after_merge stringlengths 64 17k | before_merge stringlengths 60 17k | source code and errors stringlengths 236 32.3k | full_traceback stringlengths 170 17.7k | traceback_type stringclasses 60
values |
|---|---|---|---|---|
def cmdb_get_mainline_object_topo(request, bk_biz_id, bk_supplier_account=''):
"""
@summary: 获取配置平台业务拓扑模型
@param request:
@param bk_biz_id:
@param bk_supplier_account:
@return:
"""
kwargs = {
'bk_biz_id': bk_biz_id,
'bk_supplier_account': bk_supplier_account,
}
cl... | def cmdb_get_mainline_object_topo(request, bk_biz_id, bk_supplier_account=''):
"""
@summary: 获取配置平台业务拓扑模型
@param request:
@param bk_biz_id:
@param bk_supplier_account:
@return:
"""
kwargs = {
'bk_biz_id': bk_biz_id,
'bk_supplier_account': bk_supplier_account,
}
cl... | [{'piece_type': 'error message', 'piece_content': '------STARTING: Migrate Database------\\nTraceback (most recent call last):\\nFile "manage.py", line 27, in <module>\\nexecute_from_command_line(sys.argv)\\nFile "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_... | ------STARTING: Migrate Database------
Traceback (most recent call last):
File "manage.py", line 27, in <module>
execute_from_command_line(sys.argv)
File "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_command_line
utility.execute()
File "/cache/.bk/env/lib/pyt... | ImportError |
def cc_search_object_attribute(request, obj_id, biz_cc_id, supplier_account):
"""
@summary: 获取对象自定义属性
@param request:
@param biz_cc_id:
@return:
"""
client = get_client_by_user(request.user.username)
kwargs = {
'bk_obj_id': obj_id,
'bk_supplier_account': supplier_account
... | def cc_search_object_attribute(request, obj_id, biz_cc_id, supplier_account):
"""
@summary: 获取对象自定义属性
@param request:
@param biz_cc_id:
@return:
"""
client = get_client_by_request(request)
kwargs = {
'bk_obj_id': obj_id,
'bk_supplier_account': supplier_account
}
c... | [{'piece_type': 'error message', 'piece_content': '------STARTING: Migrate Database------\\nTraceback (most recent call last):\\nFile "manage.py", line 27, in <module>\\nexecute_from_command_line(sys.argv)\\nFile "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_... | ------STARTING: Migrate Database------
Traceback (most recent call last):
File "manage.py", line 27, in <module>
execute_from_command_line(sys.argv)
File "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_command_line
utility.execute()
File "/cache/.bk/env/lib/pyt... | ImportError |
def cc_search_create_object_attribute(request, obj_id, biz_cc_id, supplier_account):
client = get_client_by_user(request.user.username)
kwargs = {
'bk_obj_id': obj_id,
'bk_supplier_account': supplier_account
}
cc_result = client.cc.search_object_attribute(kwargs)
if not cc_result['re... | def cc_search_create_object_attribute(request, obj_id, biz_cc_id, supplier_account):
client = get_client_by_request(request)
kwargs = {
'bk_obj_id': obj_id,
'bk_supplier_account': supplier_account
}
cc_result = client.cc.search_object_attribute(kwargs)
if not cc_result['result']:
... | [{'piece_type': 'error message', 'piece_content': '------STARTING: Migrate Database------\\nTraceback (most recent call last):\\nFile "manage.py", line 27, in <module>\\nexecute_from_command_line(sys.argv)\\nFile "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_... | ------STARTING: Migrate Database------
Traceback (most recent call last):
File "manage.py", line 27, in <module>
execute_from_command_line(sys.argv)
File "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_command_line
utility.execute()
File "/cache/.bk/env/lib/pyt... | ImportError |
def cc_search_topo(request, obj_id, category, biz_cc_id, supplier_account):
"""
@summary: 查询对象拓扑
@param request:
@param biz_cc_id:
@return:
"""
client = get_client_by_user(request.user.username)
kwargs = {
'bk_biz_id': biz_cc_id,
'bk_supplier_account': supplier_account
... | def cc_search_topo(request, obj_id, category, biz_cc_id, supplier_account):
"""
@summary: 查询对象拓扑
@param request:
@param biz_cc_id:
@return:
"""
client = get_client_by_request(request)
kwargs = {
'bk_biz_id': biz_cc_id,
'bk_supplier_account': supplier_account
}
cc_... | [{'piece_type': 'error message', 'piece_content': '------STARTING: Migrate Database------\\nTraceback (most recent call last):\\nFile "manage.py", line 27, in <module>\\nexecute_from_command_line(sys.argv)\\nFile "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_... | ------STARTING: Migrate Database------
Traceback (most recent call last):
File "manage.py", line 27, in <module>
execute_from_command_line(sys.argv)
File "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_command_line
utility.execute()
File "/cache/.bk/env/lib/pyt... | ImportError |
def job_get_script_list(request, biz_cc_id):
"""
查询业务脚本列表
:param request:
:param biz_cc_id:
:return:
"""
# 查询脚本列表
client = get_client_by_user(request.user.username)
script_type = request.GET.get('type')
kwargs = {
'bk_biz_id': biz_cc_id,
'is_public': True if scrip... | def job_get_script_list(request, biz_cc_id):
"""
查询业务脚本列表
:param request:
:param biz_cc_id:
:return:
"""
# 查询脚本列表
client = get_client_by_request(request)
script_type = request.GET.get('type')
kwargs = {
'bk_biz_id': biz_cc_id,
'is_public': True if script_type == '... | [{'piece_type': 'error message', 'piece_content': '------STARTING: Migrate Database------\\nTraceback (most recent call last):\\nFile "manage.py", line 27, in <module>\\nexecute_from_command_line(sys.argv)\\nFile "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_... | ------STARTING: Migrate Database------
Traceback (most recent call last):
File "manage.py", line 27, in <module>
execute_from_command_line(sys.argv)
File "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_command_line
utility.execute()
File "/cache/.bk/env/lib/pyt... | ImportError |
def job_get_job_tasks_by_biz(request, biz_cc_id):
client = get_client_by_user(request.user.username)
job_result = client.job.get_job_list({'bk_biz_id': biz_cc_id})
if not job_result['result']:
message = _(u"查询作业平台(JOB)的作业模板[app_id=%s]接口job.get_task返回失败: %s") % (
biz_cc_id, job_result['me... | def job_get_job_tasks_by_biz(request, biz_cc_id):
client = get_client_by_request(request)
job_result = client.job.get_job_list({'bk_biz_id': biz_cc_id})
if not job_result['result']:
message = _(u"查询作业平台(JOB)的作业模板[app_id=%s]接口job.get_task返回失败: %s") % (
biz_cc_id, job_result['message'])
... | [{'piece_type': 'error message', 'piece_content': '------STARTING: Migrate Database------\\nTraceback (most recent call last):\\nFile "manage.py", line 27, in <module>\\nexecute_from_command_line(sys.argv)\\nFile "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_... | ------STARTING: Migrate Database------
Traceback (most recent call last):
File "manage.py", line 27, in <module>
execute_from_command_line(sys.argv)
File "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_command_line
utility.execute()
File "/cache/.bk/env/lib/pyt... | ImportError |
def job_get_job_task_detail(request, biz_cc_id, task_id):
client = get_client_by_user(request.user.username)
job_result = client.job.get_job_detail({'bk_biz_id': biz_cc_id,
'bk_job_id': task_id})
if not job_result['result']:
message = _(u"查询作业平台(JOB)的作业模板详... | def job_get_job_task_detail(request, biz_cc_id, task_id):
client = get_client_by_request(request)
job_result = client.job.get_job_detail({'bk_biz_id': biz_cc_id,
'bk_job_id': task_id})
if not job_result['result']:
message = _(u"查询作业平台(JOB)的作业模板详情[app_id=%s... | [{'piece_type': 'error message', 'piece_content': '------STARTING: Migrate Database------\\nTraceback (most recent call last):\\nFile "manage.py", line 27, in <module>\\nexecute_from_command_line(sys.argv)\\nFile "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_... | ------STARTING: Migrate Database------
Traceback (most recent call last):
File "manage.py", line 27, in <module>
execute_from_command_line(sys.argv)
File "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_command_line
utility.execute()
File "/cache/.bk/env/lib/pyt... | ImportError |
def get_bk_user(request):
bkuser = None
if request.weixin_user and not isinstance(request.weixin_user, AnonymousUser):
user_model = get_user_model()
try:
user_property = UserProperty.objects.get(key='wx_userid', value=request.weixin_user.userid)
except UserProperty.DoesNotExi... | def get_bk_user(request):
bkuser = None
if request.weixin_user and not isinstance(request.weixin_user, AnonymousUser):
try:
user_property = UserProperty.objects.get(key='wx_userid', value=request.weixin_user.userid)
bkuser = user_property.user
except UserProperty.DoesNotE... | [{'piece_type': 'error message', 'piece_content': '------STARTING: Migrate Database------\\nTraceback (most recent call last):\\nFile "manage.py", line 27, in <module>\\nexecute_from_command_line(sys.argv)\\nFile "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_... | ------STARTING: Migrate Database------
Traceback (most recent call last):
File "manage.py", line 27, in <module>
execute_from_command_line(sys.argv)
File "/cache/.bk/env/lib/python2.7/site-packages/django/core/management/__init__.py", line 354, in execute_from_command_line
utility.execute()
File "/cache/.bk/env/lib/pyt... | ImportError |
def fit(self, dataset: Dataset):
"""Calculates statistics for this workflow on the input dataset
Parameters
-----------
dataset: Dataset
The input dataset to calculate statistics for. If there is a train/test split this
data should be the training dataset onl... | def fit(self, dataset: Dataset):
"""Calculates statistics for this workflow on the input dataset
Parameters
-----------
dataset: Dataset
The input dataset to calculate statistics for. If there is a train/test split this
data should be the training dataset onl... | [{'piece_type': 'error message', 'piece_content': 'E0224 15:58:10.330248 178 model_repository_manager.cc:963] failed to load \\'amazonreview_tf\\' version 1: Internal: unable to create stream: the provided PTX was compiled with an unsupported toolchain.\\n/nvtabular/nvtabular/workflow.py:236: UserWarning: Loading workf... | E0224 15:58:10.330248 178 model_repository_manager.cc:963] failed to load 'amazonreview_tf' version 1: Internal: unable to create stream: the provided PTX was compiled with an unsupported toolchain.
