Develop Reference

LoweringError: Failed in nopython mode pipeline (step: native lowering)

The following is the code I try to run. It used to work but I made changes to some installations (dont remember what unfortunately - scipy or scikit? my kmeans function also stopped working)
from umap import UMAP
umap_2d_lv=UMAP(n_components=2,random_state=0).fit(lv_data,y=cluster_num)
proj_2d_lv=umap_2d_lv.embedding_
this is how I tried to fix the error, from suggestions online:
pip install umap-learn>=0.5.1 & pip install numba==0.53.0
also tried this:
pip install umap-learn
and then
import umap.umap_ as UMAP
this is the the error that comes out:
AttributeError Traceback (most recent call last)
~\AppData\Roaming\Python\Python38\site-packages\numba\core\errors.py in new_error_context(fmt_, *args, **kwargs)
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower_block(self, block)
234 """
--> 235 Create CPython wrapper(s) around this function (or generator).
236 """
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower_inst(self, inst)
379
--> 380 elif isinstance(inst, ir.SetItem):
381 signature = self.fndesc.calltypes[inst]
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower_assign(self, ty, inst)
581
--> 582 def cast_result(res):
583 return self.context.cast(self.builder, res,
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in incref(self, typ, val)
~\AppData\Roaming\Python\Python38\site-packages\numba\core\runtime\context.py in incref(self, builder, typ, value)
217 """
--> 218 self._call_incref_decref(builder, typ, value, "NRT_incref")
219
~\AppData\Roaming\Python\Python38\site-packages\numba\core\runtime\context.py in _call_incref_decref(self, builder, typ, value, funcname)
206 mod = builder.module
--> 207 fn = mod.get_or_insert_function(incref_decref_ty, name=funcname)
208 # XXX "nonnull" causes a crash in test_dyn_array: can this
AttributeError: 'Module' object has no attribute 'get_or_insert_function'
During handling of the above exception, another exception occurred:
LoweringError Traceback (most recent call last)
<timed exec> in <module>
~\anaconda3\lib\site-packages\umap\__init__.py in <module>
1 from warnings import warn, catch_warnings, simplefilter
----> 2 from .umap_ import UMAP
3
4 try:
5 with catch_warnings():
~\anaconda3\lib\site-packages\umap\umap_.py in <module>
30 import umap.distances as dist
31
---> 32 import umap.sparse as sparse
33
34 from umap.utils import (
~\anaconda3\lib\site-packages\umap\sparse.py in <module>
10 import numpy as np
11
---> 12 from umap.utils import norm
13
14 locale.setlocale(locale.LC_NUMERIC, "C")
~\anaconda3\lib\site-packages\umap\utils.py in <module>
39
40 #numba.njit("i4(i8[:])")
---> 41 def tau_rand_int(state):
42 """A fast (pseudo)-random number generator.
43
~\AppData\Roaming\Python\Python38\site-packages\numba\core\decorators.py in wrapper(func)
224
225 return wrapper
--> 226
227
228 def generated_jit(function=None, target='cpu', cache=False,
~\AppData\Roaming\Python\Python38\site-packages\numba\core\dispatcher.py in compile(self, sig)
977 else:
978 return dict((sig, self.overloads[sig].metadata) for sig in self.signatures)
--> 979
980 def get_function_type(self):
981 """Return unique function type of dispatcher when possible, otherwise
~\AppData\Roaming\Python\Python38\site-packages\numba\core\dispatcher.py in compile(self, args, return_type)
139
140 def _get_implementation(self, args, kws):
--> 141 impl = self.py_func(*args, **kws)
142 # Check the generating function and implementation signatures are
143 # compatible, otherwise compiling would fail later.
~\AppData\Roaming\Python\Python38\site-packages\numba\core\dispatcher.py in _compile_cached(self, args, return_type)
153 pyparam.kind != implparam.kind or
154 (implparam.default is not implparam.empty and
--> 155 implparam.default != pyparam.default)):
156 ok = False
157 if not ok:
~\AppData\Roaming\Python\Python38\site-packages\numba\core\dispatcher.py in _compile_core(self, args, return_type)
166 '_CompileStats', ('cache_path', 'cache_hits', 'cache_misses'))
167
--> 168
169 class _CompilingCounter(object):
170 """
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler.py in compile_extra(typingctx, targetctx, func, args, return_type, flags, locals, library, pipeline_class)
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler.py in compile_extra(self, func)
426 """The default compiler
427 """
--> 428
429 def define_pipelines(self):
430 # this maintains the objmode fallback behaviour
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler.py in _compile_bytecode(self)
490 pm.add_pass(AnnotateTypes, "annotate types")
491
--> 492 # strip phis
493 pm.add_pass(PreLowerStripPhis, "remove phis nodes")
494
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler.py in _compile_core(self)
469 return pm
470
--> 471 #staticmethod
472 def define_nopython_lowering_pipeline(state, name='nopython_lowering'):
473 pm = PassManager(name)
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler.py in _compile_core(self)
460 pm.passes.extend(untyped_passes.passes)
461
--> 462 typed_passes = dpb.define_typed_pipeline(state)
463 pm.passes.extend(typed_passes.passes)
464
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler_machinery.py in run(self, state)
341 def dependency_analysis(self):
342 """
--> 343 Computes dependency analysis
344 """
345 deps = dict()
