05c - OOM
raybellwaves opened this issue · comments
Running
base_model = keras.applications.resnet.ResNet50(weights='imagenet', include_top=False, input_shape=(224,224,3))
Gives
InternalError: CUDA runtime implicit initialization on GPU:0 failed. Status: out of memory
Full Traceback and enviornment below
TensorFlow version: 2.3.1
Keras version: 2.4.0
Note i'm running locally and I do have a GPU so not sure if that is the cause
---------------------------------------------------------------------------
InternalError Traceback (most recent call last)
<ipython-input-4-50b0035545e7> in <module>
----> 1 base_model = keras.applications.resnet.ResNet50(weights='imagenet', include_top=False, input_shape=(224,224,3))
2 print(base_model.summary())
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/keras/applications/resnet.py in ResNet50(include_top, weights, input_tensor, input_shape, pooling, classes, **kwargs)
473
474 return ResNet(stack_fn, False, True, 'resnet50', include_top, weights,
--> 475 input_tensor, input_shape, pooling, classes, **kwargs)
476
477
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/keras/applications/resnet.py in ResNet(stack_fn, preact, use_bias, model_name, include_top, weights, input_tensor, input_shape, pooling, classes, classifier_activation, **kwargs)
169 x = layers.ZeroPadding2D(
170 padding=((3, 3), (3, 3)), name='conv1_pad')(img_input)
--> 171 x = layers.Conv2D(64, 7, strides=2, use_bias=use_bias, name='conv1_conv')(x)
172
173 if not preact:
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, *args, **kwargs)
924 if _in_functional_construction_mode(self, inputs, args, kwargs, input_list):
925 return self._functional_construction_call(inputs, args, kwargs,
--> 926 input_list)
927
928 # Maintains info about the `Layer.call` stack.
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in _functional_construction_call(self, inputs, args, kwargs, input_list)
1096 # Build layer if applicable (if the `build` method has been
1097 # overridden).
-> 1098 self._maybe_build(inputs)
1099 cast_inputs = self._maybe_cast_inputs(inputs, input_list)
1100
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in _maybe_build(self, inputs)
2641 # operations.
2642 with tf_utils.maybe_init_scope(self):
-> 2643 self.build(input_shapes) # pylint:disable=not-callable
2644 # We must set also ensure that the layer is marked as built, and the build
2645 # shape is stored since user defined build functions may not be calling
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/keras/layers/convolutional.py in build(self, input_shape)
202 constraint=self.kernel_constraint,
203 trainable=True,
--> 204 dtype=self.dtype)
205 if self.use_bias:
206 self.bias = self.add_weight(
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in add_weight(self, name, shape, dtype, initializer, regularizer, trainable, constraint, partitioner, use_resource, synchronization, aggregation, **kwargs)
612 synchronization=synchronization,
613 aggregation=aggregation,
--> 614 caching_device=caching_device)
615 if regularizer is not None:
616 # TODO(fchollet): in the future, this should be handled at the
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/training/tracking/base.py in _add_variable_with_custom_getter(self, name, shape, dtype, initializer, getter, overwrite, **kwargs_for_getter)
748 dtype=dtype,
749 initializer=initializer,
--> 750 **kwargs_for_getter)
751
752 # If we set an initializer and the variable processed it, tracking will not
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer_utils.py in make_variable(name, shape, dtype, initializer, trainable, caching_device, validate_shape, constraint, use_resource, collections, synchronization, aggregation, partitioner)
143 synchronization=synchronization,
144 aggregation=aggregation,
--> 145 shape=variable_shape if variable_shape else None)
146
147
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/ops/variables.py in __call__(cls, *args, **kwargs)
258 def __call__(cls, *args, **kwargs):
259 if cls is VariableV1:
--> 260 return cls._variable_v1_call(*args, **kwargs)
261 elif cls is Variable:
262 return cls._variable_v2_call(*args, **kwargs)
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/ops/variables.py in _variable_v1_call(cls, initial_value, trainable, collections, validate_shape, caching_device, name, variable_def, dtype, expected_shape, import_scope, constraint, use_resource, synchronization, aggregation, shape)
219 synchronization=synchronization,
220 aggregation=aggregation,
--> 221 shape=shape)
222
223 def _variable_v2_call(cls,
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/ops/variables.py in <lambda>(**kwargs)
197 shape=None):
198 """Call on Variable class. Useful to force the signature."""
