install tox in base image

[nv-alaiacano]

In order to use tox to run tests on jenkins we have to install it in the base image.

[github-actions]

Documentation preview

https://nvidia-merlin.github.io/Merlin/review/pr-532

[nvidia-merlin-bot]

Click to view CI Results

GitHub pull request #532 of commit 66ed2eb724ad394cfe75d4adb229a2df28c906cc, no merge conflicts.
Running as SYSTEM
Setting status of 66ed2eb724ad394cfe75d4adb229a2df28c906cc to PENDING with url https://10.20.13.93:8080/job/merlin_merlin/334/console and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_merlin
using credential systems-login
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/Merlin # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/Merlin
 > git --version # timeout=10
using GIT_ASKPASS to set credentials login for merlin-systems
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/Merlin +refs/pull/532/*:refs/remotes/origin/pr/532/* # timeout=10
 > git rev-parse 66ed2eb724ad394cfe75d4adb229a2df28c906cc^{commit} # timeout=10
Checking out Revision 66ed2eb724ad394cfe75d4adb229a2df28c906cc (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 66ed2eb724ad394cfe75d4adb229a2df28c906cc # timeout=10
Commit message: "install tox in base image"
 > git rev-list --no-walk df88d4b685158dfb8ab622772ebb81c61eb770e2 # timeout=10
[merlin_merlin] $ /bin/bash /tmp/jenkins12983467929973243946.sh
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.2, pluggy-1.0.0
rootdir: /var/jenkins_home/workspace/merlin_merlin/merlin
plugins: anyio-3.6.1, xdist-2.5.0, forked-1.4.0, cov-3.0.0
collected 3 items
tests/unit/test_version.py .                                             [ 33%]

tests/unit/examples/test_building_deploying_multi_stage_RecSys.py F      [ 66%]

tests/unit/examples/test_scaling_criteo_merlin_models.py F               [100%]
=================================== FAILURES ===================================

__________________________________ test_func ___________________________________
self = <testbook.client.TestbookNotebookClient object at 0x7f66a45002b0>

cell = [53], kwargs = {}, cell_indexes = [53], executed_cells = [], idx = 53
def execute_cell(self, cell, **kwargs) -> Union[Dict, List[Dict]]:
    """
    Executes a cell or list of cells
    """
    if isinstance(cell, slice):
        start, stop = self._cell_index(cell.start), self._cell_index(cell.stop)
        if cell.step is not None:
            raise TestbookError('testbook does not support step argument')

        cell = range(start, stop + 1)
    elif isinstance(cell, str) or isinstance(cell, int):
        cell = [cell]

    cell_indexes = cell

    if all(isinstance(x, str) for x in cell):
        cell_indexes = [self._cell_index(tag) for tag in cell]

    executed_cells = []
    for idx in cell_indexes:
        try:


          cell = super().execute_cell(self.nb['cells'][idx], idx, **kwargs)


/usr/local/lib/python3.8/dist-packages/testbook/client.py:133:

args = (<testbook.client.TestbookNotebookClient object at 0x7f66a45002b0>, {'id': 'f4bba4ca', 'cell_type': 'code', 'metadata'...ast.py, line 299 in transform>]"\n\nAt:\n  /tmp/examples/poc_ensemble/3_queryfeast/1/model.py(122): execute\n']}]}, 53)

kwargs = {}
def wrapped(*args, **kwargs):


  return just_run(coro(*args, **kwargs))


/usr/local/lib/python3.8/dist-packages/nbclient/util.py:85:

coro = <coroutine object NotebookClient.async_execute_cell at 0x7f65cb814e40>
def just_run(coro: Awaitable) -> Any:
    """Make the coroutine run, even if there is an event loop running (using nest_asyncio)"""
    try:
        loop = asyncio.get_running_loop()
    except RuntimeError:
        loop = None
    if loop is None:
        had_running_loop = False
        loop = asyncio.new_event_loop()
        asyncio.set_event_loop(loop)
    else:
        had_running_loop = True
    if had_running_loop:
        # if there is a running loop, we patch using nest_asyncio
        # to have reentrant event loops
        check_ipython()
        import nest_asyncio

        nest_asyncio.apply()
        check_patch_tornado()


  return loop.run_until_complete(coro)


/usr/local/lib/python3.8/dist-packages/nbclient/util.py:60:

self = <_UnixSelectorEventLoop running=False closed=False debug=False>

future = <Task finished name='Task-369' coro=<NotebookClient.async_execute_cell() done, defined at /usr/local/lib/python3.8/dis...ps/feast.py, line 299 in transform>]"\n\nAt:\n  /tmp/examples/poc_ensemble/3_queryfeast/1/model.py(122): execute\n\n')>
def run_until_complete(self, future):
    """Run until the Future is done.