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler_machinery.py in run(self, state)
332 raise BaseException("Legacy pass in use")
333 except _EarlyPipelineCompletion as e:
--> 334 raise e
335 except Exception as e:
336 msg = "Failed in %s mode pipeline (step: %s)" % \
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler_lock.py in _acquire_compile_lock(*args, **kwargs)
33 def _acquire_compile_lock(*args, **kwargs):
34 with self:
---> 35 return func(*args, **kwargs)
36 return _acquire_compile_lock
37
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler_machinery.py in _runPass(self, index, pss, internal_state)
287 mutated |= check(pss.run_initialization, internal_state)
288 with SimpleTimer() as pass_time:
--> 289 mutated |= check(pss.run_pass, internal_state)
290 with SimpleTimer() as finalize_time:
291 mutated |= check(pss.run_finalizer, internal_state)
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler_machinery.py in check(func, compiler_state)
260
261 def check(func, compiler_state):
--> 262 mangled = func(compiler_state)
263 if mangled not in (True, False):
264 msg = ("CompilerPass implementations should return True/False. "
~\AppData\Roaming\Python\Python38\site-packages\numba\core\typed_passes.py in run_pass(self, state)
394 else:
395 if isinstance(restype,
--> 396 (types.Optional, types.Generator)):
397 pass
398 else:
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower(self)
136 self.lower_normal_function(self.fndesc)
137 else:
--> 138 self.genlower = self.GeneratorLower(self)
139 self.gentype = self.genlower.gentype
140
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower_normal_function(self, fndesc)
190 entry_block_tail = self.lower_function_body()
191
--> 192 # Close tail of entry block
193 self.builder.position_at_end(entry_block_tail)
194 self.builder.branch(self.blkmap[self.firstblk])
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower_function_body(self)
219
220 def lower_block(self, block):
--> 221 """
222 Lower the given block.
223 """
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower_block(self, block)
233 def create_cpython_wrapper(self, release_gil=False):
234 """
--> 235 Create CPython wrapper(s) around this function (or generator).
236 """
237 if self.genlower:
~\anaconda3\lib\contextlib.py in __exit__(self, type, value, traceback)
129 value = type()
130 try:
--> 131 self.gen.throw(type, value, traceback)
132 except StopIteration as exc:
133 # Suppress StopIteration *unless* it's the same exception that
~\AppData\Roaming\Python\Python38\site-packages\numba\core\errors.py in new_error_context(fmt_, *args, **kwargs)
LoweringError: Failed in nopython mode pipeline (step: native lowering)
'Module' object has no attribute 'get_or_insert_function'
File "..\..\..\anaconda3\lib\site-packages\umap\utils.py", line 53:
def tau_rand_int(state):
<source elided>
"""
state[0] = (((state[0] & 4294967294) << 12) & 0xFFFFFFFF) ^ (
^
During: lowering "state = arg(0, name=state)" at C:\Users\User\anaconda3\lib\site-packages\umap\utils.py (53)

Attribute Error with: "import umap.umap_ as UMAP"

Using jupyter lab with numba = 0.55.1 and umap learn = 0.5.2. Does it matter that umap has "pypi" as channel and numba doesn't? both in anaconda3. I've already tried several solutions shown here.
So, with the following code:
import umap.umap_ as UMAP
I get the following errors:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
~\AppData\Roaming\Python\Python38\site-packages\numba\core\errors.py in new_error_context(fmt_, *args, **kwargs)
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower_block(self, block)
234 """
--> 235 Create CPython wrapper(s) around this function (or generator).
236 """
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower_inst(self, inst)
379
--> 380 elif isinstance(inst, ir.SetItem):
381 signature = self.fndesc.calltypes[inst]
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower_assign(self, ty, inst)
581
--> 582 def cast_result(res):
583 return self.context.cast(self.builder, res,
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in incref(self, typ, val)
~\AppData\Roaming\Python\Python38\site-packages\numba\core\runtime\context.py in incref(self, builder, typ, value)
217 """
--> 218 self._call_incref_decref(builder, typ, value, "NRT_incref")
219
~\AppData\Roaming\Python\Python38\site-packages\numba\core\runtime\context.py in _call_incref_decref(self, builder, typ, value, funcname)
206 mod = builder.module
--> 207 fn = mod.get_or_insert_function(incref_decref_ty, name=funcname)
208 # XXX "nonnull" causes a crash in test_dyn_array: can this
AttributeError: 'Module' object has no attribute 'get_or_insert_function'
During handling of the above exception, another exception occurred:
LoweringError Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_12580/4057111716.py in <module>
----> 1 import umap.umap_ as UMAP
~\anaconda3\lib\site-packages\umap\umap_.py in <module>
30 import umap.distances as dist
31
---> 32 import umap.sparse as sparse
33
34 from umap.utils import (
~\anaconda3\lib\site-packages\umap\sparse.py in <module>
10 import numpy as np
11
---> 12 from umap.utils import norm
13
14 locale.setlocale(locale.LC_NUMERIC, "C")
~\anaconda3\lib\site-packages\umap\utils.py in <module>
39
40 #numba.njit("i4(i8[:])")
---> 41 def tau_rand_int(state):
42 """A fast (pseudo)-random number generator.
