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.
Related
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)
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)
I am simply trying to plot some values against datetime64[ns] timestamps with holoviews.
That is,
x-axis = nx1 datetime64[ns] values
y-axis = nx1 data.
Here is a screen shot of what I have:
Screenshot of my dataframe
<class 'pandas._libs.tslibs.timestamps.Timestamp'>
and my overall code:
import hvplot.pandas
import pandas as pd
##
Code ommitted at the start to extract data and create dictionary to convert to data frame
##
#create dictionary
temp_dict = dict(sampling_time=time_y_value_is_taken, y_axis_values = y_values)
df = pd.Dataframe.from_dict(temp_dict)
df.sampling_time=df.sampling_time.astype('datetime64[ns]')
df=df.set_index('sampling_time')
##The following code cannot run this line- it throws error
df.hvplot.line()
I keep getting the error code : 'pandas_datetime_types' is not defined. I have also tried importing datetime as datetime - but it does not work.
EDIT: Here is the traceback:
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
~\miniconda3\envs\mpess_visual\lib\site-packages\IPython\core\formatters.py in __call__(self, obj, include, exclude)
968
969 if method is not None:
--> 970 return method(include=include, exclude=exclude)
971 return None
972 else:
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\core\dimension.py in _repr_mimebundle_(self, include, exclude)
1315 combined and returned.
1316 """
-> 1317 return Store.render(self)
1318
1319
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\core\options.py in render(cls, obj)
1403 data, metadata = {}, {}
1404 for hook in hooks:
-> 1405 ret = hook(obj)
1406 if ret is None:
1407 continue
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\ipython\display_hooks.py in pprint_display(obj)
280 if not ip.display_formatter.formatters['text/plain'].pprint:
281 return None
--> 282 return display(obj, raw_output=True)
283
284
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\ipython\display_hooks.py in display(obj, raw_output, **kwargs)
250 elif isinstance(obj, (CompositeOverlay, ViewableElement)):
251 with option_state(obj):
--> 252 output = element_display(obj)
253 elif isinstance(obj, (Layout, NdLayout, AdjointLayout)):
254 with option_state(obj):
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\ipython\display_hooks.py in wrapped(element)
144 try:
145 max_frames = OutputSettings.options['max_frames']
--> 146 mimebundle = fn(element, max_frames=max_frames)
147 if mimebundle is None:
148 return {}, {}
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\ipython\display_hooks.py in element_display(element, max_frames)
190 return None
191
--> 192 return render(element)
193
194
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\ipython\display_hooks.py in render(obj, **kwargs)
66 renderer = renderer.instance(fig='png')
67
---> 68 return renderer.components(obj, **kwargs)
69
70
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\plotting\renderer.py in components(self, obj, fmt, comm, **kwargs)
408 doc = Document()
409 with config.set(embed=embed):
--> 410 model = plot.layout._render_model(doc, comm)
411 if embed:
412 return render_model(model, comm)
~\miniconda3\envs\mpess_visual\lib\site-packages\panel\viewable.py in _render_model(self, doc, comm)
453 if comm is None:
454 comm = state._comm_manager.get_server_comm()
--> 455 model = self.get_root(doc, comm)
456
457 if config.embed:
~\miniconda3\envs\mpess_visual\lib\site-packages\panel\viewable.py in get_root(self, doc, comm, preprocess)
510 """
511 doc = init_doc(doc)
--> 512 root = self._get_model(doc, comm=comm)
513 if preprocess:
514 self._preprocess(root)
~\miniconda3\envs\mpess_visual\lib\site-packages\panel\layout\base.py in _get_model(self, doc, root, parent, comm)
120 if root is None:
121 root = model
--> 122 objects = self._get_objects(model, [], doc, root, comm)
123 props = dict(self._init_params(), objects=objects)
124 model.update(**self._process_param_change(props))
~\miniconda3\envs\mpess_visual\lib\site-packages\panel\layout\base.py in _get_objects(self, model, old_objects, doc, root, comm)
110 else:
111 try:
--> 112 child = pane._get_model(doc, root, model, comm)
113 except RerenderError:
114 return self._get_objects(model, current_objects[:i], doc, root, comm)
~\miniconda3\envs\mpess_visual\lib\site-packages\panel\pane\holoviews.py in _get_model(self, doc, root, parent, comm)
237 plot = self.object
238 else:
--> 239 plot = self._render(doc, comm, root)
240
241 plot.pane = self
~\miniconda3\envs\mpess_visual\lib\site-packages\panel\pane\holoviews.py in _render(self, doc, comm, root)
304 kwargs['comm'] = comm
305
--> 306 return renderer.get_plot(self.object, **kwargs)
307
308 def _cleanup(self, root):
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\plotting\bokeh\renderer.py in get_plot(self_or_cls, obj, doc, renderer, **kwargs)
71 combining the bokeh model with another plot.
