"Collaborative Filtering on Google Analytics data" lab fails with `NotImplementedError: Cannot convert a symbolic Tensor (cond_1/strided_slice_4:0) to a numpy array.` #2441

MrCsabaToth · 2023-09-13T19:43:06Z

Just like the lab in #2439 this one (https://www.cloudskillsboost.google/course_sessions/2920313/labs/325084) is also part of the recommendation course (of the Professional Machine Learning Engineer Path), and also uses 1.15 TF. It set off on the right foot by using a CLI command to instantiate the Vertex AI Workbench Anaconda VM, since 1.15 TF is not selectable on the User Managed Notebook creation GUI any more.

The notebook spews warnings left and right (which we can usually ignore), but it failed at the Run as a Python module step's gcloud ai-platform local train CLI step. The root cause looked to be NotImplementedError: Cannot convert a symbolic Tensor (cond_1/strided_slice_4:0) to a numpy array.

WARNING:tensorflow:From /home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/walsmodel/model.py:27: The name tf.logging.set_verbosity is deprecated. Please use tf.compat.v1.logging.set_verbosity instead.

WARNING:tensorflow:From /home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/walsmodel/model.py:27: The name tf.logging.INFO is deprecated. Please use tf.compat.v1.logging.INFO instead.

WARNING:tensorflow:From /home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/walsmodel/model.py:198: run (from tensorflow.contrib.learn.python.learn.learn_runner) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.estimator.train_and_evaluate.
WARNING:tensorflow:
The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
  * https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.

WARNING:tensorflow:From /opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/estimators/estimator.py:1180: BaseEstimator.__init__ (from tensorflow.contrib.learn.python.learn.estimators.estimator) is deprecated and will be removed in a future version.
Instructions for updating:
Please replace uses of any Estimator from tf.contrib.learn with an Estimator from tf.estimator.*
WARNING:tensorflow:From /opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/estimators/estimator.py:427: RunConfig.__init__ (from tensorflow.contrib.learn.python.learn.estimators.run_config) is deprecated and will be removed in a future version.
Instructions for updating:
When switching to tf.estimator.Estimator, use tf.estimator.RunConfig instead.
INFO:tensorflow:Using default config.
INFO:tensorflow:Using config: {'_task_type': None, '_task_id': 0, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f8ca98dce90>, '_master': '', '_num_ps_replicas': 0, '_num_worker_replicas': 0, '_environment': 'cloud', '_is_chief': True, '_evaluation_master': '', '_train_distribute': None, '_eval_distribute': None, '_experimental_max_worker_delay_secs': None, '_device_fn': None, '_tf_config': gpu_options {
  per_process_gpu_memory_fraction: 1.0
}
, '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_secs': 600, '_log_step_count_steps': 100, '_protocol': None, '_session_config': None, '_save_checkpoints_steps': None, '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_model_dir': '/home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/wals_trained/', '_session_creation_timeout_secs': 7200}
WARNING:tensorflow:From /home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/walsmodel/model.py:194: make_export_strategy (from tensorflow.contrib.learn.python.learn.utils.saved_model_export_utils) is deprecated and will be removed in a future version.
Instructions for updating:
Switch to tf.estimator.Exporter and associated utilities.
WARNING:tensorflow:From /opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/utils/saved_model_export_utils.py:484: ExportStrategy.__new__ (from tensorflow.contrib.learn.python.learn.export_strategy) is deprecated and will be removed in a future version.
Instructions for updating:
Please switch to tf.estimator.train_and_evaluate, and use tf.estimator.Exporter.
WARNING:tensorflow:From /home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/walsmodel/model.py:194: Experiment.__init__ (from tensorflow.contrib.learn.python.learn.experiment) is deprecated and will be removed in a future version.
Instructions for updating:
Please switch to tf.estimator.train_and_evaluate. You will also have to convert to a tf.estimator.Estimator.
WARNING:tensorflow:From /opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/monitors.py:279: BaseMonitor.__init__ (from tensorflow.contrib.learn.python.learn.monitors) is deprecated and will be removed after 2016-12-05.
Instructions for updating:
Monitors are deprecated. Please use tf.train.SessionRunHook.
WARNING:tensorflow:From /home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/walsmodel/model.py:85: The name tf.gfile.Glob is deprecated. Please use tf.io.gfile.glob instead.