43
~\AppData\Roaming\Python\Python38\site-packages\numba\core\decorators.py in wrapper(func)
224
225 return wrapper
--> 226
227
228 def generated_jit(function=None, target='cpu', cache=False,
~\AppData\Roaming\Python\Python38\site-packages\numba\core\dispatcher.py in compile(self, sig)
977 else:
978 return dict((sig, self.overloads[sig].metadata) for sig in self.signatures)
--> 979
980 def get_function_type(self):
981 """Return unique function type of dispatcher when possible, otherwise
~\AppData\Roaming\Python\Python38\site-packages\numba\core\dispatcher.py in compile(self, args, return_type)
139
140 def _get_implementation(self, args, kws):
--> 141 impl = self.py_func(*args, **kws)
142 # Check the generating function and implementation signatures are
143 # compatible, otherwise compiling would fail later.
~\AppData\Roaming\Python\Python38\site-packages\numba\core\dispatcher.py in _compile_cached(self, args, return_type)
153 pyparam.kind != implparam.kind or
154 (implparam.default is not implparam.empty and
--> 155 implparam.default != pyparam.default)):
156 ok = False
157 if not ok:
~\AppData\Roaming\Python\Python38\site-packages\numba\core\dispatcher.py in _compile_core(self, args, return_type)
166 '_CompileStats', ('cache_path', 'cache_hits', 'cache_misses'))
167
--> 168
169 class _CompilingCounter(object):
170 """
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler.py in compile_extra(typingctx, targetctx, func, args, return_type, flags, locals, library, pipeline_class)
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler.py in compile_extra(self, func)
426 """The default compiler
427 """
--> 428
429 def define_pipelines(self):
430 # this maintains the objmode fallback behaviour
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler.py in _compile_bytecode(self)
490 pm.add_pass(AnnotateTypes, "annotate types")
491
--> 492 # strip phis
493 pm.add_pass(PreLowerStripPhis, "remove phis nodes")
494
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler.py in _compile_core(self)
469 return pm
470
--> 471 #staticmethod
472 def define_nopython_lowering_pipeline(state, name='nopython_lowering'):
473 pm = PassManager(name)
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler.py in _compile_core(self)
460 pm.passes.extend(untyped_passes.passes)
461
--> 462 typed_passes = dpb.define_typed_pipeline(state)
463 pm.passes.extend(typed_passes.passes)
464
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler_machinery.py in run(self, state)
341 def dependency_analysis(self):
342 """
--> 343 Computes dependency analysis
344 """
345 deps = dict()
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler_machinery.py in run(self, state)
332 raise BaseException("Legacy pass in use")
333 except _EarlyPipelineCompletion as e:
--> 334 raise e
335 except Exception as e:
336 msg = "Failed in %s mode pipeline (step: %s)" % \
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler_lock.py in _acquire_compile_lock(*args, **kwargs)
33 def _acquire_compile_lock(*args, **kwargs):
34 with self:
---> 35 return func(*args, **kwargs)
36 return _acquire_compile_lock
37
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler_machinery.py in _runPass(self, index, pss, internal_state)
287 mutated |= check(pss.run_initialization, internal_state)
288 with SimpleTimer() as pass_time:
--> 289 mutated |= check(pss.run_pass, internal_state)
290 with SimpleTimer() as finalize_time:
291 mutated |= check(pss.run_finalizer, internal_state)
~\AppData\Roaming\Python\Python38\site-packages\numba\core\compiler_machinery.py in check(func, compiler_state)
260
261 def check(func, compiler_state):
--> 262 mangled = func(compiler_state)
263 if mangled not in (True, False):
264 msg = ("CompilerPass implementations should return True/False. "
~\AppData\Roaming\Python\Python38\site-packages\numba\core\typed_passes.py in run_pass(self, state)
394 else:
395 if isinstance(restype,
--> 396 (types.Optional, types.Generator)):
397 pass
398 else:
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower(self)
136 self.lower_normal_function(self.fndesc)
137 else:
--> 138 self.genlower = self.GeneratorLower(self)
139 self.gentype = self.genlower.gentype
140
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower_normal_function(self, fndesc)
190 entry_block_tail = self.lower_function_body()
191
--> 192 # Close tail of entry block
193 self.builder.position_at_end(entry_block_tail)
194 self.builder.branch(self.blkmap[self.firstblk])
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower_function_body(self)
219
220 def lower_block(self, block):
--> 221 """
222 Lower the given block.
223 """
~\AppData\Roaming\Python\Python38\site-packages\numba\core\lowering.py in lower_block(self, block)
233 def create_cpython_wrapper(self, release_gil=False):
234 """
--> 235 Create CPython wrapper(s) around this function (or generator).