/nvtabular/nvtabular/workflow.py:236: UserWarning: Loading workflow generated with cudf version 0+untagged.1.gbd321d1 - b... | TypeError |
def main(args):
"""Multi-GPU Criteo/DLRM Preprocessing Benchmark
This benchmark is designed to measure the time required to preprocess
the Criteo (1TB) dataset for Facebook’s DLRM model. The user must specify
the path of the raw dataset (using the `--data-path` flag), as well as the
output directo... | def main(args):
"""Multi-GPU Criteo/DLRM Preprocessing Benchmark
This benchmark is designed to measure the time required to preprocess
the Criteo (1TB) dataset for Facebook’s DLRM model. The user must specify
the path of the raw dataset (using the `--data-path` flag), as well as the
output directo... | [{'piece_type': 'error message', 'piece_content': '(rapids) root@dafff4b22f48:/nvtabular# python examples/dask-nvtabular-criteo-benchmark.py -d 0,1,2,3,4,5,6,7 --data-path gs://merlin-datasets/crit_int_pq --out-path gs://merlin-datasets/output --freq-limit 0 --part-mem-frac 0.12 --device-limit-f\\nrac 0.7 --device-poo... | (rapids) root@dafff4b22f48:/nvtabular# python examples/dask-nvtabular-criteo-benchmark.py -d 0,1,2,3,4,5,6,7 --data-path gs://merlin-datasets/crit_int_pq --out-path gs://merlin-datasets/output --freq-limit 0 --part-mem-frac 0.12 --device-limit-f
rac 0.7 --device-pool-frac 0.8
distributed.worker - WARNING - Compute Fa... | FileNotFoundError |
def __init__(self, out_dir, **kwargs):
super().__init__(out_dir, **kwargs)
self.data_paths = []
self.data_files = []
self.data_writers = []
self.data_bios = []
self._lock = threading.RLock()
self.pwriter = self._pwriter
self.pwriter_kwargs = {} | def __init__(self, out_dir, **kwargs):
super().__init__(out_dir, **kwargs)
self.data_paths = []
self.data_writers = []
self.data_bios = []
self._lock = threading.RLock()
self.pwriter = self._pwriter
self.pwriter_kwargs = {} | [{'piece_type': 'error message', 'piece_content': '(rapids) root@dafff4b22f48:/nvtabular# python examples/dask-nvtabular-criteo-benchmark.py -d 0,1,2,3,4,5,6,7 --data-path gs://merlin-datasets/crit_int_pq --out-path gs://merlin-datasets/output --freq-limit 0 --part-mem-frac 0.12 --device-limit-f\\nrac 0.7 --device-poo... | (rapids) root@dafff4b22f48:/nvtabular# python examples/dask-nvtabular-criteo-benchmark.py -d 0,1,2,3,4,5,6,7 --data-path gs://merlin-datasets/crit_int_pq --out-path gs://merlin-datasets/output --freq-limit 0 --part-mem-frac 0.12 --device-limit-f
rac 0.7 --device-pool-frac 0.8
distributed.worker - WARNING - Compute Fa... | FileNotFoundError |
def _append_writer(self, path, schema=None, add_args=None, add_kwargs=None):
# Add additional args and kwargs
_args = add_args or []
_kwargs = tlz.merge(self.pwriter_kwargs, add_kwargs or {})
if self.bytes_io:
bio = BytesIO()
self.data_bios.append(bio)
... | def _append_writer(self, path, schema=None, add_args=None, add_kwargs=None):
# Add additional args and kwargs
_args = add_args or []
_kwargs = tlz.merge(self.pwriter_kwargs, add_kwargs or {})
if self.bytes_io:
bio = BytesIO()
self.data_bios.append(bio)
... | [{'piece_type': 'error message', 'piece_content': '(rapids) root@dafff4b22f48:/nvtabular# python examples/dask-nvtabular-criteo-benchmark.py -d 0,1,2,3,4,5,6,7 --data-path gs://merlin-datasets/crit_int_pq --out-path gs://merlin-datasets/output --freq-limit 0 --part-mem-frac 0.12 --device-limit-f\\nrac 0.7 --device-poo... | (rapids) root@dafff4b22f48:/nvtabular# python examples/dask-nvtabular-criteo-benchmark.py -d 0,1,2,3,4,5,6,7 --data-path gs://merlin-datasets/crit_int_pq --out-path gs://merlin-datasets/output --freq-limit 0 --part-mem-frac 0.12 --device-limit-f
rac 0.7 --device-pool-frac 0.8
distributed.worker - WARNING - Compute Fa... | FileNotFoundError |
def _close_writers(self):
md_dict = {}
for writer, path in zip(self.data_writers, self.data_paths):
fn = path.split(self.fs.sep)[-1]
md_dict[fn] = writer.close(metadata_file_path=fn)
for f in self.data_files:
f.close()
return md_dict | def _close_writers(self):
md_dict = {}
for writer, path in zip(self.data_writers, self.data_paths):
fn = path.split(self.fs.sep)[-1]
md_dict[fn] = writer.close(metadata_file_path=fn)
return md_dict | [{'piece_type': 'error message', 'piece_content': '(rapids) root@dafff4b22f48:/nvtabular# python examples/dask-nvtabular-criteo-benchmark.py -d 0,1,2,3,4,5,6,7 --data-path gs://merlin-datasets/crit_int_pq --out-path gs://merlin-datasets/output --freq-limit 0 --part-mem-frac 0.12 --device-limit-f\\nrac 0.7 --device-poo... | (rapids) root@dafff4b22f48:/nvtabular# python examples/dask-nvtabular-criteo-benchmark.py -d 0,1,2,3,4,5,6,7 --data-path gs://merlin-datasets/crit_int_pq --out-path gs://merlin-datasets/output --freq-limit 0 --part-mem-frac 0.12 --device-limit-f
rac 0.7 --device-pool-frac 0.8
distributed.worker - WARNING - Compute Fa... | FileNotFoundError |
def fetch_table_data(
table_cache, path, cache="disk", cats_only=False, reader=None, columns=None, **kwargs
):
"""Utility to retrieve a cudf DataFrame from a cache (and add the
DataFrame to a cache if the element is missing). Note that `cats_only=True`
results in optimized logic for the `Categorify` tr... | def fetch_table_data(
table_cache, path, cache="disk", cats_only=False, reader=None, columns=None, **kwargs
):
"""Utility to retrieve a cudf DataFrame from a cache (and add the
DataFrame to a cache if the element is missing). Note that `cats_only=True`
results in optimized logic for the `Categorify` tr... | [{'piece_type': 'error message', 'piece_content': '(rapids) root@dafff4b22f48:/nvtabular# python examples/dask-nvtabular-criteo-benchmark.py -d 0,1,2,3,4,5,6,7 --data-path gs://merlin-datasets/crit_int_pq --out-path gs://merlin-datasets/output --freq-limit 0 --part-mem-frac 0.12 --device-limit-f\\nrac 0.7 --device-poo... | (rapids) root@dafff4b22f48:/nvtabular# python examples/dask-nvtabular-criteo-benchmark.py -d 0,1,2,3,4,5,6,7 --data-path gs://merlin-datasets/crit_int_pq --out-path gs://merlin-datasets/output --freq-limit 0 --part-mem-frac 0.12 --device-limit-f
rac 0.7 --device-pool-frac 0.8
distributed.worker - WARNING - Compute Fa... | FileNotFoundError |
def _chunkwise_moments(df):
df2 = cudf.DataFrame()
for col in df.columns:
df2[col] = df[col].astype("float64").pow(2)
vals = {
"df-count": df.count().to_frame().transpose(),
"df-sum": df.sum().astype("float64").to_frame().transpose(),
"df2-sum": df2.sum().to_frame().transpose... | def _chunkwise_moments(df):
df2 = cudf.DataFrame()
for col in df.columns:
df2[col] = df[col].astype("float64").pow(2)
vals = {
"df-count": df.count().to_frame().transpose(),
"df-sum": df.sum().to_frame().transpose(),
"df2-sum": df2.sum().to_frame().transpose(),
}
# NO... | [{'piece_type': 'error message', 'piece_content': '/opt/conda/envs/rapids/lib/python3.7/site-packages/pandas/core/series.py:726: RuntimeWarning: invalid value encountered in sqrt\\nresult = getattr(ufunc, method)(*inputs, **kwargs)\\n---------------------------------------------------------------------------\\nValueErr... | /opt/conda/envs/rapids/lib/python3.7/site-packages/pandas/core/series.py:726: RuntimeWarning: invalid value encountered in sqrt
result = getattr(ufunc, method)(*inputs, **kwargs)
---------------------------------------------------------------------------
ValueError Traceback (most recent ... | ValueError |
def to_ddf(self, columns=None):
return dask_cudf.read_parquet(
self.paths,
columns=columns,
# can't omit reading the index in if we aren't being passed columns
index=None if columns is None else False,
gather_statistics=False,
split_row... | def to_ddf(self, columns=None):
return dask_cudf.read_parquet(
self.paths,
columns=columns,
index=False,
gather_statistics=False,
split_row_groups=self.row_groups_per_part,
storage_options=self.storage_options,
) | [{'piece_type': 'error message', 'piece_content': '---------------------------------------------------------------------------\\nValueError Traceback (most recent call last)\\n<ipython-input-13-b133e2b51cbf> in <module>\\n2 valid_dataset = nvt.Dataset(OUTPUT_BUCKET_FOLDER+\\'valid_gdf.par... | ---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-13-b133e2b51cbf> in <module>
2 valid_dataset = nvt.Dataset(OUTPUT_BUCKET_FOLDER+'valid_gdf.parquet', part_mem_fraction=0.12)
3
----> 4 workflow.apply(tra... | ValueError |
def get_ddf(self):
if self.ddf is None:
raise ValueError("No dask_cudf frame available.")
elif isinstance(self.ddf, Dataset):
# Right now we can't distinguish between input columns and generated columns
# in the dataset, we don't limit the columm set right now in ... | def get_ddf(self):
if self.ddf is None:
raise ValueError("No dask_cudf frame available.")
elif isinstance(self.ddf, Dataset):
columns = self.columns_ctx["all"]["base"]
return self.ddf.to_ddf(columns=columns, shuffle=self._shuffle_parts)
return self.ddf | [{'piece_type': 'error message', 'piece_content': '---------------------------------------------------------------------------\\nValueError Traceback (most recent call last)\\n<ipython-input-13-b133e2b51cbf> in <module>\\n2 valid_dataset = nvt.Dataset(OUTPUT_BUCKET_FOLDER+\\'valid_gdf.par... | ---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-13-b133e2b51cbf> in <module>
2 valid_dataset = nvt.Dataset(OUTPUT_BUCKET_FOLDER+'valid_gdf.parquet', part_mem_fraction=0.12)
3
----> 4 workflow.apply(tra... | ValueError |
def add_data(self, gdf):
# Populate columns idxs
if not self.col_idx:
for i, x in enumerate(gdf.columns.values):
self.col_idx[str(x)] = i
# list columns in cudf don't currently support chunked writing in parquet.
# hack around this by just writing a singl... | def add_data(self, gdf):
# Populate columns idxs
if not self.col_idx:
for i, x in enumerate(gdf.columns.values):
self.col_idx[str(x)] = i
# list columns in cudf don't currently support chunked writing in parquet.
# hack around this by just writing a singl... | [{'piece_type': 'other', 'piece_content': "df = cudf.DataFrame({'doc_id': [1, 1, 2, 2, 3, 3, 4, 4], 'category_id': [1, 2, 3, 3, 5, 6, 6, 1], 'confidence_level': [0.92, 0.251, 0.352, 0.359, 0.978, 0.988, 0.978, 0.988]})\\n\\ndf_grouped = df.groupby('doc_id', as_index=False).agg({'category_id': ['collect'], 'confidence_l... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-19-f93c44c3b381> in <module>
11 proc.add_preprocess(JoinExternal(df_grouped, on= ['doc_id'], on_ext= ['doc_id'], kind_ext=kind_ext, columns_ext=columns_e... | AttributeError |
def __init__(
self,
paths,
part_size,
storage_options,
row_groups_per_part=None,
legacy=False,
batch_size=None,
):
# TODO: Improve dask_cudf.read_parquet performance so that
# this class can be slimmed down.
super().__init__(paths, ... | def __init__(
self,
paths,
part_size,
storage_options,
row_groups_per_part=None,
legacy=False,
batch_size=None,
):
# TODO: Improve dask_cudf.read_parquet performance so that
# this class can be slimmed down.
super().__init__(paths, ... | [{'piece_type': 'other', 'piece_content': 'python dataloader_bench.py torch <PATH TO Folder with Parquet Files on local> parquet 0.2'}, {'piece_type': 'error message', 'piece_content': 'Traceback (most recent call last):\\nFile "main.py", line 106, in <module>\\nmain(args)\\nFile "main.py", line 61, in main\\ntrain_pat... | Traceback (most recent call last):
File "main.py", line 106, in <module>
main(args)
File "main.py", line 61, in main
train_paths, engine="parquet", part_mem_fraction=float(args.gpu_mem_frac)
File "/root/miniconda/lib/python3.7/site-packages/nvtabular/io/dataset.py", line 224, in __init__
paths, part_size, storage_optio... | AttributeError |
def __init__(self, *args, **kwargs):
super().__init__(*args)
self._meta = {}
self.csv_kwargs = kwargs
self.names = self.csv_kwargs.get("names", None)
# CSV reader needs a list of files
# (Assume flat directory structure if this is a dir)
if len(self.paths) == ... | def __init__(self, *args, **kwargs):
super().__init__(*args)
self._meta = {}
self.names = kwargs.pop("names", None)
self.csv_kwargs = kwargs
# CSV reader needs a list of files
# (Assume flat directory structure if this is a dir)
if len(self.paths) == 1 and sel... | [{'piece_type': 'error message', 'piece_content': "AttributeErrorTraceback (most recent call last)\\n<ipython-input-1-84910288ec3f> in <module>\\n44 del gdf\\n45 path_out = '/raid/criteo/tests/jp_csv_orig/'\\n---> 46 file_to_pq(train_set, 'csv', output_folder=path_out, cols=cols, dtypes=dtypes)\\n\\n<ipython-in... | AttributeErrorTraceback (most recent call last)
<ipython-input-1-84910288ec3f> in <module>
44 del gdf
45 path_out = '/raid/criteo/tests/jp_csv_orig/'
---> 46 file_to_pq(train_set, 'csv', output_folder=path_out, cols=cols, dtypes=dtypes)
<ipython-input-1-84910288ec3f> in file_to_pq(target_files, file_type, outp... | AttributeError |
def to_ddf(self, columns=None):
return dask_cudf.read_csv(self.paths, chunksize=self.part_size, **self.csv_kwargs)[columns] | def to_ddf(self, columns=None):
return dask_cudf.read_csv(
self.paths, names=self.names, chunksize=self.part_size, **self.csv_kwargs
)[columns] | [{'piece_type': 'error message', 'piece_content': "AttributeErrorTraceback (most recent call last)\\n<ipython-input-1-84910288ec3f> in <module>\\n44 del gdf\\n45 path_out = '/raid/criteo/tests/jp_csv_orig/'\\n---> 46 file_to_pq(train_set, 'csv', output_folder=path_out, cols=cols, dtypes=dtypes)\\n\\n<ipython-in... | AttributeErrorTraceback (most recent call last)
<ipython-input-1-84910288ec3f> in <module>
44 del gdf
45 path_out = '/raid/criteo/tests/jp_csv_orig/'
---> 46 file_to_pq(train_set, 'csv', output_folder=path_out, cols=cols, dtypes=dtypes)
<ipython-input-1-84910288ec3f> in file_to_pq(target_files, file_type, outp... | AttributeError |
def _predict(self, X):
"""Collect results from clf.predict calls."""