    If the argument is a coroutine, it is wrapped in a Task.

    WARNING: It would be disastrous to call run_until_complete()
    with the same coroutine twice -- it would wrap it in two
    different Tasks and that can't be good.

    Return the Future's result, or raise its exception.
    """
    self._check_closed()
    self._check_running()

    new_task = not futures.isfuture(future)
    future = tasks.ensure_future(future, loop=self)
    if new_task:
        # An exception is raised if the future didn't complete, so there
        # is no need to log the "destroy pending task" message
        future._log_destroy_pending = False

    future.add_done_callback(_run_until_complete_cb)
    try:
        self.run_forever()
    except:
        if new_task and future.done() and not future.cancelled():
            # The coroutine raised a BaseException. Consume the exception
            # to not log a warning, the caller doesn't have access to the
            # local task.
            future.exception()
        raise
    finally:
        future.remove_done_callback(_run_until_complete_cb)
    if not future.done():
        raise RuntimeError('Event loop stopped before Future completed.')


  return future.result()


/usr/lib/python3.8/asyncio/base_events.py:616:

self = <testbook.client.TestbookNotebookClient object at 0x7f66a45002b0>

cell = {'id': 'f4bba4ca', 'cell_type': 'code', 'metadata': {'execution': {'iopub.status.busy': '2022-08-09T21:13:35.225504Z',...ps/feast.py, line 299 in transform>]"\n\nAt:\n  /tmp/examples/poc_ensemble/3_queryfeast/1/model.py(122): execute\n']}]}

cell_index = 53, execution_count = None, store_history = True
async def async_execute_cell(
    self,
    cell: NotebookNode,
    cell_index: int,
    execution_count: t.Optional[int] = None,
    store_history: bool = True,
) -> NotebookNode:
    """
    Executes a single code cell.

    To execute all cells see :meth:`execute`.

    Parameters
    ----------
    cell : nbformat.NotebookNode
        The cell which is currently being processed.
    cell_index : int
        The position of the cell within the notebook object.
    execution_count : int
        The execution count to be assigned to the cell (default: Use kernel response)
    store_history : bool
        Determines if history should be stored in the kernel (default: False).
        Specific to ipython kernels, which can store command histories.

    Returns
    -------
    output : dict
        The execution output payload (or None for no output).

    Raises
    ------
    CellExecutionError
        If execution failed and should raise an exception, this will be raised
        with defaults about the failure.

    Returns
    -------
    cell : NotebookNode
        The cell which was just processed.
    """
    assert self.kc is not None

    await run_hook(self.on_cell_start, cell=cell, cell_index=cell_index)

    if cell.cell_type != 'code' or not cell.source.strip():
        self.log.debug("Skipping non-executing cell %s", cell_index)
        return cell

    if self.skip_cells_with_tag in cell.metadata.get("tags", []):
        self.log.debug("Skipping tagged cell %s", cell_index)
        return cell

    if self.record_timing:  # clear execution metadata prior to execution
        cell['metadata']['execution'] = {}

    self.log.debug("Executing cell:\n%s", cell.source)

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors or "raises-exception" in cell.metadata.get("tags", [])
    )

    await run_hook(self.on_cell_execute, cell=cell, cell_index=cell_index)
    parent_msg_id = await ensure_async(
        self.kc.execute(
            cell.source, store_history=store_history, stop_on_error=not cell_allows_errors
        )
    )
    await run_hook(self.on_cell_complete, cell=cell, cell_index=cell_index)
    # We launched a code cell to execute
    self.code_cells_executed += 1
    exec_timeout = self._get_timeout(cell)

    cell.outputs = []
    self.clear_before_next_output = False

    task_poll_kernel_alive = asyncio.ensure_future(self._async_poll_kernel_alive())
    task_poll_output_msg = asyncio.ensure_future(
        self._async_poll_output_msg(parent_msg_id, cell, cell_index)
    )
    self.task_poll_for_reply = asyncio.ensure_future(
        self._async_poll_for_reply(
            parent_msg_id, cell, exec_timeout, task_poll_output_msg, task_poll_kernel_alive
        )
    )
    try:
        exec_reply = await self.task_poll_for_reply
    except asyncio.CancelledError:
        # can only be cancelled by task_poll_kernel_alive when the kernel is dead
        task_poll_output_msg.cancel()
        raise DeadKernelError("Kernel died")
    except Exception as e:
        # Best effort to cancel request if it hasn't been resolved
        try:
            # Check if the task_poll_output is doing the raising for us
            if not isinstance(e, CellControlSignal):
                task_poll_output_msg.cancel()
        finally:
            raise

    if execution_count:
        cell['execution_count'] = execution_count
    await run_hook(
        self.on_cell_executed, cell=cell, cell_index=cell_index, execute_reply=exec_reply
    )


  await self._check_raise_for_error(cell, cell_index, exec_reply)