236 """
237 if self.genlower:
~\anaconda3\lib\contextlib.py in __exit__(self, type, value, traceback)
129 value = type()
130 try:
--> 131 self.gen.throw(type, value, traceback)
132 except StopIteration as exc:
133 # Suppress StopIteration *unless* it's the same exception that
~\AppData\Roaming\Python\Python38\site-packages\numba\core\errors.py in new_error_context(fmt_, *args, **kwargs)
LoweringError: Failed in nopython mode pipeline (step: native lowering)
'Module' object has no attribute 'get_or_insert_function'
File "..\..\..\anaconda3\lib\site-packages\umap\utils.py", line 53:
def tau_rand_int(state):
<source elided>
"""
state[0] = (((state[0] & 4294967294) << 12) & 0xFFFFFFFF) ^ (
^
During: lowering "state = arg(0, name=state)" at C:\Users\User\anaconda3\lib\site-packages\umap\utils.py (53)

NotImplementedError: Failed in nopython mode pipeline. Use of unknown opcode MAP_ADD at line 116 of <ipython-input-287-147d4798a88b>

I try to launch a code with Numba and I get errors.
What I want to do is to compute the cosine similarity with a cosinus_sparse function. This class method I use in the search class method, then I call search in the results method. Although I added the #jit decorator before each method I have this implementation error that appears.
Here is my code:
import numpy as np
from numba import jit
from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer
import pandas as pd
import math
class Search:
def __init__(self, corpus, method='XTERM', stop_words='english', max_df=1.0, min_df=1, max_features=None):
self.corpus = corpus
self.method = method
self.stop_words = stop_words
self.max_df = max_df
self.min_df = min_df
self.max_features = max_features
self.vectorization()
self.get_shape()
self.features_names = self.bag_of_word.get_feature_names()
def vectorization(self):
if self.method == 'XTERM':
self.bag_of_word = CountVectorizer(stop_words=self.stop_words,
max_df=self.max_df, min_df=self.min_df,
max_features=self.max_features)
self.corpus_vectorized = self.bag_of_word.fit_transform(self.corpus)
elif self.method == 'TFxIDF':
self.bag_of_word = TfidfVectorizer(stop_words=self.stop_words,
max_df=self.max_df, min_df=self.min_df,
max_features=self.max_features)
self.corpus_vectorized = self.bag_of_word.fit_transform(self.corpus)
else:
raise MethodError('Method provided is not valid')
def get_shape(self):
self.n_docs, self.n_terms = self.corpus_vectorized.shape
def get_query(self, query):
self.indexes = [self.features_names.index(q) for q in query if q in self.features_names]
self.query_vec = np.zeros(self.n_terms)
self.query_vec[self.indexes] = 1
#staticmethod
#jit(nopython=True)
def cosinus_sparse(i, j):
num = i.dot(j)
spars = i * i.transpose()
den = math.sqrt(spars[0, 0]) * math.sqrt(sum(j * j))
if (den > 0):
return int(num) / den
else:
return 0
#jit(nopython=True)
def search(self, q) -> dict:
cc = {i: self.cosinus_sparse(self.corpus_vectorized[i, :], q) for i in range(self.n_docs)}
cc = sorted(cc.items(), key=lambda x: x[1], reverse=True)
return cc
#jit
def get_result(self) -> list:
self.result = self.search(self.query_vec)
def result_announcer(self):
self.search_lenght = len([i for i in self.result if i[1] > 0])
print('{} documents linked to your query where found'.format(search_lenght))
def verif_query_vec(self, query):
if int(sum(self.query_vec)) != len(query):
raise QueryError('Error in query or query_vec')
def processing(self, query):
try:
self.get_query(query)
self.verif_query_vec(query)
self.get_result()
except NameError:
self.vectorisation()
self.get_shape()
self.get_feature_names()
self.get_query(query)
self.verif_query_vec(query)
self.get_result()
import ipywidgets as widgets
from IPython.display import display
text = widgets.Text(
value='',
placeholder='Type words',
description='String:',
disabled=False
)
method_radio = widgets.RadioButtons(
options=['XTERM', 'TFxIDF'],
# value='TF',
description='Method:',
disabled=False
)
submit = widgets.Button(description = 'Search')
display(widgets.VBox([text, radio, submit]))
def handle_submit(sender):
global query
query = text.value.lower().split(' ')
method = method_radio.value
# instentiation de l'objet de recherche
global search_obj
search_obj = Search(corpus=corpus, method=method, )
search_obj.processing(query)
submit.on_click(handle_submit)
Here is the error
NotImplementedError Traceback (most recent call last)
<ipython-input-288-025a488daa60> in handle_submit(sender)
27 global search_obj
28 search_obj = Search(corpus=corpus, method=method, )
---> 29 search_obj.processing(query)
30
31 submit.on_click(handle_submit)
<ipython-input-287-147d4798a88b> in processing(self, query)
167 self.get_query(query)
168 self.verif_query_vec(query)
--> 169 self.get_result()
170
171 except NameError:
~\Anaconda3\lib\site-packages\numba\dispatcher.py in _compile_for_args(self, *args, **kws)
365 e.patch_message(''.join(e.args) + help_msg)
366 # ignore the FULL_TRACEBACKS config, this needs reporting!