if self.refit:
return np.asarray([clf.predict(X) for clf in self.clfs_]).T
else:
return np.asarray([self.le_.transform(clf.predict(X))
for clf in self.clfs_]).T | def _predict(self, X):
"""Collect results from clf.predict calls."""
return np.asarray([clf.predict(X) for clf in self.clfs_]).T | [{'piece_type': 'reproducing source code', 'piece_content': "import numpy as np\\nfrom sklearn.ensemble import RandomForestClassifier\\nfrom mlxtend.classifier import EnsembleVoteClassifier\\n\\ndata = np.array([0, 1, 2, 3, 0, 1, 2, 3])[:, np.newaxis]\\nlabels = ['a', 'b', 'c', 'd', 'a', 'b', 'c', 'd']\\n\\ntest = np.a... | Traceback (most recent call last):
File "/_mlxtend_bug/reproduce.py", line 16, in <module>
print(clf.predict(test))
File "/venv/py3/lib/python3.4/site-packages/mlxtend/classifier/ensemble_vote.py", line 197, in predict
arr=predictions)
File "/venv/py3/lib/python3.4/site-packages/numpy/lib/shape_base.py", line 132, in a... | TypeError |
def transform(
self,
xx: Any,
yy: Any,
zz: Any = None,
tt: Any = None,
radians: bool = False,
errcheck: bool = False,
direction: Union[TransformDirection, str] = TransformDirection.FORWARD,
) -> Any:
"""
Transform points between two... | def transform(
self,
xx: Any,
yy: Any,
zz: Any = None,
tt: Any = None,
radians: bool = False,
errcheck: bool = False,
direction: Union[TransformDirection, str] = TransformDirection.FORWARD,
) -> Any:
"""
Transform points between two... | [{'piece_type': 'other', 'piece_content': 'echo 50 25 0 | cct +proj=pipeline +ellps=GRS80 +step +proj=cart'}, {'piece_type': 'other', 'piece_content': '3717892.6072 4430811.8715 2679074.4629 inf'}, {'piece_type': 'source code', 'piece_content': 'from pyproj import Transformer\\n\\nstring = "+proj=pipeline ... | Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.7/site-packages/pyproj/transformer.py", line 446, in transform
errcheck=errcheck,
File "pyproj/_transformer.pyx", line 463, in pyproj._transformer._Transformer._transform
pyproj.exceptions.ProjError: transform error: lat... | pyproj.exceptions.ProjError |
def itransform(
self,
points: Any,
switch: bool = False,
time_3rd: bool = False,
radians: bool = False,
errcheck: bool = False,
direction: Union[TransformDirection, str] = TransformDirection.FORWARD,
) -> Iterator[Iterable]:
"""
Iterator/ge... | def itransform(
self,
points: Any,
switch: bool = False,
time_3rd: bool = False,
radians: bool = False,
errcheck: bool = False,
direction: Union[TransformDirection, str] = TransformDirection.FORWARD,
) -> Iterator[Iterable]:
"""
Iterator/ge... | [{'piece_type': 'other', 'piece_content': 'echo 50 25 0 | cct +proj=pipeline +ellps=GRS80 +step +proj=cart'}, {'piece_type': 'other', 'piece_content': '3717892.6072 4430811.8715 2679074.4629 inf'}, {'piece_type': 'source code', 'piece_content': 'from pyproj import Transformer\\n\\nstring = "+proj=pipeline ... | Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.7/site-packages/pyproj/transformer.py", line 446, in transform
errcheck=errcheck,
File "pyproj/_transformer.pyx", line 463, in pyproj._transformer._Transformer._transform
pyproj.exceptions.ProjError: transform error: lat... | pyproj.exceptions.ProjError |
def from_user_input(value: Any) -> "CRS":
"""
Initialize a CRS class instance with:
- PROJ string
- Dictionary of PROJ parameters
- PROJ keyword arguments for parameters
- JSON string with PROJ parameters
- CRS WKT string
- An authority str... | def from_user_input(value: str) -> "CRS":
"""
Initialize a CRS class instance with:
- PROJ string
- Dictionary of PROJ parameters
- PROJ keyword arguments for parameters
- JSON string with PROJ parameters
- CRS WKT string
- An authority str... | [{'piece_type': 'error message', 'piece_content': 'import pyproj\\n\\n---------------------------------------------------------------------------\\nKeyError Traceback (most recent call last)\\n~/scipy/repos/pyproj/pyproj/_crs.pyx in pyproj._crs.Datum.from_name()\\n\\nKeyError: \\'URN:OG... | import pyproj
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
~/scipy/repos/pyproj/pyproj/_crs.pyx in pyproj._crs.Datum.from_name()
KeyError: 'URN:OGC:DEF:DATUM:EPSG::6326'
During handling of the above exception, ... | KeyError |
def __init__(
self,
name: str = "undefined",
datum: Any = "urn:ogc:def:datum:EPSG::6326",
ellipsoidal_cs: Any = None,
) -> None:
"""
Parameters
----------
name: str, optional
Name of the CRS. Default is undefined.
datum: Any, op... | def __init__(
self,
name: str = "undefined",
datum: Any = "urn:ogc:def:datum:EPSG::6326",
ellipsoidal_cs: Any = Ellipsoidal2DCS(),
) -> None:
"""
Parameters
----------
name: str, optional
Name of the CRS. Default is undefined.
d... | [{'piece_type': 'error message', 'piece_content': 'import pyproj\\n\\n---------------------------------------------------------------------------\\nKeyError Traceback (most recent call last)\\n~/scipy/repos/pyproj/pyproj/_crs.pyx in pyproj._crs.Datum.from_name()\\n\\nKeyError: \\'URN:OG... | import pyproj
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
~/scipy/repos/pyproj/pyproj/_crs.pyx in pyproj._crs.Datum.from_name()
KeyError: 'URN:OGC:DEF:DATUM:EPSG::6326'
During handling of the above exception, ... | KeyError |
def __init__(
self,
base_crs: Any,
conversion: Any,
ellipsoidal_cs: Any = None,
name: str = "undefined",
) -> None:
"""
Parameters
----------
base_crs: Any
Input to create the Geodetic CRS, a :class:`GeographicCRS` or
... | def __init__(
self,
base_crs: Any,
conversion: Any,
ellipsoidal_cs: Any = Ellipsoidal2DCS(),
name: str = "undefined",
) -> None:
"""
Parameters
----------
base_crs: Any
Input to create the Geodetic CRS, a :class:`GeographicCRS` ... | [{'piece_type': 'error message', 'piece_content': 'import pyproj\\n\\n---------------------------------------------------------------------------\\nKeyError Traceback (most recent call last)\\n~/scipy/repos/pyproj/pyproj/_crs.pyx in pyproj._crs.Datum.from_name()\\n\\nKeyError: \\'URN:OG... | import pyproj
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
~/scipy/repos/pyproj/pyproj/_crs.pyx in pyproj._crs.Datum.from_name()
KeyError: 'URN:OGC:DEF:DATUM:EPSG::6326'
During handling of the above exception, ... | KeyError |
def __init__(
self,
conversion: Any,
name: str = "undefined",
cartesian_cs: Any = None,
geodetic_crs: Any = None,
) -> None:
"""
Parameters
----------
conversion: Any
Anything accepted by :meth:`pyproj.crs.CoordinateSystem.from_... | def __init__(
self,
conversion: Any,
name: str = "undefined",
cartesian_cs: Any = Cartesian2DCS(),
geodetic_crs: Any = GeographicCRS(),
) -> None:
"""
Parameters
----------
conversion: Any
Anything accepted by :meth:`pyproj.crs.... | [{'piece_type': 'error message', 'piece_content': 'import pyproj\\n\\n---------------------------------------------------------------------------\\nKeyError Traceback (most recent call last)\\n~/scipy/repos/pyproj/pyproj/_crs.pyx in pyproj._crs.Datum.from_name()\\n\\nKeyError: \\'URN:OG... | import pyproj
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
~/scipy/repos/pyproj/pyproj/_crs.pyx in pyproj._crs.Datum.from_name()
KeyError: 'URN:OGC:DEF:DATUM:EPSG::6326'
During handling of the above exception, ... | KeyError |
def __init__(
self,
name: str,
datum: Any,
vertical_cs: Any = None,
geoid_model: Optional[str] = None,
) -> None:
"""
Parameters
----------
name: str
The name of the Vertical CRS (e.g. NAVD88 height).
datum: Any
... | def __init__(
self,
name: str,
datum: Any,
vertical_cs: Any = VerticalCS(),
geoid_model: str = None,
) -> None:
"""
Parameters
----------
name: str
The name of the Vertical CRS (e.g. NAVD88 height).
datum: Any
... | [{'piece_type': 'error message', 'piece_content': 'import pyproj\\n\\n---------------------------------------------------------------------------\\nKeyError Traceback (most recent call last)\\n~/scipy/repos/pyproj/pyproj/_crs.pyx in pyproj._crs.Datum.from_name()\\n\\nKeyError: \\'URN:OG... | import pyproj
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
~/scipy/repos/pyproj/pyproj/_crs.pyx in pyproj._crs.Datum.from_name()
KeyError: 'URN:OGC:DEF:DATUM:EPSG::6326'
During handling of the above exception, ... | KeyError |
def set_data_dir(proj_data_dir):
"""
Set the data directory for PROJ to use.
Parameters
----------
proj_data_dir: str
The path to rhe PROJ data directory.
"""
global _USER_PROJ_DATA
_USER_PROJ_DATA = proj_data_dir
# reset search paths
from pyproj._datadir import PYPROJ_C... | def set_data_dir(proj_data_dir):
"""
Set the data directory for PROJ to use.
Parameters
----------
proj_data_dir: str
The path to rhe PROJ data directory.
"""
global _USER_PROJ_DATA
_USER_PROJ_DATA = proj_data_dir
# reset search paths
from pyproj._datadir import PYPROJ_C... | [{'piece_type': 'other', 'piece_content': 'Fatal Python error: Segmentation fault\\n\\nCurrent thread 0x00007fa0f79c4700 (most recent call first):\\nFile "/opt/conda/lib/python3.7/site-packages/pyproj/crs.py", line 303 in __init__\\nFile "/opt/conda/lib/python3.7/site-packages/pyproj/crs.py", line 434 in from_user_inpu... | Traceback (most recent call last):
File "<stdin>", line 1, in <module>
...
File "/opt/conda/lib/python3.7/site-packages/geopandas/geodataframe.py", line 459, in to_crs
geom = df.geometry.to_crs(crs=crs, epsg=epsg)
File "/opt/conda/lib/python3.7/site-packages/geopandas/geoseries.py", line 304, in to_crs
proj_in = pyproj... | pyproj.exceptions.DataDirError |
def set_data_dir(proj_data_dir):
"""
Set the data directory for PROJ to use.
Parameters
----------
proj_data_dir: str
The path to rhe PROJ data directory.
"""
global _USER_PROJ_DATA
_USER_PROJ_DATA = proj_data_dir
# reset search paths
from pyproj._datadir import PYPROJ_C... | def set_data_dir(proj_data_dir):
"""
Set the data directory for PROJ to use.
Parameters
----------
proj_data_dir: str
The path to rhe PROJ data directory.