72 """
---> 73 plot = super(BokehRenderer, self_or_cls).get_plot(obj, doc, renderer, **kwargs)
74 if plot.document is None:
75 plot.document = Document() if self_or_cls.notebook_context else curdoc()
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\plotting\renderer.py in get_plot(self_or_cls, obj, doc, renderer, comm, **kwargs)
241 init_key = tuple(v if d is None else d for v, d in
242 zip(plot.keys[0], defaults))
--> 243 plot.update(init_key)
244 else:
245 plot = obj
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\plotting\plot.py in update(self, key)
980 def update(self, key):
981 if len(self) == 1 and ((key == 0) or (key == self.keys[0])) and not self.drawn:
--> 982 return self.initialize_plot()
983 item = self.__getitem__(key)
984 self.traverse(lambda x: setattr(x, '_updated', True))
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\plotting\bokeh\element.py in initialize_plot(self, ranges, plot, plots, source)
1388 element = self.hmap.last
1389 key = util.wrap_tuple(self.hmap.last_key)
-> 1390 ranges = self.compute_ranges(self.hmap, key, ranges)
1391 self.current_ranges = ranges
1392 self.current_frame = element
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\plotting\plot.py in compute_ranges(self, obj, key, ranges)
636 if (not (axiswise and not isinstance(obj, HoloMap)) or
637 (not framewise and isinstance(obj, HoloMap))):
--> 638 self._compute_group_range(group, elements, ranges, framewise,
639 axiswise, robust, self.top_level,
640 prev_frame)
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\plotting\plot.py in _compute_group_range(cls, group, elements, ranges, framewise, axiswise, robust, top_level, prev_frame)
853 continue
854 matching &= (
--> 855 len({'date' if isinstance(v, util.datetime_types) else 'number'
856 for rng in rs for v in rng if util.isfinite(v)}) < 2
857 )
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\plotting\plot.py in <setcomp>(.0)
854 matching &= (
855 len({'date' if isinstance(v, util.datetime_types) else 'number'
--> 856 for rng in rs for v in rng if util.isfinite(v)}) < 2
857 )
858 if matching:
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\core\util.py in isfinite(val)
902 return finite
903 elif isinstance(val, datetime_types+timedelta_types):
--> 904 return not isnat(val)
905 elif isinstance(val, (basestring, bytes)):
906 return True
~\miniconda3\envs\mpess_visual\lib\site-packages\holoviews\core\util.py in isnat(val)
866 elif pd and val is pd.NaT:
867 return True
--> 868 elif pd and isinstance(val, pandas_datetime_types+pandas_timedelta_types):
869 return pd.isna(val)
870 else:
NameError: name 'pandas_datetime_types' is not defined
Any suggestions? Thank you
Although I couldn't find any official doc to support my statement, it's a compatibility issue (HoloViews 1.14.4 was released before Pandas 1.3.0).
Looking at [gitHub]: holoviz/holoviews - (v1.14.4) holoviews/holoviews/core/util.py (starting with line #83), there are some conditional imports. One of them is ABCIndexClass.
[GitHub]: pandas-dev/pandas - (v1.3.0) pandas/pandas/core/dtypes/dtypes.py on the other hand, does not provide it (as opposed from let's say its v1.2.5 counterpart) yielding (silent) exception, and the behavior you're experiencing.
Ways to go:
Upgrade HoloViews to v1.14.5 which no longer has this problem, (or at least, there's a Pandas 1.3.0 conditional as well - fixed by [GitHub]: holoviz/holoviews - Add support for pandas>=1.3)
You could also downgrade Pandas to (e.g.) v1.2.5, although this is not the way to go
I am trying to load a sasbdat file in python using pd.read_sas() and I fail to load the data due to the below error.
ValueError Traceback (most recent call last)
<ipython-input-148-64f915da8256> in <module>
----> 1 df_sas = pd.read_sas('input_sasfile.sas7bdat', format='sas7bdat')
~\.conda\envs\overloaded-new\lib\site-packages\pandas\io\sas\sasreader.py in read_sas(filepath_or_buffer, format, index, encoding, chunksize, iterator)
121
122 reader = SAS7BDATReader(
--> 123 filepath_or_buffer, index=index, encoding=encoding, chunksize=chunksize
124 )
125 else:
~\.conda\envs\overloaded-new\lib\site-packages\pandas\io\sas\sas7bdat.py in __init__(self, path_or_buf, index, convert_dates, blank_missing, chunksize, encoding, convert_text, convert_header_text)
144
145 self._get_properties()
--> 146 self._parse_metadata()
147
148 def column_data_lengths(self):
~\.conda\envs\overloaded-new\lib\site-packages\pandas\io\sas\sas7bdat.py in _parse_metadata(self)
349 self.close()
350 raise ValueError("Failed to read a meta data page from the SAS file.")