WARNING:tensorflow:From /opt/conda/lib/python3.7/site-packages/tensorflow_core/python/autograph/converters/directives.py:119: The name tf.FixedLenFeature is deprecated. Please use tf.io.FixedLenFeature instead.

WARNING:tensorflow:From /opt/conda/lib/python3.7/site-packages/tensorflow_core/python/autograph/converters/directives.py:119: The name tf.VarLenFeature is deprecated. Please use tf.io.VarLenFeature instead.

WARNING:tensorflow:From /opt/conda/lib/python3.7/site-packages/tensorflow_core/python/autograph/converters/directives.py:119: The name tf.parse_single_example is deprecated. Please use tf.io.parse_single_example instead.

WARNING:tensorflow:From /home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/walsmodel/model.py:41: sparse_merge (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.
Instructions for updating:
No similar op available at this time.
WARNING:tensorflow:From /opt/conda/lib/python3.7/site-packages/tensorflow_core/python/ops/array_ops.py:1475: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
WARNING:tensorflow:From /home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/walsmodel/model.py:93: DatasetV1.make_one_shot_iterator (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `for ... in dataset:` to iterate over a dataset. If using `tf.estimator`, return the `Dataset` object directly from your input function. As a last resort, you can use `tf.compat.v1.data.make_one_shot_iterator(dataset)`.
WARNING:tensorflow:From /opt/conda/lib/python3.7/site-packages/tensorflow_core/python/training/training_util.py:236: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version.
Instructions for updating:
Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts.
WARNING:tensorflow:From /opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/factorization/python/ops/wals.py:315: ModelFnOps.__new__ (from tensorflow.contrib.learn.python.learn.estimators.model_fn) is deprecated and will be removed in a future version.
Instructions for updating:
When switching to tf.estimator.Estimator, use tf.estimator.EstimatorSpec. You can use the `estimator_spec` method to create an equivalent one.
INFO:tensorflow:Create CheckpointSaverHook.
INFO:tensorflow:Graph was finalized.

User settings:

   KMP_AFFINITY=granularity=fine,verbose,compact,1,0
   KMP_BLOCKTIME=0
   KMP_DUPLICATE_LIB_OK=True
   KMP_INIT_AT_FORK=FALSE
   KMP_SETTINGS=1
   OMP_NUM_THREADS=1

Effective settings:

   KMP_ABORT_DELAY=0
   KMP_ADAPTIVE_LOCK_PROPS='1,1024'
   KMP_ALIGN_ALLOC=64
   KMP_ALL_THREADPRIVATE=128
   KMP_ATOMIC_MODE=2
   KMP_BLOCKTIME=0
   KMP_CPUINFO_FILE: value is not defined
   KMP_DETERMINISTIC_REDUCTION=false
   KMP_DEVICE_THREAD_LIMIT=2147483647
   KMP_DISP_HAND_THREAD=false
   KMP_DISP_NUM_BUFFERS=7
   KMP_DUPLICATE_LIB_OK=true
   KMP_FORCE_REDUCTION: value is not defined
   KMP_FOREIGN_THREADS_THREADPRIVATE=true
   KMP_FORKJOIN_BARRIER='2,2'
   KMP_FORKJOIN_BARRIER_PATTERN='hyper,hyper'
   KMP_FORKJOIN_FRAMES=true
   KMP_FORKJOIN_FRAMES_MODE=3
   KMP_GTID_MODE=3
   KMP_HANDLE_SIGNALS=false
   KMP_HOT_TEAMS_MAX_LEVEL=1
   KMP_HOT_TEAMS_MODE=0
   KMP_INIT_AT_FORK=true
   KMP_ITT_PREPARE_DELAY=0
   KMP_LIBRARY=throughput
   KMP_LOCK_KIND=queuing
   KMP_MALLOC_POOL_INCR=1M
   KMP_MWAIT_HINTS=0
   KMP_NUM_LOCKS_IN_BLOCK=1
   KMP_PLAIN_BARRIER='2,2'
   KMP_PLAIN_BARRIER_PATTERN='hyper,hyper'
   KMP_REDUCTION_BARRIER='1,1'
   KMP_REDUCTION_BARRIER_PATTERN='hyper,hyper'
   KMP_SCHEDULE='static,balanced;guided,iterative'
   KMP_SETTINGS=true
   KMP_SPIN_BACKOFF_PARAMS='4096,100'
   KMP_STACKOFFSET=64
   KMP_STACKPAD=0
   KMP_STACKSIZE=8M
   KMP_STORAGE_MAP=false
   KMP_TASKING=2
   KMP_TASKLOOP_MIN_TASKS=0
   KMP_TASK_STEALING_CONSTRAINT=1
   KMP_TEAMS_THREAD_LIMIT=1
   KMP_TOPOLOGY_METHOD=all
   KMP_USER_LEVEL_MWAIT=false
   KMP_USE_YIELD=1
   KMP_VERSION=false
   KMP_WARNINGS=true
   OMP_AFFINITY_FORMAT='OMP: pid %P tid %i thread %n bound to OS proc set {%A}'
   OMP_ALLOCATOR=omp_default_mem_alloc
   OMP_CANCELLATION=false
   OMP_DEBUG=disabled
   OMP_DEFAULT_DEVICE=0
   OMP_DISPLAY_AFFINITY=false
   OMP_DISPLAY_ENV=false
   OMP_DYNAMIC=false
   OMP_MAX_ACTIVE_LEVELS=2147483647
   OMP_MAX_TASK_PRIORITY=0
   OMP_NESTED=false
   OMP_NUM_THREADS='1'
   OMP_PLACES: value is not defined
   OMP_PROC_BIND='intel'
   OMP_SCHEDULE='static'
   OMP_STACKSIZE=8M
   OMP_TARGET_OFFLOAD=DEFAULT
   OMP_THREAD_LIMIT=2147483647
   OMP_TOOL=enabled
   OMP_TOOL_LIBRARIES: value is not defined
   OMP_WAIT_POLICY=PASSIVE
   KMP_AFFINITY='verbose,warnings,respect,granularity=fine,compact,1,0'