"""
global _USER_PROJ_DATA
global _VALIDATED_PROJ_DATA
_USER_PROJ_DATA = proj_data_dir
# set to none to re-validate
... | [{'piece_type': 'error message', 'piece_content': '97%|█████████████████████████████████▊ | 88243/91210 [00:26<00:00, 6190.94it/s]\\nCRSs instantiated: 507\\nCRSs instantiated (cache hits included): 88603\\nTransformers instantiated: 502\\nTransformers instantiated (cache hits included): 88389\\n-----------------------... | 97%|█████████████████████████████████▊ | 88243/91210 [00:26<00:00, 6190.94it/s]
CRSs instantiated: 507
CRSs instantiated (cache hits included): 88603
Transformers instantiated: 502
Transformers instantiated (cache hits included): 88389
---------------------------------------------------------------------------
ProjErro... | ProjError |
def get_data_dir():
"""
The order of preference for the data directory is:
1. The one set by pyproj.datadir.set_data_dir (if exists & valid)
2. The internal proj directory (if exists & valid)
3. The directory in PROJ_LIB (if exists & valid)
4. The directory on the PATH (if exists & valid)
... | def get_data_dir():
"""
The order of preference for the data directory is:
1. The one set by pyproj.datadir.set_data_dir (if exists & valid)
2. The internal proj directory (if exists & valid)
3. The directory in PROJ_LIB (if exists & valid)
4. The directory on the PATH (if exists & valid)
... | [{'piece_type': 'error message', 'piece_content': '97%|█████████████████████████████████▊ | 88243/91210 [00:26<00:00, 6190.94it/s]\\nCRSs instantiated: 507\\nCRSs instantiated (cache hits included): 88603\\nTransformers instantiated: 502\\nTransformers instantiated (cache hits included): 88389\\n-----------------------... | 97%|█████████████████████████████████▊ | 88243/91210 [00:26<00:00, 6190.94it/s]
CRSs instantiated: 507
CRSs instantiated (cache hits included): 88603
Transformers instantiated: 502
Transformers instantiated (cache hits included): 88389
---------------------------------------------------------------------------
ProjErro... | ProjError |
def from_proj(proj_from, proj_to, skip_equivalent=False, always_xy=False):
"""Make a Transformer from a :obj:`~pyproj.proj.Proj` or input used to create one.
Parameters
----------
proj_from: :obj:`~pyproj.proj.Proj` or input used to create one
Projection of input data.
... | def from_proj(proj_from, proj_to, skip_equivalent=False, always_xy=False):
"""Make a Transformer from a :obj:`~pyproj.proj.Proj` or input used to create one.
Parameters
----------
proj_from: :obj:`~pyproj.proj.Proj` or input used to create one
Projection of input data.
... | [{'piece_type': 'error message', 'piece_content': "In [4]: t = pyproj.Transformer()\\n\\nIn [5]: t\\nOut[5]: <pyproj.transformer.Transformer at 0x7fd75ff9b860>\\n\\nIn [6]: t.transform(0, 0)\\n---------------------------------------------------------------------------\\nAttributeError Traceba... | In [4]: t = pyproj.Transformer()
In [5]: t
Out[5]: <pyproj.transformer.Transformer at 0x7fd75ff9b860>
In [6]: t.transform(0, 0)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-6-65405fa99360> in <mod... | AttributeError |
def from_crs(crs_from, crs_to, skip_equivalent=False, always_xy=False):
"""Make a Transformer from a :obj:`~pyproj.crs.CRS` or input used to create one.
Parameters
----------
crs_from: ~pyproj.crs.CRS or input used to create one
Projection of input data.
crs_to: ... | def from_crs(crs_from, crs_to, skip_equivalent=False, always_xy=False):
"""Make a Transformer from a :obj:`~pyproj.crs.CRS` or input used to create one.
Parameters
----------
crs_from: ~pyproj.crs.CRS or input used to create one
Projection of input data.
crs_to: ... | [{'piece_type': 'error message', 'piece_content': "In [4]: t = pyproj.Transformer()\\n\\nIn [5]: t\\nOut[5]: <pyproj.transformer.Transformer at 0x7fd75ff9b860>\\n\\nIn [6]: t.transform(0, 0)\\n---------------------------------------------------------------------------\\nAttributeError Traceba... | In [4]: t = pyproj.Transformer()
In [5]: t
Out[5]: <pyproj.transformer.Transformer at 0x7fd75ff9b860>
In [6]: t.transform(0, 0)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-6-65405fa99360> in <mod... | AttributeError |
def from_pipeline(proj_pipeline):
"""Make a Transformer from a PROJ pipeline string.
https://proj4.org/operations/pipeline.html
Parameters
----------
proj_pipeline: str
Projection pipeline string.
Returns
-------
~Transformer
""... | def from_pipeline(proj_pipeline):
"""Make a Transformer from a PROJ pipeline string.
https://proj4.org/operations/pipeline.html
Parameters
----------
proj_pipeline: str
Projection pipeline string.
Returns
-------
~Transformer
""... | [{'piece_type': 'error message', 'piece_content': "In [4]: t = pyproj.Transformer()\\n\\nIn [5]: t\\nOut[5]: <pyproj.transformer.Transformer at 0x7fd75ff9b860>\\n\\nIn [6]: t.transform(0, 0)\\n---------------------------------------------------------------------------\\nAttributeError Traceba... | In [4]: t = pyproj.Transformer()
In [5]: t
Out[5]: <pyproj.transformer.Transformer at 0x7fd75ff9b860>
In [6]: t.transform(0, 0)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-6-65405fa99360> in <mod... | AttributeError |
def _dict2string(projparams):
# convert a dict to a proj4 string.
pjargs = []
proj_inserted = False
for key, value in projparams.items():
# the towgs84 as list
if isinstance(value, (list, tuple)):
value = ",".join([str(val) for val in value])
# issue 183 (+ no_rot)
... | def _dict2string(projparams):
# convert a dict to a proj4 string.
pjargs = []
for key, value in projparams.items():
# the towgs84 as list
if isinstance(value, (list, tuple)):
value = ",".join([str(val) for val in value])
# issue 183 (+ no_rot)
if value is None or ... | [{'piece_type': 'error message', 'piece_content': 'from pyproj import Proj\\nProj({\\'a\\': 6371229.0, \\'b\\': 6371229.0, \\'lon_0\\': -10.0, \\'o_lat_p\\': 30.0, \\'o_lon_p\\': 0.0, \\'o_proj\\': \\'longlat\\', \\'proj\\'\\n: \\'ob_tran\\'})\\nTraceback (most recent call last):\\nFile "<stdin>", line 1, in <module>\\... | from pyproj import Proj
Proj({'a': 6371229.0, 'b': 6371229.0, 'lon_0': -10.0, 'o_lat_p': 30.0, 'o_lon_p': 0.0, 'o_proj': 'longlat', 'proj'
: 'ob_tran'})
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File ".../lib/python3.7/site-packages/pyproj/proj.py", line 303, in __init__
cstrencode(self.crs... | AttributeError |
def __init__(self, projparams=None, preserve_units=True, **kwargs):
"""
initialize a Proj class instance.
See the proj documentation (https://github.com/OSGeo/proj.4/wiki)
for more information about projection parameters.
Parameters
----------
projparams: in... | def __init__(self, projparams=None, preserve_units=True, **kwargs):
"""
initialize a Proj class instance.
See the proj documentation (https://github.com/OSGeo/proj.4/wiki)
for more information about projection parameters.
Parameters
----------
projparams: in... | [{'piece_type': 'error message', 'piece_content': 'from pyproj import Proj\\nProj({\\'a\\': 6371229.0, \\'b\\': 6371229.0, \\'lon_0\\': -10.0, \\'o_lat_p\\': 30.0, \\'o_lon_p\\': 0.0, \\'o_proj\\': \\'longlat\\', \\'proj\\'\\n: \\'ob_tran\\'})\\nTraceback (most recent call last):\\nFile "<stdin>", line 1, in <module>\\... | from pyproj import Proj
Proj({'a': 6371229.0, 'b': 6371229.0, 'lon_0': -10.0, 'o_lat_p': 30.0, 'o_lon_p': 0.0, 'o_proj': 'longlat', 'proj'
: 'ob_tran'})
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File ".../lib/python3.7/site-packages/pyproj/proj.py", line 303, in __init__
cstrencode(self.crs... | AttributeError |
def Kuf_conv_patch(inducing_variable, kernel, Xnew):
Xp = kernel.get_patches(Xnew) # [N, num_patches, patch_len]
bigKzx = kernel.base_kernel.K(
inducing_variable.Z, Xp
) # [M, N, P] -- thanks to broadcasting of kernels
Kzx = tf.reduce_sum(bigKzx * kernel.weights if hasattr(kernel, "weights") e... | def Kuf_conv_patch(feat, kern, Xnew):
Xp = kern.get_patches(Xnew) # [N, num_patches, patch_len]
bigKzx = kern.base_kernel.K(feat.Z, Xp) # [M, N, P] -- thanks to broadcasting of kernels
Kzx = tf.reduce_sum(bigKzx * kern.weights if hasattr(kern, "weights") else bigKzx, [2])
return Kzx / kern.num_patches | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def Kuu_kernel_inducingpoints(inducing_variable: InducingPoints, kernel: Kernel, *, jitter=0.0):
Kzz = kernel(inducing_variable.Z)
Kzz += jitter * tf.eye(inducing_variable.num_inducing, dtype=Kzz.dtype)
return Kzz | def Kuu_kernel_inducingpoints(inducing_variable: InducingPoints, kernel: Kernel, *, jitter=0.0):
Kzz = kernel(inducing_variable.Z)
Kzz += jitter * tf.eye(len(inducing_variable), dtype=Kzz.dtype)
return Kzz | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def Kuu_sqexp_multiscale(inducing_variable: Multiscale, kernel: SquaredExponential, *, jitter=0.0):
Zmu, Zlen = kernel.slice(inducing_variable.Z, inducing_variable.scales)
idlengthscales2 = tf.square(kernel.lengthscales + Zlen)
sc = tf.sqrt(
idlengthscales2[None, ...] + idlengthscales2[:, None, ...]... | def Kuu_sqexp_multiscale(inducing_variable: Multiscale, kernel: SquaredExponential, *, jitter=0.0):
Zmu, Zlen = kernel.slice(inducing_variable.Z, inducing_variable.scales)
idlengthscales2 = tf.square(kernel.lengthscales + Zlen)
sc = tf.sqrt(
idlengthscales2[None, ...] + idlengthscales2[:, None, ...]... | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def Kuu_conv_patch(inducing_variable, kernel, jitter=0.0):
return kernel.base_kernel.K(inducing_variable.Z) + jitter * tf.eye(
inducing_variable.num_inducing, dtype=default_float()
) | def Kuu_conv_patch(feat, kern, jitter=0.0):
return kern.base_kernel.K(feat.Z) + jitter * tf.eye(len(feat), dtype=default_float()) | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def _Kuu(
inducing_variable: FallbackSeparateIndependentInducingVariables,
kernel: Union[SeparateIndependent, LinearCoregionalization],
*,
jitter=0.0,
):
Kmms = [Kuu(f, k) for f, k in zip(inducing_variable.inducing_variable_list, kernel.kernels)]
Kmm = tf.stack(Kmms, axis=0) # [L, M, M]
jit... | def _Kuu(
inducing_variable: FallbackSeparateIndependentInducingVariables,
kernel: Union[SeparateIndependent, LinearCoregionalization],
*,
jitter=0.0,
):
Kmms = [Kuu(f, k) for f, k in zip(inducing_variable.inducing_variable_list, kernel.kernels)]
Kmm = tf.stack(Kmms, axis=0) # [L, M, M]
jit... | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def __init__(self, Z: TensorData, name: Optional[str] = None):
"""
:param Z: the initial positions of the inducing points, size [M, D]
"""
super().__init__(name=name)
if not isinstance(Z, (tf.Variable, tfp.util.TransformedVariable)):
Z = Parameter(Z)
self.... | def __init__(self, Z: TensorData, name: Optional[str] = None):
"""
:param Z: the initial positions of the inducing points, size [M, D]
"""
super().__init__(name=name)
self.Z = Parameter(Z, dtype=default_float()) | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def __len__(self) -> int:
return tf.shape(self.Z)[0] | def __len__(self) -> int:
return self.Z.shape[0] | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def __len__(self) -> int:
return self.inducing_variable.num_inducing | def __len__(self) -> int:
return len(self.inducing_variable) | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def __len__(self) -> int:
# TODO(st--) we should check that they all have the same length...
return self.inducing_variable_list[0].num_inducing | def __len__(self) -> int:
return len(self.inducing_variable_list[0]) | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def __init__(
self,
distribution_class: Type[tfp.distributions.Distribution] = tfp.distributions.Normal,
scale_transform: Optional[tfp.bijectors.Bijector] = None,
**kwargs,
):
"""
:param distribution_class: distribution class parameterized by `loc` and `scale`
... | def __init__(
self,
distribution_class: Type[tfp.distributions.Distribution] = tfp.distributions.Normal,
scale_transform: tfp.bijectors.Bijector = positive(base="exp"),
**kwargs,
):
"""
:param distribution_class: distribution class parameterized by `loc` and `scal... | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def conditional_distribution(Fs) -> tfp.distributions.Distribution:
tf.debugging.assert_equal(tf.shape(Fs)[-1], 2)
loc = Fs[..., :1]
scale = self.scale_transform(Fs[..., 1:])
return distribution_class(loc, scale) | def conditional_distribution(Fs) -> tfp.distributions.Distribution:
tf.debugging.assert_equal(tf.shape(Fs)[-1], 2)
loc = Fs[..., :1]
scale = scale_transform(Fs[..., 1:])
return distribution_class(loc, scale) | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def elbo(self) -> tf.Tensor:
"""
Construct a tensorflow function to compute the bound on the marginal
likelihood.