/usr/local/lib/python3.8/dist-packages/nbclient/client.py:1022:

self = <testbook.client.TestbookNotebookClient object at 0x7f66a45002b0>

cell = {'id': 'f4bba4ca', 'cell_type': 'code', 'metadata': {'execution': {'iopub.status.busy': '2022-08-09T21:13:35.225504Z',...ps/feast.py, line 299 in transform>]"\n\nAt:\n  /tmp/examples/poc_ensemble/3_queryfeast/1/model.py(122): execute\n']}]}

cell_index = 53

exec_reply = {'buffers': [], 'content': {'ename': 'InferenceServerException', 'engine_info': {'engine_id': -1, 'engine_uuid': '5d19...e, 'engine': '5d194bdd-7658-4037-85a3-0dc5030a2c7e', 'started': '2022-08-09T21:13:35.225820Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(
        self.on_cell_error, cell=cell, cell_index=cell_index, execute_reply=exec_reply
    )
    if not cell_allows_errors:


      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)


E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E

E           import shutil

E           from merlin.models.loader.tf_utils import configure_tensorflow

E           configure_tensorflow()

E           from merlin.systems.triton.utils import run_ensemble_on_tritonserver

E           response = run_ensemble_on_tritonserver(

E               "/tmp/examples/poc_ensemble", outputs, request, "ensemble_model"

E           )

E           response = [x.tolist()[0] for x in response["ordered_ids"]]

E           shutil.rmtree("/tmp/examples/", ignore_errors=True)

E

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mInferenceServerException�[0m                  Traceback (most recent call last)

E           Input �[0;32mIn [32]�[0m, in �[0;36m<cell line: 5>�[0;34m()�[0m

E           �[1;32m      3�[0m configure_tensorflow()

E           �[1;32m      4�[0m �[38;5;28;01mfrom�[39;00m �[38;5;21;01mmerlin�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01msystems�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mtriton�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mutils�[39;00m �[38;5;28;01mimport�[39;00m run_ensemble_on_tritonserver

E           �[0;32m----> 5�[0m response �[38;5;241m=�[39m �[43mrun_ensemble_on_tritonserver�[49m�[43m(�[49m

E           �[1;32m      6�[0m �[43m    �[49m�[38;5;124;43m"�[39;49m�[38;5;124;43m/tmp/examples/poc_ensemble�[39;49m�[38;5;124;43m"�[39;49m�[43m,�[49m�[43m �[49m�[43moutputs�[49m�[43m,�[49m�[43m �[49m�[43mrequest�[49m�[43m,�[49m�[43m �[49m�[38;5;124;43m"�[39;49m�[38;5;124;43mensemble_model�[39;49m�[38;5;124;43m"�[39;49m

E           �[1;32m      7�[0m �[43m)�[49m

E           �[1;32m      8�[0m response �[38;5;241m=�[39m [x�[38;5;241m.�[39mtolist()[�[38;5;241m0�[39m] �[38;5;28;01mfor�[39;00m x �[38;5;129;01min�[39;00m response[�[38;5;124m"�[39m�[38;5;124mordered_ids�[39m�[38;5;124m"�[39m]]

E           �[1;32m      9�[0m shutil�[38;5;241m.�[39mrmtree(�[38;5;124m"�[39m�[38;5;124m/tmp/examples/�[39m�[38;5;124m"�[39m, ignore_errors�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)

E

E           File �[0;32m/usr/local/lib/python3.8/dist-packages/merlin/systems/triton/utils.py:93�[0m, in �[0;36mrun_ensemble_on_tritonserver�[0;34m(tmpdir, output_columns, df, model_name)�[0m

E           �[1;32m     91�[0m response �[38;5;241m=�[39m �[38;5;28;01mNone�[39;00m

E           �[1;32m     92�[0m �[38;5;28;01mwith�[39;00m run_triton_server(tmpdir) �[38;5;28;01mas�[39;00m client:

E           �[0;32m---> 93�[0m     response �[38;5;241m=�[39m �[43msend_triton_request�[49m�[43m(�[49m�[43mdf�[49m�[43m,�[49m�[43m �[49m�[43moutput_columns�[49m�[43m,�[49m�[43m �[49m�[43mclient�[49m�[38;5;241;43m=�[39;49m�[43mclient�[49m�[43m,�[49m�[43m �[49m�[43mtriton_model�[49m�[38;5;241;43m=�[39;49m�[43mmodel_name�[49m�[43m)�[49m

E           �[1;32m     95�[0m �[38;5;28;01mreturn�[39;00m response

E

E           File �[0;32m/usr/local/lib/python3.8/dist-packages/merlin/systems/triton/utils.py:141�[0m, in �[0;36msend_triton_request�[0;34m(df, outputs_list, client, endpoint, request_id, triton_model)�[0m