--> 367 raise e
368
369 def inspect_llvm(self, signature=None):
~\Anaconda3\lib\site-packages\numba\dispatcher.py in _compile_for_args(self, *args, **kws)
322 argtypes.append(self.typeof_pyval(a))
323 try:
--> 324 return self.compile(tuple(argtypes))
325 except errors.TypingError as e:
326 # Intercept typing error that may be due to an argument
~\Anaconda3\lib\site-packages\numba\compiler_lock.py in _acquire_compile_lock(*args, **kwargs)
30 def _acquire_compile_lock(*args, **kwargs):
31 with self:
---> 32 return func(*args, **kwargs)
33 return _acquire_compile_lock
34
~\Anaconda3\lib\site-packages\numba\dispatcher.py in compile(self, sig)
653
654 self._cache_misses[sig] += 1
--> 655 cres = self._compiler.compile(args, return_type)
656 self.add_overload(cres)
657 self._cache.save_overload(sig, cres)
~\Anaconda3\lib\site-packages\numba\dispatcher.py in compile(self, args, return_type)
80 args=args, return_type=return_type,
81 flags=flags, locals=self.locals,
---> 82 pipeline_class=self.pipeline_class)
83 # Check typing error if object mode is used
84 if cres.typing_error is not None and not flags.enable_pyobject:
~\Anaconda3\lib\site-packages\numba\compiler.py in compile_extra(typingctx, targetctx, func, args, return_type, flags, locals, library, pipeline_class)
924 pipeline = pipeline_class(typingctx, targetctx, library,
925 args, return_type, flags, locals)
--> 926 return pipeline.compile_extra(func)
927
928
~\Anaconda3\lib\site-packages\numba\compiler.py in compile_extra(self, func)
372 self.lifted = ()
373 self.lifted_from = None
--> 374 return self._compile_bytecode()
375
376 def compile_ir(self, func_ir, lifted=(), lifted_from=None):
~\Anaconda3\lib\site-packages\numba\compiler.py in _compile_bytecode(self)
855 """
856 assert self.func_ir is None
--> 857 return self._compile_core()
858
859 def _compile_ir(self):
~\Anaconda3\lib\site-packages\numba\compiler.py in _compile_core(self)
842 self.define_pipelines(pm)
843 pm.finalize()
--> 844 res = pm.run(self.status)
845 if res is not None:
846 # Early pipeline completion
~\Anaconda3\lib\site-packages\numba\compiler_lock.py in _acquire_compile_lock(*args, **kwargs)
30 def _acquire_compile_lock(*args, **kwargs):
31 with self:
---> 32 return func(*args, **kwargs)
33 return _acquire_compile_lock
34
~\Anaconda3\lib\site-packages\numba\compiler.py in run(self, status)
253 # No more fallback pipelines?
254 if is_final_pipeline:
--> 255 raise patched_exception
256 # Go to next fallback pipeline
257 else:
~\Anaconda3\lib\site-packages\numba\compiler.py in run(self, status)
244 try:
245 event(stage_name)
--> 246 stage()
247 except _EarlyPipelineCompletion as e:
248 return e.result
~\Anaconda3\lib\site-packages\numba\compiler.py in stage_inline_pass(self)
582 self.flags.auto_parallel,
583 self.parfor_diagnostics.replaced_fns)
--> 584 inline_pass.run()
585 # Remove all Dels, and re-run postproc
586 post_proc = postproc.PostProcessor(self.func_ir)
~\Anaconda3\lib\site-packages\numba\inline_closurecall.py in run(self)
75
76 if guard(self._inline_closure,
---> 77 work_list, block, i, func_def):
78 modified = True
79 break # because block structure changed
~\Anaconda3\lib\site-packages\numba\ir_utils.py in guard(func, *args, **kwargs)
1358 """
1359 try:
-> 1360 return func(*args, **kwargs)
1361 except GuardException:
1362 return None
~\Anaconda3\lib\site-packages\numba\inline_closurecall.py in _inline_closure(self, work_list, block, i, func_def)
212 inline_closure_call(self.func_ir,
213 self.func_ir.func_id.func.__globals__,
--> 214 block, i, func_def, work_list=work_list)
215 return True
216
~\Anaconda3\lib\site-packages\numba\inline_closurecall.py in inline_closure_call(func_ir, glbls, block, i, callee, typingctx, arg_typs, typemap, calltypes, work_list)
253 callee_closure = callee.closure if hasattr(callee, 'closure') else callee.__closure__
254 # first, get the IR of the callee
--> 255 callee_ir = get_ir_of_code(glbls, callee_code)
256 callee_blocks = callee_ir.blocks
257
~\Anaconda3\lib\site-packages\numba\ir_utils.py in get_ir_of_code(glbls, fcode)
1572 f.__name__ = fcode.co_name
1573 from numba import compiler
-> 1574 ir = compiler.run_frontend(f)
1575 # we need to run the before inference rewrite pass to normalize the IR
1576 # XXX: check rewrite pass flag?