"""
Y_data = self.data
pX = DiagonalGaussian(self.X_data_mean, self.X_data_var)
num_inducing = self.inducing_variable.num_inducing
psi0 ... | def elbo(self) -> tf.Tensor:
"""
Construct a tensorflow function to compute the bound on the marginal
likelihood.
"""
Y_data = self.data
pX = DiagonalGaussian(self.X_data_mean, self.X_data_var)
num_inducing = len(self.inducing_variable)
psi0 = tf.red... | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def predict_f(
self, Xnew: InputData, full_cov: bool = False, full_output_cov: bool = False
) -> MeanAndVariance:
"""
Compute the mean and variance of the latent function at some new points.
Note that this is very similar to the SGPR prediction, for which
there are notes ... | def predict_f(
self, Xnew: InputData, full_cov: bool = False, full_output_cov: bool = False
) -> MeanAndVariance:
"""
Compute the mean and variance of the latent function at some new points.
Note that this is very similar to the SGPR prediction, for which
there are notes ... | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def __init__(
self,
data: RegressionData,
kernel: Kernel,
likelihood: Likelihood,
mean_function: Optional[MeanFunction] = None,
num_latent_gps: Optional[int] = None,
inducing_variable: Optional[InducingPoints] = None,
):
"""
data is a tuple... | def __init__(
self,
data: RegressionData,
kernel: Kernel,
likelihood: Likelihood,
mean_function: Optional[MeanFunction] = None,
num_latent_gps: Optional[int] = None,
inducing_variable: Optional[InducingPoints] = None,
):
"""
data is a tuple... | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def upper_bound(self) -> tf.Tensor:
"""
Upper bound for the sparse GP regression marginal likelihood. Note that
the same inducing points are used for calculating the upper bound, as are
used for computing the likelihood approximation. This may not lead to the
best upper boun... | def upper_bound(self) -> tf.Tensor:
"""
Upper bound for the sparse GP regression marginal likelihood. Note that
the same inducing points are used for calculating the upper bound, as are
used for computing the likelihood approximation. This may not lead to the
best upper boun... | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def elbo(self) -> tf.Tensor:
"""
Construct a tensorflow function to compute the bound on the marginal
likelihood. For a derivation of the terms in here, see the associated
SGPR notebook.
"""
X_data, Y_data = self.data
num_inducing = self.inducing_variable.num... | def elbo(self) -> tf.Tensor:
"""
Construct a tensorflow function to compute the bound on the marginal
likelihood. For a derivation of the terms in here, see the associated
SGPR notebook.
"""
X_data, Y_data = self.data
num_inducing = len(self.inducing_variable... | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def predict_f(self, Xnew: InputData, full_cov=False, full_output_cov=False) -> MeanAndVariance:
"""
Compute the mean and variance of the latent function at some new points
Xnew. For a derivation of the terms in here, see the associated SGPR
notebook.
"""
X_data, Y_dat... | def predict_f(self, Xnew: InputData, full_cov=False, full_output_cov=False) -> MeanAndVariance:
"""
Compute the mean and variance of the latent function at some new points
Xnew. For a derivation of the terms in here, see the associated SGPR
notebook.
"""
X_data, Y_dat... | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def common_terms(self):
X_data, Y_data = self.data
num_inducing = self.inducing_variable.num_inducing
err = Y_data - self.mean_function(X_data) # size [N, R]
Kdiag = self.kernel(X_data, full_cov=False)
kuf = Kuf(self.inducing_variable, self.kernel, X_data)
kuu = Kuu(... | def common_terms(self):
X_data, Y_data = self.data
num_inducing = len(self.inducing_variable)
err = Y_data - self.mean_function(X_data) # size [N, R]
Kdiag = self.kernel(X_data, full_cov=False)
kuf = Kuf(self.inducing_variable, self.kernel, X_data)
kuu = Kuu(self.ind... | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def __init__(
self,
kernel,
likelihood,
inducing_variable,
*,
mean_function=None,
num_latent_gps: int = 1,
q_diag: bool = False,
q_mu=None,
q_sqrt=None,
whiten: bool = True,
num_data=None,
):
"""
- ke... | def __init__(
self,
kernel,
likelihood,
inducing_variable,
*,
mean_function=None,
num_latent_gps: int = 1,
q_diag: bool = False,
q_mu=None,
q_sqrt=None,
whiten: bool = True,
num_data=None,
):
"""
- ke... | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nimport tensorflow as tf\\n\\nclass VariableInducingPoints(gpflow.inducing_variables.InducingPoints):\\ndef __init__(self, Z, name=None):\\nsuper().__init__(Z, name=name)\\n# overwrite with Variable with None as first eleme... | TypeError Traceback (most recent call last)
<ipython-input-24-9a082736eedc> in <module>
38
39
---> 40 optimization_step()
41
42
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
778 else:
779 compiler = "no... | TypeError |
def ndiagquad(funcs, H: int, Fmu, Fvar, logspace: bool = False, **Ys):
"""
Computes N Gaussian expectation integrals of one or more functions
using Gauss-Hermite quadrature. The Gaussians must be independent.
The means and variances of the Gaussians are specified by Fmu and Fvar.
The N-integrals ar... | def ndiagquad(funcs, H: int, Fmu, Fvar, logspace: bool = False, **Ys):
"""
Computes N Gaussian expectation integrals of one or more functions
using Gauss-Hermite quadrature. The Gaussians must be independent.
The means and variances of the Gaussians are specified by Fmu and Fvar.
The N-integrals ar... | [{'piece_type': 'other', 'piece_content': 'tensorflow.python.framework.errors_impl.OperatorNotAllowedInGraphError: using a `tf.Tensor` as a Python `bool` is not allowed: AutoGraph is disabled in this function. Try decorating it directly with @tf.function.'}, {'piece_type': 'reproducing source code', 'piece_content': "i... | Traceback (most recent call last):
File "gpflow_error.py", line 20, in <module>
go()
File "gpflow_error.py", line 16, in go
quad = compute()
File "/Users/nferguson/gpflow_error/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 580, in __call__
result = self._call(*args, **kwds)
File "/Users/nfe... | tensorflow.python.framework.errors_impl.OperatorNotAllowedInGraphError |
def wrapper(old_fun):
def new_fun(X, **Ys):
Xs = tf.unstack(X, axis=-1)
fun_eval = old_fun(*Xs, **Ys)
return tf.cond(
pred=tf.less(tf.rank(fun_eval), tf.rank(X)),
true_fn=lambda: fun_eval[..., tf.newaxis],
false_fn=lambda: f... | def wrapper(old_fun):
def new_fun(X, **Ys):
Xs = tf.unstack(X, axis=-1)
fun_eval = old_fun(*Xs, **Ys)
if tf.rank(fun_eval) < tf.rank(X):
fun_eval = tf.expand_dims(fun_eval, axis=-1)
return fun_eval
return new_fun | [{'piece_type': 'other', 'piece_content': 'tensorflow.python.framework.errors_impl.OperatorNotAllowedInGraphError: using a `tf.Tensor` as a Python `bool` is not allowed: AutoGraph is disabled in this function. Try decorating it directly with @tf.function.'}, {'piece_type': 'reproducing source code', 'piece_content': "i... | Traceback (most recent call last):
File "gpflow_error.py", line 20, in <module>
go()
File "gpflow_error.py", line 16, in go
quad = compute()
File "/Users/nferguson/gpflow_error/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 580, in __call__
result = self._call(*args, **kwds)
File "/Users/nfe... | tensorflow.python.framework.errors_impl.OperatorNotAllowedInGraphError |
def new_fun(X, **Ys):
Xs = tf.unstack(X, axis=-1)
fun_eval = old_fun(*Xs, **Ys)
return tf.cond(
pred=tf.less(tf.rank(fun_eval), tf.rank(X)),
true_fn=lambda: fun_eval[..., tf.newaxis],
false_fn=lambda: fun_eval,
) | def new_fun(X, **Ys):
Xs = tf.unstack(X, axis=-1)
fun_eval = old_fun(*Xs, **Ys)
if tf.rank(fun_eval) < tf.rank(X):
fun_eval = tf.expand_dims(fun_eval, axis=-1)
return fun_eval | [{'piece_type': 'other', 'piece_content': 'tensorflow.python.framework.errors_impl.OperatorNotAllowedInGraphError: using a `tf.Tensor` as a Python `bool` is not allowed: AutoGraph is disabled in this function. Try decorating it directly with @tf.function.'}, {'piece_type': 'reproducing source code', 'piece_content': "i... | Traceback (most recent call last):
File "gpflow_error.py", line 20, in <module>
go()
File "gpflow_error.py", line 16, in go
quad = compute()
File "/Users/nferguson/gpflow_error/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 580, in __call__
result = self._call(*args, **kwds)
File "/Users/nfe... | tensorflow.python.framework.errors_impl.OperatorNotAllowedInGraphError |
def __init__(
self,
data: OutputData,
latent_dim: int,
X_data_mean: Optional[tf.Tensor] = None,
kernel: Optional[Kernel] = None,
mean_function: Optional[MeanFunction] = None,
):
"""
Initialise GPLVM object. This method only works with a Gaussian li... | def __init__(
self,
data: OutputData,
latent_dim: int,
X_data_mean: Optional[tf.Tensor] = None,
kernel: Optional[Kernel] = None,
mean_function: Optional[MeanFunction] = None,
):
"""
Initialise GPLVM object. This method only works with a Gaussian li... | [{'piece_type': 'other', 'piece_content': 'ValueError: Cannot create a tensor proto whose content is larger than 2GB.'}, {'piece_type': 'error message', 'piece_content': 'Traceback (most recent call last):\\nFile "main.py", line 177, in <module>\\nmain(args)\\nFile "main.py", line 64, in main\\nbuild_allele(args)\\nFil... | Traceback (most recent call last):
File "main.py", line 177, in <module>
main(args)
File "main.py", line 64, in main
build_allele(args)
File "/path/to/1_model_sim/drivers.py", line 226, in build_allele
opt_model_list(m)
File "/path/to/1_model_sim/model.py", line 355, in opt_model_list
m.trainable_variables)
File "/path... | ValueError |
def __init__(
self,
data: OutputData,
X_data_mean: tf.Tensor,
X_data_var: tf.Tensor,
kernel: Kernel,
num_inducing_variables: Optional[int] = None,
inducing_variable=None,
X_prior_mean=None,
X_prior_var=None,
):
"""
Initialis... | def __init__(
self,
data: OutputData,
X_data_mean: tf.Tensor,
X_data_var: tf.Tensor,
kernel: Kernel,
num_inducing_variables: Optional[int] = None,
inducing_variable=None,
X_prior_mean=None,
X_prior_var=None,
):
"""
Initialis... | [{'piece_type': 'other', 'piece_content': 'ValueError: Cannot create a tensor proto whose content is larger than 2GB.'}, {'piece_type': 'error message', 'piece_content': 'Traceback (most recent call last):\\nFile "main.py", line 177, in <module>\\nmain(args)\\nFile "main.py", line 64, in main\\nbuild_allele(args)\\nFil... | Traceback (most recent call last):
File "main.py", line 177, in <module>
main(args)
File "main.py", line 64, in main
build_allele(args)
File "/path/to/1_model_sim/drivers.py", line 226, in build_allele
opt_model_list(m)
File "/path/to/1_model_sim/model.py", line 355, in opt_model_list
m.trainable_variables)
File "/path... | ValueError |
def __init__(
self,
data: RegressionData,
kernel: Kernel,
mean_function: Optional[MeanFunction] = None,
noise_variance: float = 1.0,
):
likelihood = gpflow.likelihoods.Gaussian(noise_variance)
_, Y_data = data
super().__init__(kernel, likelihood, m... | def __init__(
self,
data: RegressionData,
kernel: Kernel,
mean_function: Optional[MeanFunction] = None,
noise_variance: float = 1.0,
):
likelihood = gpflow.likelihoods.Gaussian(noise_variance)
_, Y_data = data
super().__init__(kernel, likelihood, m... | [{'piece_type': 'other', 'piece_content': 'ValueError: Cannot create a tensor proto whose content is larger than 2GB.'}, {'piece_type': 'error message', 'piece_content': 'Traceback (most recent call last):\\nFile "main.py", line 177, in <module>\\nmain(args)\\nFile "main.py", line 64, in main\\nbuild_allele(args)\\nFil... | Traceback (most recent call last):
File "main.py", line 177, in <module>
main(args)
File "main.py", line 64, in main
build_allele(args)
File "/path/to/1_model_sim/drivers.py", line 226, in build_allele
opt_model_list(m)
File "/path/to/1_model_sim/model.py", line 355, in opt_model_list
m.trainable_variables)
File "/path... | ValueError |
def __init__(
self,
data: RegressionData,
kernel: Kernel,
likelihood: Likelihood,
mean_function: Optional[MeanFunction] = None,
num_latent_gps: Optional[int] = None,
inducing_variable: Optional[InducingPoints] = None,
):
"""
data is a tuple... | def __init__(
self,
data: RegressionData,
kernel: Kernel,
likelihood: Likelihood,
mean_function: Optional[MeanFunction] = None,
num_latent_gps: Optional[int] = None,
inducing_variable: Optional[InducingPoints] = None,
):
"""