2023-09-13 19:24:41.488800: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2299995000 Hz
2023-09-13 19:24:41.488984: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x556f96f35350 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2023-09-13 19:24:41.489018: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2023-09-13 19:24:41.489118: I tensorflow/core/common_runtime/process_util.cc:136] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.
INFO:tensorflow:Running local_init_op.
INFO:tensorflow:Done running local_init_op.
INFO:tensorflow:Saving checkpoints for 0 into /home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/wals_trained/model.ckpt.
INFO:tensorflow:SweepHook running init op.
INFO:tensorflow:SweepHook running prep ops for the row sweep.
OMP: Info #212: KMP_AFFINITY: decoding x2APIC ids.
OMP: Info #210: KMP_AFFINITY: Affinity capable, using global cpuid leaf 11 info
OMP: Info #154: KMP_AFFINITY: Initial OS proc set respected: 0
OMP: Info #156: KMP_AFFINITY: 1 available OS procs
OMP: Info #157: KMP_AFFINITY: Uniform topology
OMP: Info #159: KMP_AFFINITY: 1 packages x 1 cores/pkg x 1 threads/core (1 total cores)
OMP: Info #214: KMP_AFFINITY: OS proc to physical thread map:
OMP: Info #171: KMP_AFFINITY: OS proc 0 maps to package 0 
OMP: Info #250: KMP_AFFINITY: pid 2369 tid 2396 thread 0 bound to OS proc set 0
OMP: Info #250: KMP_AFFINITY: pid 2369 tid 2396 thread 1 bound to OS proc set 0
INFO:tensorflow:Next fit step starting.
OMP: Info #250: KMP_AFFINITY: pid 2369 tid 2398 thread 2 bound to OS proc set 0
OMP: Info #250: KMP_AFFINITY: pid 2369 tid 2395 thread 3 bound to OS proc set 0
INFO:tensorflow:loss = 171085.25, step = 1
INFO:tensorflow:Next fit step starting.
INFO:tensorflow:Saving checkpoints for 2 into /home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/wals_trained/model.ckpt.
INFO:tensorflow:Loss for final step: 170297.7.
INFO:tensorflow:Starting evaluation at 2023-09-13T19:24:43Z
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from /home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/wals_trained/model.ckpt-2
INFO:tensorflow:Running local_init_op.
INFO:tensorflow:Done running local_init_op.
OMP: Info #250: KMP_AFFINITY: pid 2369 tid 2440 thread 2 bound to OS proc set 0
INFO:tensorflow:Evaluation [1/1]
INFO:tensorflow:Finished evaluation at 2023-09-13-19:24:44
INFO:tensorflow:Saving dict for global step 2: global_step = 2, loss = 171085.25
WARNING:tensorflow:From /opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/estimators/estimator.py:1374: get_timestamped_export_dir (from tensorflow.contrib.learn.python.learn.utils.saved_model_export_utils) is deprecated and will be removed in a future version.
Instructions for updating:
Switch to tf.estimator.Exporter and associated utilities.
WARNING:tensorflow:From /opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/estimators/estimator.py:1379: get_temp_export_dir (from tensorflow.contrib.learn.python.learn.utils.saved_model_export_utils) is deprecated and will be removed in a future version.
Instructions for updating:
Switch to tf.estimator.Exporter and associated utilities.
WARNING:tensorflow:From /home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/walsmodel/model.py:157: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.

WARNING:tensorflow:From /opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/estimators/estimator.py:1389: get_input_alternatives (from tensorflow.contrib.learn.python.learn.utils.saved_model_export_utils) is deprecated and will be removed in a future version.
Instructions for updating:
Switch to tf.estimator.Exporter and associated utilities.
Traceback (most recent call last):
  File "/opt/conda/lib/python3.7/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/opt/conda/lib/python3.7/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/walsmodel/task.py", line 98, in <module>
    model.train_and_evaluate(arguments)
  File "/home/jupyter/training-data-analyst/courses/machine_learning/deepdive2/recommendation_systems/labs/walsmodel/model.py", line 198, in train_and_evaluate
    learn_runner.run(experiment_fn = experiment_fn, output_dir = args["output_dir"])
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/python/util/deprecation.py", line 324, in new_func
    return func(*args, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/learn_runner.py", line 225, in run
    return _execute_schedule(experiment, schedule)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/learn_runner.py", line 52, in _execute_schedule
    return task()
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/experiment.py", line 688, in train_and_evaluate
    export_results = self._maybe_export(eval_result)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/experiment.py", line 809, in _maybe_export
    eval_result=eval_result))
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/export_strategy.py", line 110, in export
    return self.export_fn(estimator, export_path, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/utils/saved_model_export_utils.py", line 479, in export_fn
    strip_default_attrs=strip_default_attrs)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/estimators/estimator.py", line 1400, in export_savedmodel
    model_fn_lib.ModeKeys.INFER)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/learn/python/learn/estimators/estimator.py", line 1228, in _call_model_fn
    model_fn_results = self._model_fn(features, labels, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/factorization/python/ops/wals.py", line 338, in _wals_factorization_model_function
    get_col_projection)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/python/ops/control_flow_ops.py", line 1224, in cond
    orig_res_t, res_t = context_t.BuildCondBranch(true_fn)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/python/ops/control_flow_ops.py", line 1061, in BuildCondBranch
    original_result = fn()
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/factorization/python/ops/wals.py", line 326, in get_row_projection
    transpose_input=False)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/factorization/python/ops/factorization_ops.py", line 773, in project_row_factors
    row_weights=projection_weights)[0]
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/factorization/python/ops/factorization_ops.py", line 934, in _process_input_helper
    lambda: math_ops.cast(row_weights, dtypes.float32))
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/python/ops/control_flow_ops.py", line 1224, in cond
    orig_res_t, res_t = context_t.BuildCondBranch(true_fn)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/python/ops/control_flow_ops.py", line 1061, in BuildCondBranch
    original_result = fn()
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/contrib/factorization/python/ops/factorization_ops.py", line 933, in <lambda>
    lambda: (array_ops.ones([num_indices]) * row_weights),
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/python/ops/array_ops.py", line 2560, in ones
    output = _constant_if_small(one, shape, dtype, name)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/python/ops/array_ops.py", line 2295, in _constant_if_small
    if np.prod(shape) < 1000:
  File "<__array_function__ internals>", line 6, in prod
  File "/opt/conda/lib/python3.7/site-packages/numpy/core/fromnumeric.py", line 3052, in prod
    keepdims=keepdims, initial=initial, where=where)
  File "/opt/conda/lib/python3.7/site-packages/numpy/core/fromnumeric.py", line 86, in _wrapreduction
    return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
  File "/opt/conda/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 736, in __array__
    " array.".format(self.name))
NotImplementedError: Cannot convert a symbolic Tensor (cond_1/strided_slice_4:0) to a numpy array.
---------------------------------------------------------------------------
CalledProcessError                        Traceback (most recent call last)
/tmp/ipykernel_19794/806600591.py in <module>
----> 1 get_ipython().run_cell_magic('bash', '', 'rm -rf wals.tar.gz wals_trained\ngcloud ai-platform local train \\\n    --module-name=walsmodel.task \\\n    --package-path=${PWD}/walsmodel \\\n    -- \\\n    --output_dir=${PWD}/wals_trained \\\n    --input_path=${PWD}/data \\\n    --num_epochs=0.01 --nitems=${NITEMS} --nusers=${NUSERS} \\\n    --job-dir=./tmp\n')