~\Anaconda3\lib\site-packages\numba\compiler.py in run_frontend(func)
168 interp = interpreter.Interpreter(func_id)
169 bc = bytecode.ByteCode(func_id=func_id)
--> 170 func_ir = interp.interpret(bc)
171 post_proc = postproc.PostProcessor(func_ir)
172 post_proc.run()
~\Anaconda3\lib\site-packages\numba\interpreter.py in interpret(self, bytecode)
101 # Data flow analysis
102 self.dfa = dataflow.DataFlowAnalysis(self.cfa)
--> 103 self.dfa.run()
104
105 # Temp states during interpretation
~\Anaconda3\lib\site-packages\numba\dataflow.py in run(self)
26 def run(self):
27 for blk in self.cfa.iterliveblocks():
---> 28 self.infos[blk.offset] = self.run_on_block(blk)
29
30 def run_on_block(self, blk):
~\Anaconda3\lib\site-packages\numba\dataflow.py in run_on_block(self, blk)
76 for offset in blk:
77 inst = self.bytecode[offset]
---> 78 self.dispatch(info, inst)
79 return info
80
~\Anaconda3\lib\site-packages\numba\dataflow.py in dispatch(self, info, inst)
86 fname = "op_%s" % inst.opname.replace('+', '_')
87 fn = getattr(self, fname, self.handle_unknown_opcode)
---> 88 fn(info, inst)
89
90 def handle_unknown_opcode(self, info, inst):
~\Anaconda3\lib\site-packages\numba\dataflow.py in handle_unknown_opcode(self, info, inst)
91 msg = "Use of unknown opcode {} at line {} of {}"
92 raise NotImplementedError(msg.format(inst.opname, inst.lineno,
---> 93 self.bytecode.func_id.filename))
94
95 def dup_topx(self, info, inst, count):
NotImplementedError: Failed in nopython mode pipeline (step: inline calls to locally defined closures)
Use of unknown opcode MAP_ADD at line 116 of <ipython-input-287-147d4798a88b>
How do I fix this error?
Thanks a lot for your help.

opening computer files using kivy, getting a unicode error

import kivy
from kivy.app import App
from kivy.uix.boxlayout import BoxLayout
from kivy.lang import Builder
from kivy.config import Config
from kivy.uix.button import Button
from kivy.uix.filechooser import FileChooserListView
Config.set('graphics', 'fullscreen', '0')#keeps screen in a smaller window when running
Config.write()
import os
class MyWidget(BoxLayout):
def __init__(self, **kwargs):
super(MyWidget,self).__init__(**kwargs)
container = BoxLayout(orientation='vertical')
filechooser = FileChooserListView()
filechooser.bind(on_selection=lambda x: self.selected(filechooser.selection))
open_btn = Button(text='open', size_hint=(1, .2))
open_btn.bind(on_release=lambda x: self.open(filechooser.path, filechooser.selection))
container.add_widget(filechooser)
container.add_widget(open_btn)
self.add_widget(container)
def open(self, path, filename):
print(filename)
if len(filename) > 0:
with open(os.path.join(path, filename[0])) as f:
print(f.read())
def selected(self, filename):
print("selected: %s" % filename[0])
class MyApp(App):
def build(self):
return MyWidget()
if __name__ == '__main__':
MyApp().run()
I am trying to create a program that can open files in kivy, I have a feeling its something to do with my 'os.path.join' I tried to add 'enconding =utf-8' to the area in the code where it says 'with open' that did not work in both cases. Below is the full error, maybe im missing something but hopefully the full error will help.
UnicodeDecodeError Traceback (most recent call last)
<ipython-input-1-ad2b3c0779e3> in <module>
45
46 if __name__ == '__main__':
---> 47 MyApp().run()
~\anaconda3\lib\site-packages\kivy\app.py in run(self)
853
854 self.dispatch('on_start')
--> 855 runTouchApp()
856 self.stop()
857
~\anaconda3\lib\site-packages\kivy\base.py in runTouchApp(widget, slave)
502 _run_mainloop()
503 else:
--> 504 EventLoop.window.mainloop()
505 finally:
506 stopTouchApp()
~\anaconda3\lib\site-packages\kivy\core\window\window_sdl2.py in mainloop(self)
745 while not EventLoop.quit and EventLoop.status == 'started':
746 try:
--> 747 self._mainloop()
748 except BaseException as inst:
749 # use exception manager first
~\anaconda3\lib\site-packages\kivy\core\window\window_sdl2.py in _mainloop(self)
477
478 def _mainloop(self):
--> 479 EventLoop.idle()
480
481 # for android/iOS, we don't want to have any event nor executing our
~\anaconda3\lib\site-packages\kivy\base.py in idle(self)
340
341 # read and dispatch input from providers
--> 342 self.dispatch_input()
343
344 # flush all the canvas operation
~\anaconda3\lib\site-packages\kivy\base.py in dispatch_input(self)
325 post_dispatch_input = self.post_dispatch_input
326 while input_events:
--> 327 post_dispatch_input(*pop(0))
328
329 def idle(self):
~\anaconda3\lib\site-packages\kivy\base.py in post_dispatch_input(self, etype, me)
291 wid.dispatch('on_touch_up', me)
292 else:
--> 293 wid.dispatch('on_touch_up', me)
294
295 wid._context.pop()
kivy\_event.pyx in kivy._event.EventDispatcher.dispatch()
~\anaconda3\lib\site-packages\kivy\uix\behaviors\button.py in on_touch_up(self, touch)
177 else:
178 self._do_release()
--> 179 self.dispatch('on_release')
180 return True
181
kivy\_event.pyx in kivy._event.EventDispatcher.dispatch()
kivy\_event.pyx in kivy._event.EventObservers.dispatch()
kivy\_event.pyx in kivy._event.EventObservers._dispatch()
<ipython-input-1-ad2b3c0779e3> in <lambda>(x)
23
24 open_btn = Button(text='open', size_hint=(1, .2))
---> 25 open_btn.bind(on_release=lambda x: self.open(filechooser.path, filechooser.selection))
26
27 container.add_widget(filechooser)
<ipython-input-1-ad2b3c0779e3> in open(self, path, filename)
33 if len(filename) > 0:
34 with open(os.path.join(path, filename[0])) as f:
---> 35 print(f.read())
36
37 def selected(self, filename):
~\anaconda3\lib\encodings\cp1252.py in decode(self, input, final)
21 class IncrementalDecoder(codecs.IncrementalDecoder):
22 def decode(self, input, final=False):
---> 23 return codecs.charmap_decode(input,self.errors,decoding_table)[0]
24
25 class StreamWriter(Codec,codecs.StreamWriter):
UnicodeDecodeError: 'charmap' codec can't decode byte 0x8f in position 57: character maps to <undefined>
​

"Error while extracting" from tensorflow datasets

I want to train a tensorflow image segmentation model on COCO, and thought I would leverage the dataset builder already included. Download seems to be completed but it crashes on extracting the zip files.