data is a tuple... | [{'piece_type': 'other', 'piece_content': 'ValueError: Cannot create a tensor proto whose content is larger than 2GB.'}, {'piece_type': 'error message', 'piece_content': 'Traceback (most recent call last):\\nFile "main.py", line 177, in <module>\\nmain(args)\\nFile "main.py", line 64, in main\\nbuild_allele(args)\\nFil... | Traceback (most recent call last):
File "main.py", line 177, in <module>
main(args)
File "main.py", line 64, in main
build_allele(args)
File "/path/to/1_model_sim/drivers.py", line 226, in build_allele
opt_model_list(m)
File "/path/to/1_model_sim/model.py", line 355, in opt_model_list
m.trainable_variables)
File "/path... | ValueError |
def __init__(
self,
data: RegressionData,
kernel: Kernel,
inducing_variable: InducingPoints,
*,
mean_function: Optional[MeanFunction] = None,
num_latent_gps: Optional[int] = None,
noise_variance: float = 1.0,
):
"""
`data`: a tuple... | def __init__(
self,
data: RegressionData,
kernel: Kernel,
inducing_variable: InducingPoints,
*,
mean_function: Optional[MeanFunction] = None,
num_latent_gps: Optional[int] = None,
noise_variance: float = 1.0,
):
"""
`data`: a tuple... | [{'piece_type': 'other', 'piece_content': 'ValueError: Cannot create a tensor proto whose content is larger than 2GB.'}, {'piece_type': 'error message', 'piece_content': 'Traceback (most recent call last):\\nFile "main.py", line 177, in <module>\\nmain(args)\\nFile "main.py", line 64, in main\\nbuild_allele(args)\\nFil... | Traceback (most recent call last):
File "main.py", line 177, in <module>
main(args)
File "main.py", line 64, in main
build_allele(args)
File "/path/to/1_model_sim/drivers.py", line 226, in build_allele
opt_model_list(m)
File "/path/to/1_model_sim/model.py", line 355, in opt_model_list
m.trainable_variables)
File "/path... | ValueError |
def __init__(
self,
data: RegressionData,
kernel: Kernel,
likelihood: Likelihood,
mean_function: Optional[MeanFunction] = None,
num_latent_gps: Optional[int] = None,
):
"""
data = (X, Y) contains the input points [N, D] and the observations [N, P]
... | def __init__(
self,
data: RegressionData,
kernel: Kernel,
likelihood: Likelihood,
mean_function: Optional[MeanFunction] = None,
num_latent_gps: Optional[int] = None,
):
"""
data = (X, Y) contains the input points [N, D] and the observations [N, P]
... | [{'piece_type': 'other', 'piece_content': 'ValueError: Cannot create a tensor proto whose content is larger than 2GB.'}, {'piece_type': 'error message', 'piece_content': 'Traceback (most recent call last):\\nFile "main.py", line 177, in <module>\\nmain(args)\\nFile "main.py", line 64, in main\\nbuild_allele(args)\\nFil... | Traceback (most recent call last):
File "main.py", line 177, in <module>
main(args)
File "main.py", line 64, in main
build_allele(args)
File "/path/to/1_model_sim/drivers.py", line 226, in build_allele
opt_model_list(m)
File "/path/to/1_model_sim/model.py", line 355, in opt_model_list
m.trainable_variables)
File "/path... | ValueError |
def __init__(
self,
data: RegressionData,
kernel: Kernel,
likelihood: Likelihood,
mean_function: Optional[MeanFunction] = None,
num_latent_gps: Optional[int] = None,
):
"""
data = (X, Y) contains the input points [N, D] and the observations [N, P]
... | def __init__(
self,
data: RegressionData,
kernel: Kernel,
likelihood: Likelihood,
mean_function: Optional[MeanFunction] = None,
num_latent_gps: Optional[int] = None,
):
"""
data = (X, Y) contains the input points [N, D] and the observations [N, P]
... | [{'piece_type': 'other', 'piece_content': 'ValueError: Cannot create a tensor proto whose content is larger than 2GB.'}, {'piece_type': 'error message', 'piece_content': 'Traceback (most recent call last):\\nFile "main.py", line 177, in <module>\\nmain(args)\\nFile "main.py", line 64, in main\\nbuild_allele(args)\\nFil... | Traceback (most recent call last):
File "main.py", line 177, in <module>
main(args)
File "main.py", line 64, in main
build_allele(args)
File "/path/to/1_model_sim/drivers.py", line 226, in build_allele
opt_model_list(m)
File "/path/to/1_model_sim/model.py", line 355, in opt_model_list
m.trainable_variables)
File "/path... | ValueError |
def __init__(
self,
data: RegressionData,
kernel: Kernel,
likelihood: Likelihood,
mean_function: Optional[MeanFunction] = None,
num_latent_gps: Optional[int] = None,
):
"""
data is a tuple of X, Y with X, a data matrix, size [N, D] and Y, a data ma... | def __init__(
self,
data: RegressionData,
kernel: Kernel,
likelihood: Likelihood,
mean_function: Optional[MeanFunction] = None,
num_latent_gps: Optional[int] = None,
):
"""
data is a tuple of X, Y with X, a data matrix, size [N, D] and Y, a data ma... | [{'piece_type': 'other', 'piece_content': 'ValueError: Cannot create a tensor proto whose content is larger than 2GB.'}, {'piece_type': 'error message', 'piece_content': 'Traceback (most recent call last):\\nFile "main.py", line 177, in <module>\\nmain(args)\\nFile "main.py", line 64, in main\\nbuild_allele(args)\\nFil... | Traceback (most recent call last):
File "main.py", line 177, in <module>
main(args)
File "main.py", line 64, in main
build_allele(args)
File "/path/to/1_model_sim/drivers.py", line 226, in build_allele
opt_model_list(m)
File "/path/to/1_model_sim/model.py", line 355, in opt_model_list
m.trainable_variables)
File "/path... | ValueError |
def K(self, X: tf.Tensor, X2: Optional[tf.Tensor] = None) -> tf.Tensor:
sig_X = self._sigmoids(X) # N1 x 1 x Ncp
sig_X2 = self._sigmoids(X2) if X2 is not None else sig_X # N2 x 1 x Ncp
# `starters` are the sigmoids going from 0 -> 1, whilst `stoppers` go
# from 1 -> 0, dimensions ... | def K(self, X: tf.Tensor, X2: Optional[tf.Tensor] = None) -> tf.Tensor:
sig_X = self._sigmoids(X) # N x 1 x Ncp
sig_X2 = self._sigmoids(X2) if X2 is not None else sig_X
# `starters` are the sigmoids going from 0 -> 1, whilst `stoppers` go
# from 1 -> 0, dimensions are N x N x Ncp
... | [{'piece_type': 'reproducing source code', 'piece_content': 'import numpy as np\\nimport gpflow\\nX = np.linspace(0,100,100).reshape(100,1)\\nbase_k1 = gpflow.kernels.Matern32(lengthscales=0.2)\\nbase_k2 = gpflow.kernels.Matern32(lengthscales=2.0)\\nk = gpflow.kernels.ChangePoints([base_k1, base_k2], [0.0], steepness=5... | ---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
<ipython-input-25-d1dbc7941bae> in <module>
----> 1 k(X, xx)
~/Code/GPflow/gpflow/kernels/base.py in __call__(self, X, X2, full_cov, presliced)
170
171 else:
-... | InvalidArgumentError |
def autoflow(*af_args, **af_kwargs):
def autoflow_wrapper(method):
@functools.wraps(method)
def runnable(obj, *args, **kwargs):
if not isinstance(obj, Node):
raise GPflowError(
'AutoFlow works only with node-like objects.')
if obj.is_built_... | def autoflow(*af_args, **af_kwargs):
def autoflow_wrapper(method):
@functools.wraps(method)
def runnable(obj, *args, **kwargs):
if not isinstance(obj, Node):
raise GPflowError(
'AutoFlow works only with node-like objects.')
if obj.is_built_... | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def autoflow_wrapper(method):
@functools.wraps(method)
def runnable(obj, *args, **kwargs):
if not isinstance(obj, Node):
raise GPflowError(
'AutoFlow works only with node-like objects.')
if obj.is_built_coherence(obj.graph) is Build.NO:
... | def autoflow_wrapper(method):
@functools.wraps(method)
def runnable(obj, *args, **kwargs):
if not isinstance(obj, Node):
raise GPflowError(
'AutoFlow works only with node-like objects.')
if obj.is_built_coherence(obj.graph) is Build.NO:
... | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def runnable(obj, *args, **kwargs):
if not isinstance(obj, Node):
raise GPflowError(
'AutoFlow works only with node-like objects.')
if obj.is_built_coherence(obj.graph) is Build.NO:
raise GPflowError('Not built with "{graph}".'.format(g... | def runnable(obj, *args, **kwargs):
if not isinstance(obj, Node):
raise GPflowError(
'AutoFlow works only with node-like objects.')
if obj.is_built_coherence(obj.graph) is Build.NO:
raise GPflowError('Not built with "{graph}".'.format(g... | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def initialize_variables(variables=None, session=None, force=False, **run_kwargs):
session = tf.get_default_session() if session is None else session
if variables is None:
initializer = tf.global_variables_initializer()
else:
if force:
vars_for_init = list(_initializable_tensors(... | def initialize_variables(variables=None, session=None, force=False, **run_kwargs):
session = tf.get_default_session() if session is None else session
if variables is None:
initializer = tf.global_variables_initializer()
else:
if force:
initializer = tf.variables_initializer(varia... | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def _clear(self):
self._reset_name()
self._initial_value_tensor = None
self._dataholder_tensor = None
self._is_initialized_tensor = None | def _clear(self):
self._reset_name()
self._initial_value_tensor = None
self._dataholder_tensor = None | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def _build(self):
tensor = self._build_parameter()
self._dataholder_tensor = tensor
self._is_initialized_tensor = tf.is_variable_initialized(tensor) | def _build(self):
self._dataholder_tensor = self._build_parameter() # pylint: disable=W0201 | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def _init_parameter_defaults(self):
self._initial_value_tensor = None
self._dataholder_tensor = None
self._is_initialized_tensor = None | def _init_parameter_defaults(self):
self._initial_value_tensor = None
self._dataholder_tensor = None | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def initializables(self):
if self._externally_defined:
return None
return [(self.parameter_tensor, self.is_initialized_tensor)] | def initializables(self):
if self._externally_defined:
return None
return [self.parameter_tensor] | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def read_value(self, session=None):
if session is not None and not isinstance(session, tf.Session):
raise ValueError('TensorFlow session expected as an argument.')
if session is None and self._externally_defined:
raise GPflowError('Externally defined parameter requires sessio... | def read_value(self, session=None):
if session is not None:
if not isinstance(session, tf.Session):
raise ValueError('TensorFlow session expected as session argument.')
is_built = self.is_built_coherence(session.graph)
if is_built is Build.YES:
... | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def _clear(self):
self._reset_name()
self._externally_defined = False
self._is_initialized_tensor = None
self._initial_value_tensor = None
self._unconstrained_tensor = None
self._constrained_tensor = None
self._prior_tensor = None | def _clear(self):
self._reset_name()
self._externally_defined = False # pylint: disable=W0201
self._initial_value_tensor = None # pylint: disable=W0201
self._unconstrained_tensor = None # pylint: disable=W0201
self._constrained_tensor = None # pylint: disable=W0201
... | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def _build(self):
unconstrained = self._build_parameter()
constrained = self._build_constrained(unconstrained)
prior = self._build_prior(unconstrained, constrained)
self._is_initialized_tensor = tf.is_variable_initialized(unconstrained)
self._unconstrained_tensor = unconstra... | def _build(self):
unconstrained = self._build_parameter()
constrained = self._build_constrained(unconstrained)
prior = self._build_prior(unconstrained, constrained)
self._unconstrained_tensor = unconstrained # pylint: disable=W0201
self._constrained_tensor = constrained ... | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def _build_parameter(self):
if self._externally_defined:
self._check_tensor_trainable(self.parameter_tensor)
return self.parameter_tensor
name = self._parameter_name()
tensor = misc.get_variable_by_name(name)
if tensor is not None:
raise GPflowErr... | def _build_parameter(self):
if self._externally_defined:
self._check_tensor_trainable(self.parameter_tensor)
return self.parameter_tensor
name = self._parameter_name()
tensor = misc.get_variable_by_name(name)
if tensor is not None:
raise GPflowErr... | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def _init_parameter_defaults(self):
self._is_initialized_tensor = None
self._initial_value_tensor = None
self._unconstrained_tensor = None
self._prior_tensor = None
self._constrained_tensor = None | def _init_parameter_defaults(self):
self._initial_value_tensor = None
self._unconstrained_tensor = None
self._prior_tensor = None
self._constrained_tensor = None | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def minimize(self, model, session=None, var_list=None, feed_dict=None,
maxiter=1000, initialize=False, anchor=True, **kwargs):
"""
Minimizes objective function of the model.