--> 199 previous_getter = lambda **kwargs: default_variable_creator(None, **kwargs)
200 for _, getter in ops.get_default_graph()._variable_creator_stack: # pylint: disable=protected-access
201 previous_getter = _make_getter(getter, previous_getter)
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/ops/variable_scope.py in default_variable_creator(next_creator, **kwargs)
2595 synchronization=synchronization,
2596 aggregation=aggregation,
-> 2597 shape=shape)
2598 else:
2599 return variables.RefVariable(
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/ops/variables.py in __call__(cls, *args, **kwargs)
262 return cls._variable_v2_call(*args, **kwargs)
263 else:
--> 264 return super(VariableMetaclass, cls).__call__(*args, **kwargs)
265
266
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/ops/resource_variable_ops.py in __init__(self, initial_value, trainable, collections, validate_shape, caching_device, name, dtype, variable_def, import_scope, constraint, distribute_strategy, synchronization, aggregation, shape)
1516 aggregation=aggregation,
1517 shape=shape,
-> 1518 distribute_strategy=distribute_strategy)
1519
1520 def _init_from_args(self,
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/ops/resource_variable_ops.py in _init_from_args(self, initial_value, trainable, collections, caching_device, name, dtype, constraint, synchronization, aggregation, distribute_strategy, shape)
1649 with ops.name_scope("Initializer"), device_context_manager(None):
1650 initial_value = ops.convert_to_tensor(
-> 1651 initial_value() if init_from_fn else initial_value,
1652 name="initial_value", dtype=dtype)
1653 if shape is not None:
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/keras/initializers/initializers_v2.py in __call__(self, shape, dtype)
395 (via `tf.keras.backend.set_floatx(float_dtype)`)
396 """
--> 397 return super(VarianceScaling, self).__call__(shape, dtype=_get_dtype(dtype))
398
399
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/ops/init_ops_v2.py in __call__(self, shape, dtype)
559 else:
560 limit = math.sqrt(3.0 * scale)
--> 561 return self._random_generator.random_uniform(shape, -limit, limit, dtype)
562
563 def get_config(self):
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/ops/init_ops_v2.py in random_uniform(self, shape, minval, maxval, dtype)
1042 op = random_ops.random_uniform
1043 return op(
-> 1044 shape=shape, minval=minval, maxval=maxval, dtype=dtype, seed=self.seed)
1045
1046 def truncated_normal(self, shape, mean, stddev, dtype):
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/util/dispatch.py in wrapper(*args, **kwargs)
199 """Call target, and fall back on dispatchers if there is a TypeError."""
200 try:
--> 201 return target(*args, **kwargs)
202 except (TypeError, ValueError):
203 # Note: convert_to_eager_tensor currently raises a ValueError, not a
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/ops/random_ops.py in random_uniform(shape, minval, maxval, dtype, seed, name)
286 maxval = 1
287 with ops.name_scope(name, "random_uniform", [shape, minval, maxval]) as name:
--> 288 shape = tensor_util.shape_tensor(shape)
289 # In case of [0,1) floating results, minval and maxval is unused. We do an
290 # `is` comparison here since this is cheaper than isinstance or __eq__.
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/framework/tensor_util.py in shape_tensor(shape)
1027 # not convertible to Tensors because of mixed content.
1028 shape = tuple(map(tensor_shape.dimension_value, shape))
-> 1029 return ops.convert_to_tensor(shape, dtype=dtype, name="shape")
1030
1031
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in convert_to_tensor(value, dtype, name, as_ref, preferred_dtype, dtype_hint, ctx, accepted_result_types)
1497
1498 if ret is None:
-> 1499 ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
1500
1501 if ret is NotImplemented:
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py in _constant_tensor_conversion_function(v, dtype, name, as_ref)
336 as_ref=False):
337 _ = as_ref
--> 338 return constant(v, dtype=dtype, name=name)
339
340
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py in constant(value, dtype, shape, name)
262 """
263 return _constant_impl(value, dtype, shape, name, verify_shape=False,
--> 264 allow_broadcast=True)
265
266
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py in _constant_impl(value, dtype, shape, name, verify_shape, allow_broadcast)
273 with trace.Trace("tf.constant"):
274 return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
--> 275 return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
276
277 g = ops.get_default_graph()
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py in _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
298 def _constant_eager_impl(ctx, value, dtype, shape, verify_shape):
299 """Implementation of eager constant."""