Running with TF 2.0.0 on a Jupyter Notebook under a conda environment. Computer is 64-bit Windows 10. The Oxford Pet III dataset used in the official image segmentation tutorial works fine.
Below is the error message (my local user name replaced with %user%).
---------------------------------------------------------------------------
OutOfRangeError Traceback (most recent call last)
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\extractor.py in _sync_extract(self, from_path, method, to_path)
88 try:
---> 89 for path, handle in iter_archive(from_path, method):
90 path = tf.compat.as_text(path)
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\extractor.py in iter_zip(arch_f)
176 with _open_or_pass(arch_f) as fobj:
--> 177 z = zipfile.ZipFile(fobj)
178 for member in z.infolist():
~\.conda\envs\tf-tutorial\lib\zipfile.py in __init__(self, file, mode, compression, allowZip64)
1130 if mode == 'r':
-> 1131 self._RealGetContents()
1132 elif mode in ('w', 'x'):
~\.conda\envs\tf-tutorial\lib\zipfile.py in _RealGetContents(self)
1193 try:
-> 1194 endrec = _EndRecData(fp)
1195 except OSError:
~\.conda\envs\tf-tutorial\lib\zipfile.py in _EndRecData(fpin)
263 # Determine file size
--> 264 fpin.seek(0, 2)
265 filesize = fpin.tell()
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\util\deprecation.py in new_func(*args, **kwargs)
506 instructions)
--> 507 return func(*args, **kwargs)
508
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\lib\io\file_io.py in seek(self, offset, whence, position)
166 elif whence == 2:
--> 167 offset += self.size()
168 else:
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\lib\io\file_io.py in size(self)
101 """Returns the size of the file."""
--> 102 return stat(self.__name).length
103
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\lib\io\file_io.py in stat(filename)
726 """
--> 727 return stat_v2(filename)
728
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\lib\io\file_io.py in stat_v2(path)
743 file_statistics = pywrap_tensorflow.FileStatistics()
--> 744 pywrap_tensorflow.Stat(compat.as_bytes(path), file_statistics)
745 return file_statistics
OutOfRangeError: C:\Users\%user%\tensorflow_datasets\downloads\images.cocodataset.org_zips_train20147eQIfmQL3bpVDgkOrnAQklNLVUtCsFrDPwMAuYSzF3U.zip; Unknown error
During handling of the above exception, another exception occurred:
ExtractError Traceback (most recent call last)
<ipython-input-27-887fa0198611> in <module>
1 cocoBuilder = tfds.builder('coco')
2 info = cocoBuilder.info
----> 3 cocoBuilder.download_and_prepare()
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\api_utils.py in disallow_positional_args_dec(fn, instance, args, kwargs)
50 _check_no_positional(fn, args, ismethod, allowed=allowed)
51 _check_required(fn, kwargs)
---> 52 return fn(*args, **kwargs)
53
54 return disallow_positional_args_dec(wrapped) # pylint: disable=no-value-for-parameter
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\dataset_builder.py in download_and_prepare(self, download_dir, download_config)
285 self._download_and_prepare(
286 dl_manager=dl_manager,
--> 287 download_config=download_config)
288
289 # NOTE: If modifying the lines below to put additional information in
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\dataset_builder.py in _download_and_prepare(self, dl_manager, download_config)
946 super(GeneratorBasedBuilder, self)._download_and_prepare(
947 dl_manager=dl_manager,
--> 948 max_examples_per_split=download_config.max_examples_per_split,
949 )
950
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\dataset_builder.py in _download_and_prepare(self, dl_manager, **prepare_split_kwargs)
802 # Generating data for all splits
803 split_dict = splits_lib.SplitDict()
--> 804 for split_generator in self._split_generators(dl_manager):
805 if splits_lib.Split.ALL == split_generator.split_info.name:
806 raise ValueError(
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\image\coco.py in _split_generators(self, dl_manager)
237 root_url = 'http://images.cocodataset.org/'
238 extracted_paths = dl_manager.download_and_extract({
--> 239 key: root_url + url for key, url in urls.items()
240 })
241
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\download_manager.py in download_and_extract(self, url_or_urls)
357 with self._downloader.tqdm():
358 with self._extractor.tqdm():
--> 359 return _map_promise(self._download_extract, url_or_urls)
360
361 #property
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\download_manager.py in _map_promise(map_fn, all_inputs)
393 """Map the function into each element and resolve the promise."""