E           �[1;32m    139�[0m outputs �[38;5;241m=�[39m [grpcclient�[38;5;241m.�[39mInferRequestedOutput(col) �[38;5;28;01mfor�[39;00m col �[38;5;129;01min�[39;00m outputs_list]

E           �[1;32m    140�[0m �[38;5;28;01mwith�[39;00m client:

E           �[0;32m--> 141�[0m     response �[38;5;241m=�[39m �[43mclient�[49m�[38;5;241;43m.�[39;49m�[43minfer�[49m�[43m(�[49m�[43mtriton_model�[49m�[43m,�[49m�[43m �[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[43mrequest_id�[49m�[38;5;241;43m=�[39;49m�[43mrequest_id�[49m�[43m,�[49m�[43m �[49m�[43moutputs�[49m�[38;5;241;43m=�[39;49m�[43moutputs�[49m�[43m)�[49m

E           �[1;32m    143�[0m results �[38;5;241m=�[39m {}

E           �[1;32m    144�[0m �[38;5;28;01mfor�[39;00m col �[38;5;129;01min�[39;00m outputs_list:

E

E           File �[0;32m/usr/local/lib/python3.8/dist-packages/tritonclient/grpc/init.py:1322�[0m, in �[0;36mInferenceServerClient.infer�[0;34m(self, model_name, inputs, model_version, outputs, request_id, sequence_id, sequence_start, sequence_end, priority, timeout, client_timeout, headers, compression_algorithm)�[0m

E           �[1;32m   1320�[0m     �[38;5;28;01mreturn�[39;00m result

E           �[1;32m   1321�[0m �[38;5;28;01mexcept�[39;00m grpc�[38;5;241m.�[39mRpcError �[38;5;28;01mas�[39;00m rpc_error:

E           �[0;32m-> 1322�[0m     �[43mraise_error_grpc�[49m�[43m(�[49m�[43mrpc_error�[49m�[43m)�[49m

E

E           File �[0;32m/usr/local/lib/python3.8/dist-packages/tritonclient/grpc/init.py:62�[0m, in �[0;36mraise_error_grpc�[0;34m(rpc_error)�[0m

E           �[1;32m     61�[0m �[38;5;28;01mdef�[39;00m �[38;5;21mraise_error_grpc�[39m(rpc_error):

E           �[0;32m---> 62�[0m     �[38;5;28;01mraise�[39;00m get_error_grpc(rpc_error) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E

E           �[0;31mInferenceServerException�[0m: [StatusCode.INTERNAL] in ensemble 'ensemble_model', Failed to process the request(s) for model instance '3_queryfeast', message: TypeError: init(): incompatible constructor arguments. The following argument types are supported:

E               1. c_python_backend_utils.InferenceResponse(output_tensors: List[c_python_backend_utils.Tensor], error: c_python_backend_utils.TritonError = None)

E

E           Invoked with: kwargs: tensors=[], error="<class 'TypeError'>, int() argument must be a string, a bytes-like object or a number, not 'NoneType', [<FrameSummary file /tmp/examples/poc_ensemble/3_queryfeast/1/model.py, line 105 in execute>, <FrameSummary file /usr/local/lib/python3.8/dist-packages/merlin/systems/dag/op_runner.py, line 38 in execute>, <FrameSummary file /usr/local/lib/python3.8/dist-packages/merlin/systems/dag/ops/feast.py, line 299 in transform>]"

E

E           At:

E             /tmp/examples/poc_ensemble/3_queryfeast/1/model.py(122): execute

E

E           InferenceServerException: [StatusCode.INTERNAL] in ensemble 'ensemble_model', Failed to process the request(s) for model instance '3_queryfeast', message: TypeError: init(): incompatible constructor arguments. The following argument types are supported:

E               1. c_python_backend_utils.InferenceResponse(output_tensors: List[c_python_backend_utils.Tensor], error: c_python_backend_utils.TritonError = None)

E

E           Invoked with: kwargs: tensors=[], error="<class 'TypeError'>, int() argument must be a string, a bytes-like object or a number, not 'NoneType', [<FrameSummary file /tmp/examples/poc_ensemble/3_queryfeast/1/model.py, line 105 in execute>, <FrameSummary file /usr/local/lib/python3.8/dist-packages/merlin/systems/dag/op_runner.py, line 38 in execute>, <FrameSummary file /usr/local/lib/python3.8/dist-packages/merlin/systems/dag/ops/feast.py, line 299 in transform>]"

E

E           At:

E             /tmp/examples/poc_ensemble/3_queryfeast/1/model.py(122): execute
/usr/local/lib/python3.8/dist-packages/nbclient/client.py:916: CellExecutionError
During handling of the above exception, another exception occurred:
def test_func():
    with testbook(
        REPO_ROOT
        / "examples"
        / "Building-and-deploying-multi-stage-RecSys"
        / "01-Building-Recommender-Systems-with-Merlin.ipynb",
        execute=False,
    ) as tb1:
        tb1.inject(
            """
            import os
            os.environ["DATA_FOLDER"] = "/tmp/data/"
            os.environ["NUM_ROWS"] = "10000"
            os.system("mkdir -p /tmp/examples")
            os.environ["BASE_DIR"] = "/tmp/examples/"
            """
        )
        tb1.execute()
        assert os.path.isdir("/tmp/examples/dlrm")
        assert os.path.isdir("/tmp/examples/feature_repo")
        assert os.path.isdir("/tmp/examples/query_tower")
        assert os.path.isfile("/tmp/examples/item_embeddings.parquet")
        assert os.path.isfile("/tmp/examples/feature_repo/user_features.py")
        assert os.path.isfile("/tmp/examples/feature_repo/item_features.py")

    with testbook(
        REPO_ROOT
        / "examples"
        / "Building-and-deploying-multi-stage-RecSys"
        / "02-Deploying-multi-stage-RecSys-with-Merlin-Systems.ipynb",
        execute=False,
    ) as tb2:
        tb2.inject(
            """
            import os
            os.environ["DATA_FOLDER"] = "/tmp/data/"
            os.environ["BASE_DIR"] = "/tmp/examples/"
            """
        )
        NUM_OF_CELLS = len(tb2.cells)
        tb2.execute_cell(list(range(0, NUM_OF_CELLS - 3)))
        top_k = tb2.ref("top_k")
        outputs = tb2.ref("outputs")
        assert outputs[0] == "ordered_ids"


      tb2.inject(


            """
            import shutil
            from merlin.models.loader.tf_utils import configure_tensorflow
            configure_tensorflow()
            from merlin.systems.triton.utils import run_ensemble_on_tritonserver
            response = run_ensemble_on_tritonserver(
                "/tmp/examples/poc_ensemble", outputs, request, "ensemble_model"
            )
            response = [x.tolist()[0] for x in response["ordered_ids"]]
            shutil.rmtree("/tmp/examples/", ignore_errors=True)
            """
        )

tests/unit/examples/test_building_deploying_multi_stage_RecSys.py:57:

/usr/local/lib/python3.8/dist-packages/testbook/client.py:237: in inject

cell = TestbookNode(self.execute_cell(inject_idx)) if run else TestbookNode(code_cell)

self = <testbook.client.TestbookNotebookClient object at 0x7f66a45002b0>

cell = [53], kwargs = {}, cell_indexes = [53], executed_cells = [], idx = 53
def execute_cell(self, cell, **kwargs) -> Union[Dict, List[Dict]]:
    """
    Executes a cell or list of cells
    """
    if isinstance(cell, slice):
        start, stop = self._cell_index(cell.start), self._cell_index(cell.stop)
        if cell.step is not None:
            raise TestbookError('testbook does not support step argument')

        cell = range(start, stop + 1)
    elif isinstance(cell, str) or isinstance(cell, int):
        cell = [cell]

    cell_indexes = cell

    if all(isinstance(x, str) for x in cell):
        cell_indexes = [self._cell_index(tag) for tag in cell]

    executed_cells = []
    for idx in cell_indexes:
        try:
            cell = super().execute_cell(self.nb['cells'][idx], idx, **kwargs)
        except CellExecutionError as ce:


          raise TestbookRuntimeError(ce.evalue, ce, self._get_error_class(ce.ename))


E               testbook.exceptions.TestbookRuntimeError: An error occurred while executing the following cell:

E               ------------------

E

E               import shutil

E               from merlin.models.loader.tf_utils import configure_tensorflow

E               configure_tensorflow()

E               from merlin.systems.triton.utils import run_ensemble_on_tritonserver

E               response = run_ensemble_on_tritonserver(

E                   "/tmp/examples/poc_ensemble", outputs, request, "ensemble_model"

E               )

E               response = [x.tolist()[0] for x in response["ordered_ids"]]

E               shutil.rmtree("/tmp/examples/", ignore_errors=True)

E

E               ------------------

E

E               �[0;31m---------------------------------------------------------------------------�[0m

E               �[0;31mInferenceServerException�[0m                  Traceback (most recent call last)

E               Input �[0;32mIn [32]�[0m, in �[0;36m<cell line: 5>�[0;34m()�[0m

E               �[1;32m      3�[0m configure_tensorflow()

E               �[1;32m      4�[0m �[38;5;28;01mfrom�[39;00m �[38;5;21;01mmerlin�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01msystems�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mtriton�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mutils�[39;00m �[38;5;28;01mimport�[39;00m run_ensemble_on_tritonserver

