31ecf6eadb09903ee4931a3\envs\pymc_env_b.pyd" "C:\Users\Opher local\AppData\Local\Aesara\compiledir_Windows-10-10.0.19043-SP0-Intel64_Family_6_Model_142_Stepping_12_GenuineIntel-3.10.6-64\tmp78frcsc_\mod.cpp" -lmkl_rt "C:\miniconda3\envs\py0.19043-SP0-Intelmc_env_aesara\python310.dll"                                                                                                                                                                             -10-10.0.19043-SP
C:/miniconda3/envs/pymc_env_strict/Library/mingw-w64/bin/../lib/gcc/x86_64-w64-mingw32/5.3.0/../../../../x86_64-w64-mingw32/bin/ld.exe: cannot find -lmkl_rt
collect2.exe: error: ld returned 1 exit status

Apply node that caused the error: Gemm{no_inplace}(obs_y{[[0.757696..72087676]]}, TensorConstant{-1.0}, TensorConstant{[[0.383318..30498162]]}, beta, TensorConstant{1.0})
Toposort index: 0
Inputs types: [TensorType(float64, (420, 6)), TensorType(float64, ()), TensorType(float64, (420, 2)), TensorType(float64, (None, None)), TensorType(float64, ())]

HINT: Use a linker other than the C linker to print the inputs' shapes and strides.
HINT: Re-running with most Aesara optimizations disabled could provide a back-trace showing when this node was created. This can be done by setting the Aesara flag 'optimizer=fast_compile'. If that does not work, Aesars not work, Aesara optimizations can be disabled with 'optimizer=None'.
HINT: Use the Aesara flag `exception_verbosity=high` for a debug print-out and storage map footprint of this Apply node.
PS C:\Opher\GitHub\bsf_donchin_jordan_2022> & C:/miniconda3/envs/pymc_env_aesara/python.exe c:/Opher/GitHub/bsf_donchin_jordan_2022/mkl_rt_test_stripped.py
Traceback (most recent call last):
  File "c:\Opher\GitHub\bsf_donchin_jordan_2022\mkl_rt_test_stripped.py", line 26, in <module>
    model = latent_variable_model(y, x, 2)
  File "c:\Opher\GitHub\bsf_donchin_jordan_2022\mkl_rt_test_stripped.py", line 17, in latent_variable_model
    beta = pm.Normal('beta', mu=0, sigma=1.5, dims=['measure'])
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\distributions\distribution.py", line 292, in __new__
    rv_out = model.register_rv(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\model.py", line 1365, in register_rv
    self.add_random_variable(rv_var, dims)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\model.py", line 1550, in add_random_variable
    raise ValueError(f"Variable name {var.name} already exists.")
ValueError: Variable name beta already exists.

In contrast, by commenting out the lines indicate and removing comments from the ones shown, I get the following:

Expand for the output:

PS C:\Opher\GitHub\bsf_donchin_jordan_2022> conda activate C:\miniconda3\envs\pymc_env_aesara
PS C:\Opher\GitHub\bsf_donchin_jordan_2022> & C:/miniconda3/envs/pymc_env_aesara/python.exe c:/Opher/GitHub/bsf_donchin_jordan_2022/mkl_rt_test_stripped.py
Auto-assigning NUTS sampler...
Initializing NUTS using jitter+adapt_diag...
Multiprocess sampling (4 chains in 4 jobs)
NUTS: [beta]
Auto-assigning NUTS sampler...
Initializing NUTS using jitter+adapt_diag...
Multiprocess sampling (4 chains in 4 jobs)
NUTS: [beta]
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "C:\miniconda3\envs\pymc_env_aesara\lib\multiprocessing\spawn.py", line 116, in spawn_main
    exitcode = _main(fd, parent_sentinel)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\multiprocessing\spawn.py", line 125, in _main
    prepare(preparation_data)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\multiprocessing\spawn.py", line 236, in prepare
    _fixup_main_from_path(data['init_main_from_path'])
  File "C:\miniconda3\envs\pymc_env_aesara\lib\multiprocessing\spawn.py", line 287, in _fixup_main_from_path
    main_content = runpy.run_path(main_path,
  File "C:\miniconda3\envs\pymc_env_aesara\lib\runpy.py", line 289, in run_path
    return _run_module_code(code, init_globals, run_name,
  File "C:\miniconda3\envs\pymc_env_aesara\lib\runpy.py", line 96, in _run_module_code
    _run_code(code, mod_globals, init_globals,
  File "C:\miniconda3\envs\pymc_env_aesara\lib\runpy.py", line 86, in _run_code
    exec(code, run_globals)
  File "c:\Opher\GitHub\bsf_donchin_jordan_2022\mkl_rt_test_stripped.py", line 29, in <module>
    fit = pm.sample()
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\sampling.py", line 613, in sample
    mtrace = _mp_sample(**sample_args, **parallel_args)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\sampling.py", line 1526, in _mp_sample
    sampler = ps.ParallelSampler(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\parallel_sampling.py", line 417, in __init__
    self._samplers = [
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\parallel_sampling.py", line 418, in <listcomp>
    ProcessAdapter(
  File "C:\miniconda3\envs\pymc_env_aesara\lib\site-packages\pymc\parallel_sampling.py", line 286, in __init__
    self._process.start()
  File "C:\miniconda3\envs\pymc_env_aesara\lib\multiprocessing\process.py", line 121, in start
    self._popen = self._Popen(self)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\multiprocessing\context.py", line 336, in _Popen
    return Popen(process_obj)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\multiprocessing\popen_spawn_win32.py", line 45, in __init__
    prep_data = spawn.get_preparation_data(process_obj._name)
  File "C:\miniconda3\envs\pymc_env_aesara\lib\multiprocessing\spawn.py", line 154, in get_preparation_data
    _check_not_importing_main()
  File "C:\miniconda3\envs\pymc_env_aesara\lib\multiprocessing\spawn.py", line 134, in _check_not_importing_main
    raise RuntimeError('''
RuntimeError:
        An attempt has been made to start a new process before the
        current process has finished its bootstrapping phase.