394 all_promises = utils.map_nested(map_fn, all_inputs) # Apply the function
--> 395 res = utils.map_nested(_wait_on_promise, all_promises)
396 return res
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\utils\py_utils.py in map_nested(function, data_struct, dict_only, map_tuple)
127 return {
128 k: map_nested(function, v, dict_only, map_tuple)
--> 129 for k, v in data_struct.items()
130 }
131 elif not dict_only:
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\utils\py_utils.py in <dictcomp>(.0)
127 return {
128 k: map_nested(function, v, dict_only, map_tuple)
--> 129 for k, v in data_struct.items()
130 }
131 elif not dict_only:
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\utils\py_utils.py in map_nested(function, data_struct, dict_only, map_tuple)
141 return tuple(mapped)
142 # Singleton
--> 143 return function(data_struct)
144
145
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\download_manager.py in _wait_on_promise(p)
377
378 def _wait_on_promise(p):
--> 379 return p.get()
380
381 else:
~\.conda\envs\tf-tutorial\lib\site-packages\promise\promise.py in get(self, timeout)
508 target = self._target()
509 self._wait(timeout or DEFAULT_TIMEOUT)
--> 510 return self._target_settled_value(_raise=True)
511
512 def _target_settled_value(self, _raise=False):
~\.conda\envs\tf-tutorial\lib\site-packages\promise\promise.py in _target_settled_value(self, _raise)
512 def _target_settled_value(self, _raise=False):
513 # type: (bool) -> Any
--> 514 return self._target()._settled_value(_raise)
515
516 _value = _reason = _target_settled_value
~\.conda\envs\tf-tutorial\lib\site-packages\promise\promise.py in _settled_value(self, _raise)
222 if _raise:
223 raise_val = self._fulfillment_handler0
--> 224 reraise(type(raise_val), raise_val, self._traceback)
225 return self._fulfillment_handler0
226
~\.conda\envs\tf-tutorial\lib\site-packages\six.py in reraise(tp, value, tb)
694 if value.__traceback__ is not tb:
695 raise value.with_traceback(tb)
--> 696 raise value
697 finally:
698 value = None
~\.conda\envs\tf-tutorial\lib\site-packages\promise\promise.py in handle_future_result(future)
840 # type: (Any) -> None
841 try:
--> 842 resolve(future.result())
843 except Exception as e:
844 tb = exc_info()[2]
~\.conda\envs\tf-tutorial\lib\concurrent\futures\_base.py in result(self, timeout)
423 raise CancelledError()
424 elif self._state == FINISHED:
--> 425 return self.__get_result()
426
427 self._condition.wait(timeout)
~\.conda\envs\tf-tutorial\lib\concurrent\futures\_base.py in __get_result(self)
382 def __get_result(self):
383 if self._exception:
--> 384 raise self._exception
385 else:
386 return self._result
~\.conda\envs\tf-tutorial\lib\concurrent\futures\thread.py in run(self)
54
55 try:
---> 56 result = self.fn(*self.args, **self.kwargs)
57 except BaseException as exc:
58 self.future.set_exception(exc)
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\extractor.py in _sync_extract(self, from_path, method, to_path)
92 except BaseException as err:
93 msg = 'Error while extracting %s to %s : %s' % (from_path, to_path, err)
---> 94 raise ExtractError(msg)
95 # `tf.io.gfile.Rename(overwrite=True)` doesn't work for non empty
96 # directories, so delete destination first, if it already exists.
ExtractError: Error while extracting C:\Users\%user%\tensorflow_datasets\downloads\images.cocodataset.org_zips_train20147eQIfmQL3bpVDgkOrnAQklNLVUtCsFrDPwMAuYSzF3U.zip to C:\Users\%user%\tensorflow_datasets\downloads\extracted\ZIP.images.cocodataset.org_zips_train20147eQIfmQL3bpVDgkOrnAQklNLVUtCsFrDPwMAuYSzF3U.zip : C:\Users\%user%\tensorflow_datasets\downloads\images.cocodataset.org_zips_train20147eQIfmQL3bpVDgkOrnAQklNLVUtCsFrDPwMAuYSzF3U.zip; Unknown error
The message seems cryptic to me. The folder to which it is trying to extract does not exist when the notebook is started - it is created by Tensorflow, and only at that command line. I obviously tried deleting it completely and running it again, to no effect.
The code that leads to the error is (everything runs fine until the last line):
import tensorflow as tf
from __future__ import absolute_import, division, print_function, unicode_literals
from tensorflow_examples.models.pix2pix import pix2pix
import tensorflow_datasets as tfds
from IPython.display import clear_output
import matplotlib.pyplot as plt
dataset, info = tfds.load('coco', with_info=True)
Also tried breaking down the last command into assigning the tdfs.builder object and then running download_and_extract, and again got the same error.
There is enough space in disk - after download, still 50+GB available, while the dataset is supposed to be 37GB in its largest version (2014).

I have a similar problem with Windows 10 & COCO 2017. My solution is simple. Extract the ZIP file manually according to the folder path in the error message.