E               �[0;32m----> 5�[0m response �[38;5;241m=�[39m �[43mrun_ensemble_on_tritonserver�[49m�[43m(�[49m

E               �[1;32m      6�[0m �[43m    �[49m�[38;5;124;43m"�[39;49m�[38;5;124;43m/tmp/examples/poc_ensemble�[39;49m�[38;5;124;43m"�[39;49m�[43m,�[49m�[43m �[49m�[43moutputs�[49m�[43m,�[49m�[43m �[49m�[43mrequest�[49m�[43m,�[49m�[43m �[49m�[38;5;124;43m"�[39;49m�[38;5;124;43mensemble_model�[39;49m�[38;5;124;43m"�[39;49m

E               �[1;32m      7�[0m �[43m)�[49m

E               �[1;32m      8�[0m response �[38;5;241m=�[39m [x�[38;5;241m.�[39mtolist()[�[38;5;241m0�[39m] �[38;5;28;01mfor�[39;00m x �[38;5;129;01min�[39;00m response[�[38;5;124m"�[39m�[38;5;124mordered_ids�[39m�[38;5;124m"�[39m]]

E               �[1;32m      9�[0m shutil�[38;5;241m.�[39mrmtree(�[38;5;124m"�[39m�[38;5;124m/tmp/examples/�[39m�[38;5;124m"�[39m, ignore_errors�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)

E

E               File �[0;32m/usr/local/lib/python3.8/dist-packages/merlin/systems/triton/utils.py:93�[0m, in �[0;36mrun_ensemble_on_tritonserver�[0;34m(tmpdir, output_columns, df, model_name)�[0m

E               �[1;32m     91�[0m response �[38;5;241m=�[39m �[38;5;28;01mNone�[39;00m

E               �[1;32m     92�[0m �[38;5;28;01mwith�[39;00m run_triton_server(tmpdir) �[38;5;28;01mas�[39;00m client:

E               �[0;32m---> 93�[0m     response �[38;5;241m=�[39m �[43msend_triton_request�[49m�[43m(�[49m�[43mdf�[49m�[43m,�[49m�[43m �[49m�[43moutput_columns�[49m�[43m,�[49m�[43m �[49m�[43mclient�[49m�[38;5;241;43m=�[39;49m�[43mclient�[49m�[43m,�[49m�[43m �[49m�[43mtriton_model�[49m�[38;5;241;43m=�[39;49m�[43mmodel_name�[49m�[43m)�[49m

E               �[1;32m     95�[0m �[38;5;28;01mreturn�[39;00m response

E

E               File �[0;32m/usr/local/lib/python3.8/dist-packages/merlin/systems/triton/utils.py:141�[0m, in �[0;36msend_triton_request�[0;34m(df, outputs_list, client, endpoint, request_id, triton_model)�[0m

E               �[1;32m    139�[0m outputs �[38;5;241m=�[39m [grpcclient�[38;5;241m.�[39mInferRequestedOutput(col) �[38;5;28;01mfor�[39;00m col �[38;5;129;01min�[39;00m outputs_list]

E               �[1;32m    140�[0m �[38;5;28;01mwith�[39;00m client:

E               �[0;32m--> 141�[0m     response �[38;5;241m=�[39m �[43mclient�[49m�[38;5;241;43m.�[39;49m�[43minfer�[49m�[43m(�[49m�[43mtriton_model�[49m�[43m,�[49m�[43m �[49m�[43minputs�[49m�[43m,�[49m�[43m �[49m�[43mrequest_id�[49m�[38;5;241;43m=�[39;49m�[43mrequest_id�[49m�[43m,�[49m�[43m �[49m�[43moutputs�[49m�[38;5;241;43m=�[39;49m�[43moutputs�[49m�[43m)�[49m

E               �[1;32m    143�[0m results �[38;5;241m=�[39m {}

E               �[1;32m    144�[0m �[38;5;28;01mfor�[39;00m col �[38;5;129;01min�[39;00m outputs_list:

E

E               File �[0;32m/usr/local/lib/python3.8/dist-packages/tritonclient/grpc/init.py:1322�[0m, in �[0;36mInferenceServerClient.infer�[0;34m(self, model_name, inputs, model_version, outputs, request_id, sequence_id, sequence_start, sequence_end, priority, timeout, client_timeout, headers, compression_algorithm)�[0m

E               �[1;32m   1320�[0m     �[38;5;28;01mreturn�[39;00m result

E               �[1;32m   1321�[0m �[38;5;28;01mexcept�[39;00m grpc�[38;5;241m.�[39mRpcError �[38;5;28;01mas�[39;00m rpc_error:

E               �[0;32m-> 1322�[0m     �[43mraise_error_grpc�[49m�[43m(�[49m�[43mrpc_error�[49m�[43m)�[49m