--> 300 t = convert_to_eager_tensor(value, ctx, dtype)
301 if shape is None:
302 return t
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py in convert_to_eager_tensor(value, ctx, dtype)
95 except AttributeError:
96 dtype = dtypes.as_dtype(dtype).as_datatype_enum
---> 97 ctx.ensure_initialized()
98 return ops.EagerTensor(value, ctx.device_name, dtype)
99
~/local/bin/anaconda3/envs/ml-basics/lib/python3.7/site-packages/tensorflow/python/eager/context.py in ensure_initialized(self)
537 if self._use_tfrt is not None:
538 pywrap_tfe.TFE_ContextOptionsSetTfrt(opts, self._use_tfrt)
--> 539 context_handle = pywrap_tfe.TFE_NewContext(opts)
540 finally:
541 pywrap_tfe.TFE_DeleteContextOptions(opts)
InternalError: CUDA runtime implicit initialization on GPU:0 failed. Status: out of memory
(ml-basics) ray@ray-MS-7B43:~$ conda list
# packages in environment at /home/ray/local/bin/anaconda3/envs/ml-basics:
#
# Name Version Build Channel
_libgcc_mutex 0.1 main
absl-py 0.10.0 pypi_0 pypi
argon2-cffi 20.1.0 pypi_0 pypi
astunparse 1.6.3 pypi_0 pypi
async-generator 1.10 pypi_0 pypi
attrs 20.2.0 pypi_0 pypi
backcall 0.2.0 pypi_0 pypi
bleach 3.2.1 pypi_0 pypi
ca-certificates 2020.7.22 0
cachetools 4.1.1 pypi_0 pypi
certifi 2020.6.20 py37_0
cffi 1.14.3 pypi_0 pypi
chardet 3.0.4 pypi_0 pypi
cycler 0.10.0 pypi_0 pypi
decorator 4.4.2 pypi_0 pypi
defusedxml 0.6.0 pypi_0 pypi
entrypoints 0.3 pypi_0 pypi
future 0.18.2 pypi_0 pypi
gast 0.3.3 pypi_0 pypi
google-auth 1.22.1 pypi_0 pypi
google-auth-oauthlib 0.4.1 pypi_0 pypi
google-pasta 0.2.0 pypi_0 pypi
grpcio 1.32.0 pypi_0 pypi
h5py 2.10.0 pypi_0 pypi
idna 2.10 pypi_0 pypi
imageio 2.9.0 pypi_0 pypi
importlib-metadata 2.0.0 pypi_0 pypi
ipykernel 5.3.4 pypi_0 pypi
ipython 7.18.1 pypi_0 pypi
ipython-genutils 0.2.0 pypi_0 pypi
ipywidgets 7.5.1 pypi_0 pypi
jedi 0.17.2 pypi_0 pypi
jinja2 2.11.2 pypi_0 pypi
joblib 0.17.0 pypi_0 pypi
jsonschema 3.2.0 pypi_0 pypi
jupyter 1.0.0 pypi_0 pypi
jupyter-client 6.1.7 pypi_0 pypi
jupyter-console 6.2.0 pypi_0 pypi
jupyter-core 4.6.3 pypi_0 pypi
jupyterlab-pygments 0.1.2 pypi_0 pypi
keras-preprocessing 1.1.2 pypi_0 pypi
kiwisolver 1.2.0 pypi_0 pypi
ld_impl_linux-64 2.33.1 h53a641e_7
libedit 3.1.20191231 h14c3975_1
libffi 3.3 he6710b0_2
libgcc-ng 9.1.0 hdf63c60_0
libstdcxx-ng 9.1.0 hdf63c60_0
markdown 3.3.1 pypi_0 pypi
markupsafe 1.1.1 pypi_0 pypi
matplotlib 3.3.2 pypi_0 pypi
mistune 0.8.4 pypi_0 pypi
nbclient 0.5.0 pypi_0 pypi
nbconvert 6.0.7 pypi_0 pypi
nbformat 5.0.7 pypi_0 pypi
ncurses 6.2 he6710b0_1
nest-asyncio 1.4.1 pypi_0 pypi
networkx 2.5 pypi_0 pypi
notebook 6.1.4 pypi_0 pypi