        This probably means that you are not using fork to start your
        child processes and you have forgotten to use the proper idiom
        in the main module:

            if __name__ == '__main__':
                freeze_support()
                ...

        The "freeze_support()" line can be omitted if the program
        is not going to be frozen to produce an executable.

[brandonwillard]

I don't know enough about aesara to build an aesara model without pymc. Sorry about that.

That's fine, but it means that the PyMC-related work being done in this issue should be done in a PyMC issue or Discussion first (i.e. until the Aesara parts of the issue are understood and reproducible). The basic idea is that readers and/or developers here may know nothing about PyMC, so it's less likely that progress would be made here than elsewhere, and that increases the chances of this becoming a stale issue.

[maresb]

Agreed. I should have mentioned that I pinged @lucianopaz, and he intends to take a look at this (in particular in relation to #947) when he finds the time.

[lucianopaz]

@opherdonchin, I reproduced your pymc model to see if I could dive into the issue further, but the model works for me.

I noticed that your aesara.config.blas__ldflags says -lmkl_rt only. Mine says: '-L"C:\\...\\anaconda3\\envs\\pymc-issue-test\\Library\\bin" -lmkl_core -lmkl_intel_thread -lmkl_rt'. So the problem you are seeing is caused by the missing library directory in the blas__ldflags. It's also strange that you don't have the other mkl libraries in those flags.

By any chance, are you attempting to modify the default blas__ldflags? There are three ways to do so:

• Set the value of aesara.config.blas__ldflags at the beginning of the script
• Set a special environment variable in your terminal, the terminal that created the notebook you are using, or inside a notebook cell
• Have an .aesararc file

If imagine that if you are not setting the aesara.config value in your script, it's highly unlikely that you are using environment variables by mistake. I think that the most likely cause to your problem is that you have an .aesararc file in one of the paths listed here that is leading to the incorrect blas flags setup. If you don't have this file, then this might indicate that there is some deeper problem with how aesara sets the default blas__ldflags (which I find very strange), or from where this configuration option is read.

[opherdonchin]

Hi @lucianopaz !

Thanks for the suggestions. In the related PyMC discourse discussion, you suggested I try adding the line:

aesara.config.blas__ldflags = f'"-L{os.path.join(sys.prefix, "Library", "bin")}" -lmkl_core -lmkl_intel_thread -lmkl_rt'

And that works! At least, it works in the stripped down environment with the stripped down script I made for this issue. I'll check the full version later but I don't see why there should be a problem.

I tried following up on the suggestions here as well. I did not find an AESARA_FLAGS or AESARARC environment variable and I also did not find a $HOME$.aesararc or $HOME\.aesararc.txt. Thus, I don't know how the aesara flags have gotten out of whack.

Is there a way to keep following this up beyond this point to identify the original problem? I mean, it is fixed for me, but it would be nice to know what went wrong.

Opher

[lucianopaz]

I honestly don’t know how the blas flags could have gotten to the state they were. If you search for mkl in aesara you find that it’s set in a few scripts in the library, so I don’t understand what could have broken them. Maybe @brandonwillard has an idea?