/opt/conda/lib/python3.7/site-packages/IPython/core/interactiveshell.py in run_cell_magic(self, magic_name, line, cell)
   2470             with self.builtin_trap:
   2471                 args = (magic_arg_s, cell)
-> 2472                 result = fn(*args, **kwargs)
   2473             return result
   2474 

/opt/conda/lib/python3.7/site-packages/IPython/core/magics/script.py in named_script_magic(line, cell)
    140             else:
    141                 line = script
--> 142             return self.shebang(line, cell)
    143 
    144         # write a basic docstring:

/opt/conda/lib/python3.7/site-packages/decorator.py in fun(*args, **kw)
    230             if not kwsyntax:
    231                 args, kw = fix(args, kw, sig)
--> 232             return caller(func, *(extras + args), **kw)
    233     fun.__name__ = func.__name__
    234     fun.__doc__ = func.__doc__

/opt/conda/lib/python3.7/site-packages/IPython/core/magic.py in <lambda>(f, *a, **k)
    185     # but it's overkill for just that one bit of state.
    186     def magic_deco(arg):
--> 187         call = lambda f, *a, **k: f(*a, **k)
    188 
    189         if callable(arg):

/opt/conda/lib/python3.7/site-packages/IPython/core/magics/script.py in shebang(self, line, cell)
    243             sys.stderr.flush()
    244         if args.raise_error and p.returncode!=0:
--> 245             raise CalledProcessError(p.returncode, cell, output=out, stderr=err)
    246 
    247     def _run_script(self, p, cell, to_close):

CalledProcessError: Command 'b'rm -rf wals.tar.gz wals_trained\ngcloud ai-platform local train \\\n    --module-name=walsmodel.task \\\n    --package-path=${PWD}/walsmodel \\\n    -- \\\n    --output_dir=${PWD}/wals_trained \\\n    --input_path=${PWD}/data \\\n    --num_epochs=0.01 --nitems=${NITEMS} --nusers=${NUSERS} \\\n    --job-dir=./tmp\n'' returned non-zero exit status 1.