oauthlib 3.1.0 pypi_0 pypi
openssl 1.1.1h h7b6447c_0
opt-einsum 3.3.0 pypi_0 pypi
packaging 20.4 pypi_0 pypi
pandas 1.1.3 pypi_0 pypi
pandocfilters 1.4.2 pypi_0 pypi
parso 0.7.1 pypi_0 pypi
pexpect 4.8.0 pypi_0 pypi
pickleshare 0.7.5 pypi_0 pypi
pillow 7.2.0 pypi_0 pypi
pip 20.2.3 py37_0
prometheus-client 0.8.0 pypi_0 pypi
prompt-toolkit 3.0.8 pypi_0 pypi
protobuf 3.13.0 pypi_0 pypi
ptyprocess 0.6.0 pypi_0 pypi
pyasn1 0.4.8 pypi_0 pypi
pyasn1-modules 0.2.8 pypi_0 pypi
pycparser 2.20 pypi_0 pypi
pygments 2.7.1 pypi_0 pypi
pyparsing 2.4.7 pypi_0 pypi
pyrsistent 0.17.3 pypi_0 pypi
python 3.7.9 h7579374_0
python-dateutil 2.8.1 pypi_0 pypi
pytz 2020.1 pypi_0 pypi
pywavelets 1.1.1 pypi_0 pypi
pyzmq 19.0.2 pypi_0 pypi
qtconsole 4.7.7 pypi_0 pypi
qtpy 1.9.0 pypi_0 pypi
readline 8.0 h7b6447c_0
requests 2.24.0 pypi_0 pypi
requests-oauthlib 1.3.0 pypi_0 pypi
rsa 4.6 pypi_0 pypi
scikit-image 0.17.2 pypi_0 pypi
scikit-learn 0.23.2 pypi_0 pypi
scipy 1.5.2 pypi_0 pypi
send2trash 1.5.0 pypi_0 pypi
setuptools 50.3.0 py37hb0f4dca_1
sqlite 3.33.0 h62c20be_0
tensorboard 2.3.0 pypi_0 pypi
tensorboard-plugin-wit 1.7.0 pypi_0 pypi
tensorflow 2.3.1 pypi_0 pypi
tensorflow-estimator 2.3.0 pypi_0 pypi
termcolor 1.1.0 pypi_0 pypi
terminado 0.9.1 pypi_0 pypi
testpath 0.4.4 pypi_0 pypi
threadpoolctl 2.1.0 pypi_0 pypi
tifffile 2020.10.1 pypi_0 pypi
tk 8.6.10 hbc83047_0
torch 1.6.0+cpu pypi_0 pypi
torchvision 0.7.0+cpu pypi_0 pypi
tornado 6.0.4 pypi_0 pypi
traitlets 5.0.4 pypi_0 pypi
urllib3 1.25.10 pypi_0 pypi
wcwidth 0.2.5 pypi_0 pypi
webencodings 0.5.1 pypi_0 pypi
werkzeug 1.0.1 pypi_0 pypi
wheel 0.35.1 py_0
widgetsnbextension 3.5.1 pypi_0 pypi
wrapt 1.12.1 pypi_0 pypi
xz 5.2.5 h7b6447c_0
zipp 3.3.0 pypi_0 pypi
zlib 1.2.11 h7b6447c_3
Note I also tried in a fresh env using tensorflow-gpu and got the same error.
(tf) ray@ray-MS-7B43:~$ conda list
# packages in environment at /home/ray/local/bin/anaconda3/envs/tf:
#
# Name Version Build Channel
_libgcc_mutex 0.1 main
absl-py 0.10.0 pypi_0 pypi
argon2-cffi 20.1.0 pypi_0 pypi
astunparse 1.6.3 pypi_0 pypi
async-generator 1.10 pypi_0 pypi
attrs 20.2.0 pypi_0 pypi
backcall 0.2.0 pypi_0 pypi
bleach 3.2.1 pypi_0 pypi
ca-certificates 2020.10.14 0
cachetools 4.1.1 pypi_0 pypi
certifi 2020.6.20 py38_0
cffi 1.14.3 pypi_0 pypi
chardet 3.0.4 pypi_0 pypi
cycler 0.10.0 pypi_0 pypi
decorator 4.4.2 pypi_0 pypi
defusedxml 0.6.0 pypi_0 pypi
entrypoints 0.3 pypi_0 pypi
gast 0.3.3 pypi_0 pypi
google-auth 1.22.1 pypi_0 pypi
google-auth-oauthlib 0.4.1 pypi_0 pypi
google-pasta 0.2.0 pypi_0 pypi
grpcio 1.32.0 pypi_0 pypi
h5py 2.10.0 pypi_0 pypi