E

E               File �[0;32m/usr/local/lib/python3.8/dist-packages/tritonclient/grpc/init.py:62�[0m, in �[0;36mraise_error_grpc�[0;34m(rpc_error)�[0m

E               �[1;32m     61�[0m �[38;5;28;01mdef�[39;00m �[38;5;21mraise_error_grpc�[39m(rpc_error):

E               �[0;32m---> 62�[0m     �[38;5;28;01mraise�[39;00m get_error_grpc(rpc_error) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E

E               �[0;31mInferenceServerException�[0m: [StatusCode.INTERNAL] in ensemble 'ensemble_model', Failed to process the request(s) for model instance '3_queryfeast', message: TypeError: init(): incompatible constructor arguments. The following argument types are supported:

E                   1. c_python_backend_utils.InferenceResponse(output_tensors: List[c_python_backend_utils.Tensor], error: c_python_backend_utils.TritonError = None)

E

E               Invoked with: kwargs: tensors=[], error="<class 'TypeError'>, int() argument must be a string, a bytes-like object or a number, not 'NoneType', [<FrameSummary file /tmp/examples/poc_ensemble/3_queryfeast/1/model.py, line 105 in execute>, <FrameSummary file /usr/local/lib/python3.8/dist-packages/merlin/systems/dag/op_runner.py, line 38 in execute>, <FrameSummary file /usr/local/lib/python3.8/dist-packages/merlin/systems/dag/ops/feast.py, line 299 in transform>]"

E

E               At:

E                 /tmp/examples/poc_ensemble/3_queryfeast/1/model.py(122): execute

E

E               InferenceServerException: [StatusCode.INTERNAL] in ensemble 'ensemble_model', Failed to process the request(s) for model instance '3_queryfeast', message: TypeError: init(): incompatible constructor arguments. The following argument types are supported:

E                   1. c_python_backend_utils.InferenceResponse(output_tensors: List[c_python_backend_utils.Tensor], error: c_python_backend_utils.TritonError = None)

E

E               Invoked with: kwargs: tensors=[], error="<class 'TypeError'>, int() argument must be a string, a bytes-like object or a number, not 'NoneType', [<FrameSummary file /tmp/examples/poc_ensemble/3_queryfeast/1/model.py, line 105 in execute>, <FrameSummary file /usr/local/lib/python3.8/dist-packages/merlin/systems/dag/op_runner.py, line 38 in execute>, <FrameSummary file /usr/local/lib/python3.8/dist-packages/merlin/systems/dag/ops/feast.py, line 299 in transform>]"

E

E               At:

E                 /tmp/examples/poc_ensemble/3_queryfeast/1/model.py(122): execute
/usr/local/lib/python3.8/dist-packages/testbook/client.py:135: TestbookRuntimeError

----------------------------- Captured stdout call -----------------------------

Signal (2) received.

----------------------------- Captured stderr call -----------------------------

2022-08-09 21:11:53.527675: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-08-09 21:11:55.578430: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 1627 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-08-09 21:11:55.579137: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14532 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

WARNING clustering 251 points to 32 centroids: please provide at least 1248 training points

2022-08-09 21:13:28.287765: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-08-09 21:13:30.289910: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 1627 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-08-09 21:13:30.290703: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14532 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

I0809 21:13:35.506421 7755 pinned_memory_manager.cc:240] Pinned memory pool is created at '0x7fe820000000' with size 268435456

I0809 21:13:35.507195 7755 cuda_memory_manager.cc:105] CUDA memory pool is created on device 0 with size 67108864

I0809 21:13:35.514282 7755 model_repository_manager.cc:1191] loading: 1_predicttensorflow:1

I0809 21:13:35.614702 7755 model_repository_manager.cc:1191] loading: 0_queryfeast:1

I0809 21:13:35.714995 7755 model_repository_manager.cc:1191] loading: 2_queryfaiss:1

I0809 21:13:35.815286 7755 model_repository_manager.cc:1191] loading: 3_queryfeast:1

I0809 21:13:35.901096 7755 tensorflow.cc:2181] TRITONBACKEND_Initialize: tensorflow

I0809 21:13:35.901134 7755 tensorflow.cc:2191] Triton TRITONBACKEND API version: 1.9

I0809 21:13:35.901141 7755 tensorflow.cc:2197] 'tensorflow' TRITONBACKEND API version: 1.9

I0809 21:13:35.901147 7755 tensorflow.cc:2221] backend configuration:

{"cmdline":{"auto-complete-config":"false","backend-directory":"/opt/tritonserver/backends","min-compute-capability":"6.000000","version":"2","default-max-batch-size":"4"}}

I0809 21:13:35.901183 7755 tensorflow.cc:2281] TRITONBACKEND_ModelInitialize: 1_predicttensorflow (version 1)