This is the second recommendation lab which fails, it needs revision for newer TF. Unfortunately I'm way to busy with work and trying to go through the course material to rewrite these notebooks.

The text was updated successfully, but these errors were encountered:

MrCsabaToth · 2023-09-13T19:52:36Z

One more thing, the gcloud notebooks instances create tensorflow-notebook --vm-image-project=deeplearning-platform-release --vm-image-family=tf-1-15-cpu --machine-type=n1-standard-1 --location=us-central1-a which instantiates the Anaconda VM failed 3 times on me (so three times is not the charm). I modified the us-central1-a location to us-central1-b. I think this should not have affected this bug, given that this is a VM.

MrCsabaToth · 2023-09-13T20:08:56Z

I just tried the solution ipynb to rule out if I mistyped something, but that fails with the exact same exception.

MrCsabaToth · 2023-09-13T20:37:20Z

Lab URL BTW: https://www.cloudskillsboost.google/course_sessions/2920313/labs/325084

MrCsabaToth · 2023-09-13T21:35:28Z

I've found something, this was very sneaky! The bug is not in the notebooks, but rather in the prepared walsmodel package sources. There's a difference between the lab's and the solution's walsmodel/model.py!!! The lab's have an extra export_strategies parameter and a whole function for the tf.contrib.learn.Experiment(. This must cause the error, because going with the solution's prepared module the lab didn't fail!

Based on that I'll be able to produce another fix PR!

…h the solution Fixes GoogleCloudPlatform#2441

MrCsabaToth mentioned this issue Sep 13, 2023

Unusable lab due to deprecated TF 1.x code in "Using Neural Networks for Content-Based Filtering" (content_based_using_neural_networks.ipynb) #2439

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MrCsabaToth added a commit to MrCsabaToth/training-data-analyst that referenced this issue Sep 13, 2023

Remove create_serving_input_fn and export_strategies from lab to matc…

a36bec2

…h the solution Fixes GoogleCloudPlatform#2441

MrCsabaToth linked a pull request Sep 13, 2023 that will close this issue

Match lab's walsmodel with the solution's, Fixes #2441 #2442

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"Collaborative Filtering on Google Analytics data" lab fails with `NotImplementedError: Cannot convert a symbolic Tensor (cond_1/strided_slice_4:0) to a numpy array.` #2441

"Collaborative Filtering on Google Analytics data" lab fails with `NotImplementedError: Cannot convert a symbolic Tensor (cond_1/strided_slice_4:0) to a numpy array.` #2441

MrCsabaToth commented Sep 13, 2023 •

edited

MrCsabaToth commented Sep 13, 2023

MrCsabaToth commented Sep 13, 2023

MrCsabaToth commented Sep 13, 2023

MrCsabaToth commented Sep 13, 2023 •

edited

"Collaborative Filtering on Google Analytics data" lab fails with NotImplementedError: Cannot convert a symbolic Tensor (cond_1/strided_slice_4:0) to a numpy array. #2441

"Collaborative Filtering on Google Analytics data" lab fails with NotImplementedError: Cannot convert a symbolic Tensor (cond_1/strided_slice_4:0) to a numpy array. #2441

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MrCsabaToth commented Sep 13, 2023 • edited

MrCsabaToth commented Sep 13, 2023

MrCsabaToth commented Sep 13, 2023

MrCsabaToth commented Sep 13, 2023

MrCsabaToth commented Sep 13, 2023 • edited

"Collaborative Filtering on Google Analytics data" lab fails with `NotImplementedError: Cannot convert a symbolic Tensor (cond_1/strided_slice_4:0) to a numpy array.` #2441

"Collaborative Filtering on Google Analytics data" lab fails with `NotImplementedError: Cannot convert a symbolic Tensor (cond_1/strided_slice_4:0) to a numpy array.` #2441

MrCsabaToth commented Sep 13, 2023 •

edited

MrCsabaToth commented Sep 13, 2023 •

edited