idna 2.10 pypi_0 pypi
ipykernel 5.3.4 pypi_0 pypi
ipython 7.18.1 pypi_0 pypi
ipython-genutils 0.2.0 pypi_0 pypi
ipywidgets 7.5.1 pypi_0 pypi
jedi 0.17.2 pypi_0 pypi
jinja2 2.11.2 pypi_0 pypi
joblib 0.17.0 pypi_0 pypi
jsonschema 3.2.0 pypi_0 pypi
jupyter 1.0.0 pypi_0 pypi
jupyter-client 6.1.7 pypi_0 pypi
jupyter-console 6.2.0 pypi_0 pypi
jupyter-core 4.6.3 pypi_0 pypi
jupyterlab-pygments 0.1.2 pypi_0 pypi
keras-preprocessing 1.1.2 pypi_0 pypi
kiwisolver 1.2.0 pypi_0 pypi
ld_impl_linux-64 2.33.1 h53a641e_7
libedit 3.1.20191231 h14c3975_1
libffi 3.3 he6710b0_2
libgcc-ng 9.1.0 hdf63c60_0
libstdcxx-ng 9.1.0 hdf63c60_0
markdown 3.3.1 pypi_0 pypi
markupsafe 1.1.1 pypi_0 pypi
matplotlib 3.3.2 pypi_0 pypi
mistune 0.8.4 pypi_0 pypi
nbclient 0.5.1 pypi_0 pypi
nbconvert 6.0.7 pypi_0 pypi
nbformat 5.0.8 pypi_0 pypi
ncurses 6.2 he6710b0_1
nest-asyncio 1.4.1 pypi_0 pypi
notebook 6.1.4 pypi_0 pypi
numpy 1.18.5 pypi_0 pypi
oauthlib 3.1.0 pypi_0 pypi
openssl 1.1.1h h7b6447c_0
opt-einsum 3.3.0 pypi_0 pypi
packaging 20.4 pypi_0 pypi
pandas 1.1.3 pypi_0 pypi
pandocfilters 1.4.2 pypi_0 pypi
parso 0.7.1 pypi_0 pypi
pexpect 4.8.0 pypi_0 pypi
pickleshare 0.7.5 pypi_0 pypi
pillow 8.0.0 pypi_0 pypi
pip 20.2.3 py38_0
prometheus-client 0.8.0 pypi_0 pypi
prompt-toolkit 3.0.8 pypi_0 pypi
protobuf 3.13.0 pypi_0 pypi
ptyprocess 0.6.0 pypi_0 pypi
pyasn1 0.4.8 pypi_0 pypi
pyasn1-modules 0.2.8 pypi_0 pypi
pycparser 2.20 pypi_0 pypi
pygments 2.7.1 pypi_0 pypi
pyparsing 2.4.7 pypi_0 pypi
pyrsistent 0.17.3 pypi_0 pypi
python 3.8.5 h7579374_1
python-dateutil 2.8.1 pypi_0 pypi
pytz 2020.1 pypi_0 pypi
pyzmq 19.0.2 pypi_0 pypi
qtconsole 4.7.7 pypi_0 pypi
qtpy 1.9.0 pypi_0 pypi
readline 8.0 h7b6447c_0
requests 2.24.0 pypi_0 pypi
requests-oauthlib 1.3.0 pypi_0 pypi
rsa 4.6 pypi_0 pypi
scikit-learn 0.23.2 pypi_0 pypi
scipy 1.5.2 pypi_0 pypi
send2trash 1.5.0 pypi_0 pypi
setuptools 50.3.0 py38hb0f4dca_1
six 1.15.0 pypi_0 pypi
sqlite 3.33.0 h62c20be_0
tensorboard 2.3.0 pypi_0 pypi
tensorboard-plugin-wit 1.7.0 pypi_0 pypi
tensorflow-estimator 2.3.0 pypi_0 pypi
tensorflow-gpu 2.3.1 pypi_0 pypi
termcolor 1.1.0 pypi_0 pypi
terminado 0.9.1 pypi_0 pypi
testpath 0.4.4 pypi_0 pypi
threadpoolctl 2.1.0 pypi_0 pypi
tk 8.6.10 hbc83047_0
tornado 6.0.4 pypi_0 pypi
traitlets 5.0.5 pypi_0 pypi
urllib3 1.25.10 pypi_0 pypi
wcwidth 0.2.5 pypi_0 pypi
webencodings 0.5.1 pypi_0 pypi
werkzeug 1.0.1 pypi_0 pypi
wheel 0.35.1 py_0
widgetsnbextension 3.5.1 pypi_0 pypi
wrapt 1.12.1 pypi_0 pypi
xz 5.2.5 h7b6447c_0
zlib 1.2.11 h7b6447c_3
Non-repro in the recommended Standard_DS11_v2 Compute Instance setup.
Confirming fine on Azure ML