--> 351 done = self._process_page_meta()
352
353 def _process_page_meta(self):
~\.conda\envs\overloaded-new\lib\site-packages\pandas\io\sas\sas7bdat.py in _process_page_meta(self)
355 pt = [const.page_meta_type, const.page_amd_type] + const.page_mix_types
356 if self._current_page_type in pt:
--> 357 self._process_page_metadata()
358 is_data_page = self._current_page_type & const.page_data_type
359 is_mix_page = self._current_page_type in const.page_mix_types
~\.conda\envs\overloaded-new\lib\site-packages\pandas\io\sas\sas7bdat.py in _process_page_metadata(self)
388 subheader_signature = self._read_subheader_signature(pointer.offset)
389 subheader_index = self._get_subheader_index(
--> 390 subheader_signature, pointer.compression, pointer.ptype
391 )
392 self._process_subheader(subheader_index, pointer)
~\.conda\envs\overloaded-new\lib\site-packages\pandas\io\sas\sas7bdat.py in _get_subheader_index(self, signature, compression, ptype)
401 else:
402 self.close()
--> 403 raise ValueError("Unknown subheader signature")
404 return index
405
ValueError: Unknown subheader signature
Though I found relevant github issue (https://github.com/pandas-dev/pandas/issues/24794), but it was closed because the issue got resolved by updating the pandas.
Any help is greatly appreciated.
I was working just fine with Google Colaboratory and suddenly this error started to pop up each time I try to load any type of file. It first started when I was trying to read an hdf file, now everything won't open.
---------------------------------------------------------------------------
OSError Traceback (most recent call last)
<ipython-input-8-65c4e8d1c435> in <module>()
----> 1 eo=EOPatch.load('./20.Clean_Textural_features/eopatch_0')
2 eo
9 frames
/usr/local/lib/python3.6/dist-packages/eolearn/core/eodata.py in load(path, features, lazy_loading, filesystem)
530 path = '/'
531
--> 532 return load_eopatch(EOPatch(), filesystem, path, features=features, lazy_loading=lazy_loading)
533
534 def time_series(self, ref_date=None, scale_time=1):
/usr/local/lib/python3.6/dist-packages/eolearn/core/eodata_io.py in load_eopatch(eopatch, filesystem, patch_location, features, lazy_loading)
76 loading_data = executor.map(lambda loader: loader.load(), loading_data)
77
---> 78 for (ftype, fname, _), value in zip(features, loading_data):
79 eopatch[(ftype, fname)] = value
80
/usr/lib/python3.6/concurrent/futures/_base.py in result_iterator()
584 # Careful not to keep a reference to the popped future
585 if timeout is None:
--> 586 yield fs.pop().result()
587 else:
588 yield fs.pop().result(end_time - time.monotonic())
/usr/lib/python3.6/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)
/usr/lib/python3.6/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
/usr/lib/python3.6/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)
/usr/local/lib/python3.6/dist-packages/eolearn/core/eodata_io.py in <lambda>(loader)
74 if not lazy_loading:
75 with concurrent.futures.ThreadPoolExecutor() as executor:
---> 76 loading_data = executor.map(lambda loader: loader.load(), loading_data)
77
78 for (ftype, fname, _), value in zip(features, loading_data):
/usr/local/lib/python3.6/dist-packages/eolearn/core/eodata_io.py in load(self)
217 return self._decode(gzip_fp, self.path)
218
--> 219 return self._decode(file_handle, self.path)
220
221 def save(self, data, file_format, compress_level=0):
/usr/local/lib/python3.6/dist-packages/eolearn/core/eodata_io.py in _decode(file, path)
268
269 if FileFormat.NPY.extension() in path:
--> 270 return np.load(file)
271
272 raise ValueError('Unsupported data type.')
/usr/local/lib/python3.6/dist-packages/numpy/lib/npyio.py in load(file, mmap_mode, allow_pickle, fix_imports, encoding)
434 _ZIP_SUFFIX = b'PK\x05\x06' # empty zip files start with this
435 N = len(format.MAGIC_PREFIX)
--> 436 magic = fid.read(N)
437 # If the file size is less than N, we need to make sure not
438 # to seek past the beginning of the file
OSError: [Errno 5] Input/output error
Also some notebooks won't open and this appears instead:
I looked around at similar posts here, but didn't understand anything. Therefore, any help would be highly appreciated.
PS: my files are in subfolders and not directly contained in 'My Drive'. I have a lso disabled all the adblocks ad the problem persists...
I think the file/link has been used for downloading beyond its weekly limit. This answer may help you.
Some discussion about Google's policy on hosting data on drive.
The solution is to wait for couple of hours/days and try again.