:param model: GPflow model with objective tensor.
:param session: Session where optimization... | def minimize(self, model, session=None, var_list=None, feed_dict=None,
maxiter=1000, initialize=True, anchor=True, **kwargs):
"""
Minimizes objective function of the model.
:param model: GPflow model with objective tensor.
:param session: Session where optimization ... | [{'piece_type': 'source code', 'piece_content': 'model = gpflow.models.svgp.SVGP(np.random.randn(1, 1),\\nnp.random.randn(1, 1),\\ngpflow.kernels.RBF(1),\\ngpflow.likelihoods.Gaussian(),\\nnp.random.randn(1, 1),\\nminibatch_size=1)\\nmodel.compute_log_likelihood()'}, {'piece_type': 'error message', 'piece_content': '--... | ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-e3c07a8fceb7> in <module>()
10 np.random.randn(M, D),
11 minibatch_size=2)
---> 12 mode... | AttributeError |
def prob_is_largest(self, Y, mu, var, gh_x, gh_w):
# work out what the mean and variance is of the indicated latent function.
oh_on = tf.cast(tf.one_hot(tf.reshape(Y, (-1,)), self.num_classes, 1., 0.), tf.float64)
mu_selected = tf.reduce_sum(oh_on * mu, 1)
var_selected = tf.reduce_su... | def prob_is_largest(self, Y, mu, var, gh_x, gh_w):
# work out what the mean and variance is of the indicated latent function.
oh_on = tf.cast(tf.one_hot(tf.reshape(Y, (-1,)), self.num_classes, 1., 0.), tf.float64)
mu_selected = tf.reduce_sum(oh_on * mu, 1)
var_selected = tf.reduce_su... | [{'piece_type': 'source code', 'piece_content': 'm.kern.white.variance.fixed = True\\nm.Z.fixed = True\\n_ = m.optimize()'}, {'piece_type': 'error message', 'piece_content': 'python\\n---------------------------------------------------------------------------\\nValueError Traceback (most ... | python
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-5-e4eebd086840> in <module>()
1 m.kern.white.variance.fixed = True
2 m.Z.fixed = True
----> 3 _ = m.optimize()
/Users/danmarthaler/GPflow/GPflow/... | ValueError |
def __call__(self, tf_method):
@wraps(tf_method)
def runnable(instance, *np_args):
graph_name = '_' + tf_method.__name__ + '_graph'
if not hasattr(instance, graph_name):
if instance._needs_recompile:
instance._compile() # ensures free_vars... | def __call__(self, tf_method):
@wraps(tf_method)
def runnable(instance, *np_args):
graph_name = '_' + tf_method.__name__ + '_graph'
if not hasattr(instance, graph_name):
instance._compile()
self.tf_args = [tf.placeholder(*a) for a in self.tf_ar... | [{'piece_type': 'other', 'piece_content': 'import GPflow\\nimport tensorflow as tf\\nimport os\\nimport numpy as np\\ndef getData():\\nrng = np.random.RandomState( 1 )\\nN = 30\\nX = rng.rand(N,1)\\nY = np.sin(12*X) + 0.66*np.cos(25*X) + rng.randn(N,1)*0.1 + 3\\nreturn X,Y\\nif __name__ == \\'__main__\\':\\nX,Y = getDa... | Traceback (most recent call last):
File "/Users/mqbssaby/PrivateProjects/BranchedGP/runfile.py", line 29, in <module>
[mu,var] = m.predict_f(X)
File "/Users/mqbssaby/pythonlibs/GPflow/GPflow/model.py", line 82, in runnable
return instance._session.run(graph, feed_dict=feed_dict)
File "/Users/mqbssaby/anaconda/lib/pytho... | ValueError |
def runnable(instance, *np_args):
graph_name = '_' + tf_method.__name__ + '_graph'
if not hasattr(instance, graph_name):
if instance._needs_recompile:
instance._compile() # ensures free_vars is up-to-date.
self.tf_args = [tf.placeholde... | def runnable(instance, *np_args):
graph_name = '_' + tf_method.__name__ + '_graph'
if not hasattr(instance, graph_name):
instance._compile()
self.tf_args = [tf.placeholder(*a) for a in self.tf_arg_tuples]
with instance.tf_mode():
... | [{'piece_type': 'other', 'piece_content': 'import GPflow\\nimport tensorflow as tf\\nimport os\\nimport numpy as np\\ndef getData():\\nrng = np.random.RandomState( 1 )\\nN = 30\\nX = rng.rand(N,1)\\nY = np.sin(12*X) + 0.66*np.cos(25*X) + rng.randn(N,1)*0.1 + 3\\nreturn X,Y\\nif __name__ == \\'__main__\\':\\nX,Y = getDa... | Traceback (most recent call last):
File "/Users/mqbssaby/PrivateProjects/BranchedGP/runfile.py", line 29, in <module>
[mu,var] = m.predict_f(X)
File "/Users/mqbssaby/pythonlibs/GPflow/GPflow/model.py", line 82, in runnable
return instance._session.run(graph, feed_dict=feed_dict)
File "/Users/mqbssaby/anaconda/lib/pytho... | ValueError |
def browse(self, uri):
logger.debug("Browsing files at: %s", uri)
result = []
local_path = path.uri_to_path(uri)
if str(local_path) == "root":
return list(self._get_media_dirs_refs())
if not self._is_in_basedir(local_path):
logger.warning(
... | def browse(self, uri):
logger.debug("Browsing files at: %s", uri)
result = []
local_path = path.uri_to_path(uri)
if str(local_path) == "root":
return list(self._get_media_dirs_refs())
if not self._is_in_basedir(local_path):
logger.warning(
... | [{'piece_type': 'error message', 'piece_content': 'FileBackend-2 DEBUG 2020-05-07 14:06:45,889 Browsing files at: file:///home/nick/Music/Tall%20Ships%20-%20Chemistry.mp3\\nCore-7 ERROR 2020-05-07 14:06:45,889 FileBackend backend caused an exception.\\nTraceback (most recent call last):\\nFile "/home/nick/Dev/mop... | FileBackend-2 DEBUG 2020-05-07 14:06:45,889 Browsing files at: file:///home/nick/Music/Tall%20Ships%20-%20Chemistry.mp3
Core-7 ERROR 2020-05-07 14:06:45,889 FileBackend backend caused an exception.
Traceback (most recent call last):
File "/home/nick/Dev/mopidy-dev/mopidy/mopidy/core/library.py", line 17, in _back... | NotADirectoryError |
def on_error(self, error, debug):
gst_logger.error(f"GStreamer error: {error.message}")
gst_logger.debug(
f"Got ERROR bus message: error={error!r} debug={debug!r}"
)
# TODO: is this needed?
self._audio.stop_playback() | def on_error(self, error, debug):
error_msg = str(error).decode()
debug_msg = debug.decode()
gst_logger.debug(
"Got ERROR bus message: error=%r debug=%r", error_msg, debug_msg
)
gst_logger.error("GStreamer error: %s", error_msg)
# TODO: is this needed?
... | [{'piece_type': 'error message', 'piece_content': 'Traceback (most recent call last):\\nFile "/home/jodal/mopidy-dev/mopidy/mopidy/audio/actor.py", line 219, in on_message\\nself.on_error(error, debug)\\nFile "/home/jodal/mopidy-dev/mopidy/mopidy/audio/actor.py", line 328, in on_error\\nerror_msg = str(error).decode()\... | Traceback (most recent call last):
File "/home/jodal/mopidy-dev/mopidy/mopidy/audio/actor.py", line 219, in on_message
self.on_error(error, debug)
File "/home/jodal/mopidy-dev/mopidy/mopidy/audio/actor.py", line 328, in on_error
error_msg = str(error).decode()
AttributeError: 'str' object has no attribute 'decode' | AttributeError |
def on_warning(self, error, debug):
gst_logger.warning(f"GStreamer warning: {error.message}")
gst_logger.debug(
f"Got WARNING bus message: error={error!r} debug={debug!r}"
) | def on_warning(self, error, debug):
error_msg = str(error).decode()
debug_msg = debug.decode()
gst_logger.warning("GStreamer warning: %s", error_msg)
gst_logger.debug(
"Got WARNING bus message: error=%r debug=%r", error_msg, debug_msg
) | [{'piece_type': 'error message', 'piece_content': 'Traceback (most recent call last):\\nFile "/home/jodal/mopidy-dev/mopidy/mopidy/audio/actor.py", line 219, in on_message\\nself.on_error(error, debug)\\nFile "/home/jodal/mopidy-dev/mopidy/mopidy/audio/actor.py", line 328, in on_error\\nerror_msg = str(error).decode()\... | Traceback (most recent call last):
File "/home/jodal/mopidy-dev/mopidy/mopidy/audio/actor.py", line 219, in on_message
self.on_error(error, debug)
File "/home/jodal/mopidy-dev/mopidy/mopidy/audio/actor.py", line 328, in on_error
error_msg = str(error).decode()
AttributeError: 'str' object has no attribute 'decode' | AttributeError |
def _unwrap_stream(uri, timeout, scanner, requests_session):
"""
Get a stream URI from a playlist URI, ``uri``.
Unwraps nested playlists until something that's not a playlist is found or
the ``timeout`` is reached.
"""
original_uri = uri
seen_uris = set()
deadline = time.time() + timeo... | def _unwrap_stream(uri, timeout, scanner, requests_session):
"""
Get a stream URI from a playlist URI, ``uri``.
Unwraps nested playlists until something that's not a playlist is found or
the ``timeout`` is reached.
"""
original_uri = uri
seen_uris = set()
deadline = time.time() + timeo... | [{'piece_type': 'error message', 'piece_content': 'ERROR StreamBackend backend caused an exception.\\nTraceback (most recent call last):\\nFile "/usr/lib64/python2.7/site-packages/mopidy/core/library.py", line 19, in _backend_error_handling\\nyield\\nFile "/usr/lib64/python2.7/site-packages/mopidy/core/library.py", ... | ERROR StreamBackend backend caused an exception.
Traceback (most recent call last):
File "/usr/lib64/python2.7/site-packages/mopidy/core/library.py", line 19, in _backend_error_handling
yield
File "/usr/lib64/python2.7/site-packages/mopidy/core/library.py", line 237, in lookup
result = future.get()
File "/usr/lib64/... | AttributeError |
def listplaylist(context, name):
"""
*musicpd.org, stored playlists section:*
``listplaylist {NAME}``
Lists the files in the playlist ``NAME.m3u``.
Output format::
file: relative/path/to/file1.flac
file: relative/path/to/file2.ogg
file: relative/path/to/file3.mp3
... | def listplaylist(context, name):
"""
*musicpd.org, stored playlists section:*
``listplaylist {NAME}``
Lists the files in the playlist ``NAME.m3u``.
Output format::
file: relative/path/to/file1.flac
file: relative/path/to/file2.ogg
file: relative/path/to/file3.mp3
... | [{'piece_type': 'error message', 'piece_content': 'ERROR Unhandled exception in MpdSession (urn:uuid:76575e20-c10f-46e2-bc60-404ed1cffc27):\\nTraceback (most recent call last):\\nFile "/usr/lib64/python2.7/site-packages/pykka/actor.py", line 201, in _actor_loop\\nresponse = self._handle_receive(message)\\nFile "/usr... | ERROR Unhandled exception in MpdSession (urn:uuid:76575e20-c10f-46e2-bc60-404ed1cffc27):
Traceback (most recent call last):
File "/usr/lib64/python2.7/site-packages/pykka/actor.py", line 201, in _actor_loop
response = self._handle_receive(message)
File "/usr/lib64/python2.7/site-packages/pykka/actor.py", line 304, i... | UnicodeDecodeError |
def track_to_mpd_format(track, position=None, stream_title=None):
"""
Format track for output to MPD client.
:param track: the track
:type track: :class:`mopidy.models.Track` or :class:`mopidy.models.TlTrack`
:param position: track's position in playlist
:type position: integer
:param strea... | def track_to_mpd_format(track, position=None, stream_title=None):
"""
Format track for output to MPD client.
:param track: the track
:type track: :class:`mopidy.models.Track` or :class:`mopidy.models.TlTrack`
:param position: track's position in playlist
:type position: integer
:param strea... | [{'piece_type': 'error message', 'piece_content': 'ERROR Unhandled exception in MpdSession (urn:uuid:76575e20-c10f-46e2-bc60-404ed1cffc27):\\nTraceback (most recent call last):\\nFile "/usr/lib64/python2.7/site-packages/pykka/actor.py", line 201, in _actor_loop\\nresponse = self._handle_receive(message)\\nFile "/usr... | ERROR Unhandled exception in MpdSession (urn:uuid:76575e20-c10f-46e2-bc60-404ed1cffc27):
Traceback (most recent call last):
File "/usr/lib64/python2.7/site-packages/pykka/actor.py", line 201, in _actor_loop
response = self._handle_receive(message)
File "/usr/lib64/python2.7/site-packages/pykka/actor.py", line 304, i... | UnicodeDecodeError |
def _get_user_dirs(xdg_config_dir):
"""Returns a dict of XDG dirs read from
``$XDG_CONFIG_HOME/user-dirs.dirs``.
This is used at import time for most users of :mod:`mopidy`. By rolling our
own implementation instead of using :meth:`glib.get_user_special_dir` we
make it possible for many extensions ... | def _get_user_dirs(xdg_config_dir):
"""Returns a dict of XDG dirs read from
``$XDG_CONFIG_HOME/user-dirs.dirs``.
This is used at import time for most users of :mod:`mopidy`. By rolling our
own implementation instead of using :meth:`glib.get_user_special_dir` we
make it possible for many extensions ... | [{'piece_type': 'error message', 'piece_content': 'ERROR FileBackend backend caused an exception.\\nTraceback (most recent call last):\\nFile "/usr/lib/python2.7/dist-packages/mopidy/core/library.py", line 19, in _backend_error_handling\\nyield\\nFile "/usr/lib/python2.7/dist-packages/mopidy/core/library.py", line 1... | ERROR FileBackend backend caused an exception.
Traceback (most recent call last):
File "/usr/lib/python2.7/dist-packages/mopidy/core/library.py", line 19, in _backend_error_handling
yield
File "/usr/lib/python2.7/dist-packages/mopidy/core/library.py", line 112, in _browse
result = backend.library.browse(uri).get()
F... | ValueError |
def validate(self, value):
value = super(Identifier, self).validate(value)
if isinstance(value, compat.text_type):
value = value.encode('utf-8')
return compat.intern(value) | def validate(self, value):
return compat.intern(str(super(Identifier, self).validate(value))) | [{'piece_type': 'error message', 'piece_content': 'INFO Scanned 3500 of 5494 files in 25s, ~14s left.\\nERROR \\'ascii\\' codec can\\'t encode character u\\'\\\\ufeff\\' in position 0: ordinal not in range(128)\\nTraceback (most recent call last):\\nFile "/usr/local/lib/python2.7/site-packages/mopidy/__main__.py... | INFO Scanned 3500 of 5494 files in 25s, ~14s left.
ERROR 'ascii' codec can't encode character u'\\ufeff' in position 0: ordinal not in range(128)
Traceback (most recent call last):
File "/usr/local/lib/python2.7/site-packages/mopidy/__main__.py", line 134, in main
return args.command.run(args, proxied_config)
Fi... | UnicodeEncodeError |
def on_stream_start(self):
gst_logger.debug('Got STREAM_START bus message')
uri = self._audio._pending_uri
logger.debug('Audio event: stream_changed(uri=%r)', uri)
AudioListener.send('stream_changed', uri=uri)
# Emit any postponed tags that we got after about-to-finish.
... | def on_stream_start(self):
gst_logger.debug('Got STREAM_START bus message')
uri = self._audio._pending_uri
logger.debug('Audio event: stream_changed(uri=%r)', uri)
AudioListener.send('stream_changed', uri=uri)
# Emit any postponed tags that we got after about-to-finish.
... | [{'piece_type': 'error message', 'piece_content': 'Traceback (most recent call last):\\nFile "/home/jodal/mopidy-dev/mopidy/mopidy/audio/actor.py", line 225, in on_message\\nself.on_tag(taglist)\\nFile "/home/jodal/mopidy-dev/mopidy/mopidy/audio/actor.py", line 340, in on_tag\\nif self._audio._tags.get(key, unique) != ... | Traceback (most recent call last):
File "/home/jodal/mopidy-dev/mopidy/mopidy/audio/actor.py", line 225, in on_message
self.on_tag(taglist)
File "/home/jodal/mopidy-dev/mopidy/mopidy/audio/actor.py", line 340, in on_tag
if self._audio._tags.get(key, unique) != value:
AttributeError: 'NoneType' object has no attribute '... | AttributeError |
def on_playbin_state_changed(self, old_state, new_state, pending_state):
gst_logger.debug(
'Got STATE_CHANGED bus message: old=%s new=%s pending=%s',
old_state.value_name, new_state.value_name,
pending_state.value_name)
if new_state == Gst.State.READY and pending... | def on_playbin_state_changed(self, old_state, new_state, pending_state):
gst_logger.debug(
'Got STATE_CHANGED bus message: old=%s new=%s pending=%s',
old_state.value_name, new_state.value_name,
pending_state.value_name)
if new_state == Gst.State.READY and pending... | [{'piece_type': 'error message', 'piece_content': 'Traceback (most recent call last):\\nFile "/home/trygve/dev/mopidy/mopidy/mopidy/audio/actor.py", line 210, in on_message\\nself.on_playbin_state_changed(old_state, new_state, pending_state)\\nFile "/home/trygve/dev/mopidy/mopidy/mopidy/audio/actor.py", line 260, in on... | Traceback (most recent call last):
File "/home/trygve/dev/mopidy/mopidy/mopidy/audio/actor.py", line 210, in on_message
self.on_playbin_state_changed(old_state, new_state, pending_state)
File "/home/trygve/dev/mopidy/mopidy/mopidy/audio/actor.py", line 260, in on_playbin_state_changed
target_state = _GST_STATE_MAPPING[... | KeyError |
def playlist_uri_from_name(self, name):
"""
Helper function to retrieve a playlist URI from its unique MPD name.
"""
if name not in self._uri_from_name:
self.refresh_playlists_mapping()
return self._uri_from_name.get(name) | def playlist_uri_from_name(self, name):
"""
Helper function to retrieve a playlist URI from its unique MPD name.
"""
if not self._uri_from_name:
self.refresh_playlists_mapping()
return self._uri_from_name.get(name) | [{'piece_type': 'error message', 'piece_content': '2015-12-04 23:41:33,959 ERROR [MpdSession-13] /home/adamcik/dev/mopidy-virtualenv/local/lib/python2.7/site-packages/pykka/actor.py:269\\npykka Unhandled exception in MpdSession (urn:uuid:093fbff0-33df-4e39-ba0b-c7259431372c):\\nTraceback (most recent call last):\\nF... | 2015-12-04 23:41:33,959 ERROR [MpdSession-13] /home/adamcik/dev/mopidy-virtualenv/local/lib/python2.7/site-packages/pykka/actor.py:269
pykka Unhandled exception in MpdSession (urn:uuid:093fbff0-33df-4e39-ba0b-c7259431372c):
Traceback (most recent call last):
File "/home/adamcik/dev/mopidy-virtualenv/local/lib/python... | ValidationError |
def _get_library(args, config):
libraries = dict((l.name, l) for l in args.registry['local:library'])
library_name = config['local']['library']
if library_name not in libraries:
logger.error('Local library %s not found', library_name)
return None
logger.debug('Using %s as the local lib... | def _get_library(args, config):
libraries = dict((l.name, l) for l in args.registry['local:library'])
library_name = config['local']['library']
if library_name not in libraries:
logger.warning('Local library %s not found', library_name)
return 1
logger.debug('Using %s as the local libr... | [{'piece_type': 'error message', 'piece_content': 'INFO Starting Mopidy 1.1.1\\nINFO Loading config from builtin defaults\\nINFO Loading config from /etc/mopidy/mopidy.conf\\nINFO Loading config from command line options\\nINFO Enabled extensions: mpd, http, stream, podcast-gpodder, m3u, podcast-itu... | INFO Starting Mopidy 1.1.1
INFO Loading config from builtin defaults
INFO Loading config from /etc/mopidy/mopidy.conf
INFO Loading config from command line options
INFO Enabled extensions: mpd, http, stream, podcast-gpodder, m3u, podcast-itunes, softwaremixer, file, musicbox_webclient, podcast, loca... | AttributeError |
def run(self, args, config):
library = _get_library(args, config)
if library is None:
return 1
prompt = '\\nAre you sure you want to clear the library? [y/N] '
if compat.input(prompt).lower() != 'y':
print('Clearing library aborted.')
return 0
... | def run(self, args, config):
library = _get_library(args, config)
prompt = '\\nAre you sure you want to clear the library? [y/N] '
if compat.input(prompt).lower() != 'y':
print('Clearing library aborted.')
return 0
if library.clear():
print('Libr... | [{'piece_type': 'error message', 'piece_content': 'INFO Starting Mopidy 1.1.1\\nINFO Loading config from builtin defaults\\nINFO Loading config from /etc/mopidy/mopidy.conf\\nINFO Loading config from command line options\\nINFO Enabled extensions: mpd, http, stream, podcast-gpodder, m3u, podcast-itu... | INFO Starting Mopidy 1.1.1
INFO Loading config from builtin defaults
INFO Loading config from /etc/mopidy/mopidy.conf
INFO Loading config from command line options
INFO Enabled extensions: mpd, http, stream, podcast-gpodder, m3u, podcast-itunes, softwaremixer, file, musicbox_webclient, podcast, loca... | AttributeError |
def run(self, args, config):
media_dir = config['local']['media_dir']
scan_timeout = config['local']['scan_timeout']
flush_threshold = config['local']['scan_flush_threshold']
excluded_file_extensions = config['local']['excluded_file_extensions']
excluded_file_extensions = tup... | def run(self, args, config):
media_dir = config['local']['media_dir']
scan_timeout = config['local']['scan_timeout']
flush_threshold = config['local']['scan_flush_threshold']
excluded_file_extensions = config['local']['excluded_file_extensions']
excluded_file_extensions = tup... | [{'piece_type': 'error message', 'piece_content': 'INFO Starting Mopidy 1.1.1\\nINFO Loading config from builtin defaults\\nINFO Loading config from /etc/mopidy/mopidy.conf\\nINFO Loading config from command line options\\nINFO Enabled extensions: mpd, http, stream, podcast-gpodder, m3u, podcast-itu... | INFO Starting Mopidy 1.1.1
INFO Loading config from builtin defaults
INFO Loading config from /etc/mopidy/mopidy.conf
INFO Loading config from command line options
INFO Enabled extensions: mpd, http, stream, podcast-gpodder, m3u, podcast-itunes, softwaremixer, file, musicbox_webclient, podcast, loca... | AttributeError |
def parse_urilist(data):
result = []
for line in data.splitlines():
if not line.strip() or line.startswith(b'#'):
continue
try:
validation.check_uri(line)
except ValueError:
return []
result.append(line)
return result | def parse_urilist(data):
result = []
for line in data.splitlines():
if not line.strip() or line.startswith('#'):
continue
try:
validation.check_uri(line)
except ValueError:
return []
result.append(line)
return result | [{'piece_type': 'error message', 'piece_content': 'INFO 2015-08-22 22:19:26,991 [855:MpdSession-31] mopidy.mpd.session\\nNew MPD connection from [::ffff:127.0.0.1]:50701\\nDEBUG 2015-08-22 22:19:26,993 [855:MpdSession-31] mopidy.mpd.session\\nRequest from [::ffff:127.0.0.1]:50701: command_list_begin\\nDEBUG 2... | INFO 2015-08-22 22:19:26,991 [855:MpdSession-31] mopidy.mpd.session
New MPD connection from [::ffff:127.0.0.1]:50701
DEBUG 2015-08-22 22:19:26,993 [855:MpdSession-31] mopidy.mpd.session
Request from [::ffff:127.0.0.1]:50701: command_list_begin
DEBUG 2015-08-22 22:19:26,993 [855:MpdSession-31] mopidy.mpd.sessi... | UnicodeDecodeError |
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