I0809 21:13:35.906118 7755 tensorflow.cc:2330] TRITONBACKEND_ModelInstanceInitialize: 1_predicttensorflow (GPU device 0)

I0809 21:13:35.915588 7755 model_repository_manager.cc:1191] loading: 4_unrollfeatures:1

I0809 21:13:36.015855 7755 model_repository_manager.cc:1191] loading: 5_predicttensorflow:1

I0809 21:13:36.116185 7755 model_repository_manager.cc:1191] loading: 6_softmaxsampling:1

2022-08-09 21:13:36.254903: I tensorflow/cc/saved_model/reader.cc:43] Reading SavedModel from: /tmp/examples/poc_ensemble/1_predicttensorflow/1/model.savedmodel

2022-08-09 21:13:36.259109: I tensorflow/cc/saved_model/reader.cc:78] Reading meta graph with tags { serve }

2022-08-09 21:13:36.259169: I tensorflow/cc/saved_model/reader.cc:119] Reading SavedModel debug info (if present) from: /tmp/examples/poc_ensemble/1_predicttensorflow/1/model.savedmodel

2022-08-09 21:13:36.259264: I tensorflow/core/platform/cpu_feature_guard.cc:152] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  SSE3 SSE4.1 SSE4.2 AVX

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-08-09 21:13:36.306716: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1525] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 11752 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-08-09 21:13:36.352593: I tensorflow/cc/saved_model/loader.cc:230] Restoring SavedModel bundle.

2022-08-09 21:13:36.432829: I tensorflow/cc/saved_model/loader.cc:214] Running initialization op on SavedModel bundle at path: /tmp/examples/poc_ensemble/1_predicttensorflow/1/model.savedmodel

2022-08-09 21:13:36.456616: I tensorflow/cc/saved_model/loader.cc:321] SavedModel load for tags { serve }; Status: success: OK. Took 201730 microseconds.

I0809 21:13:36.456900 7755 model_repository_manager.cc:1345] successfully loaded '1_predicttensorflow' version 1

I0809 21:13:36.460135 7755 tensorflow.cc:2281] TRITONBACKEND_ModelInitialize: 5_predicttensorflow (version 1)

I0809 21:13:36.461445 7755 python.cc:2388] TRITONBACKEND_ModelInstanceInitialize: 0_queryfeast (GPU device 0)

I0809 21:13:38.818696 7755 python.cc:2388] TRITONBACKEND_ModelInstanceInitialize: 2_queryfaiss (GPU device 0)

I0809 21:13:38.818957 7755 model_repository_manager.cc:1345] successfully loaded '0_queryfeast' version 1

I0809 21:13:41.218937 7755 python.cc:2388] TRITONBACKEND_ModelInstanceInitialize: 3_queryfeast (GPU device 0)

I0809 21:13:41.219066 7755 model_repository_manager.cc:1345] successfully loaded '2_queryfaiss' version 1

I0809 21:13:43.568369 7755 python.cc:2388] TRITONBACKEND_ModelInstanceInitialize: 4_unrollfeatures (GPU device 0)

I0809 21:13:43.568488 7755 model_repository_manager.cc:1345] successfully loaded '3_queryfeast' version 1

I0809 21:13:45.689964 7755 tensorflow.cc:2330] TRITONBACKEND_ModelInstanceInitialize: 5_predicttensorflow (GPU device 0)

I0809 21:13:45.690231 7755 model_repository_manager.cc:1345] successfully loaded '4_unrollfeatures' version 1

2022-08-09 21:13:45.691616: I tensorflow/cc/saved_model/reader.cc:43] Reading SavedModel from: /tmp/examples/poc_ensemble/5_predicttensorflow/1/model.savedmodel

2022-08-09 21:13:45.708179: I tensorflow/cc/saved_model/reader.cc:78] Reading meta graph with tags { serve }

2022-08-09 21:13:45.708224: I tensorflow/cc/saved_model/reader.cc:119] Reading SavedModel debug info (if present) from: /tmp/examples/poc_ensemble/5_predicttensorflow/1/model.savedmodel

2022-08-09 21:13:45.710214: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1525] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 11752 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-08-09 21:13:45.731604: I tensorflow/cc/saved_model/loader.cc:230] Restoring SavedModel bundle.

2022-08-09 21:13:45.882805: I tensorflow/cc/saved_model/loader.cc:214] Running initialization op on SavedModel bundle at path: /tmp/examples/poc_ensemble/5_predicttensorflow/1/model.savedmodel

2022-08-09 21:13:45.935999: I tensorflow/cc/saved_model/loader.cc:321] SavedModel load for tags { serve }; Status: success: OK. Took 244396 microseconds.

I0809 21:13:45.936132 7755 python.cc:2388] TRITONBACKEND_ModelInstanceInitialize: 6_softmaxsampling (GPU device 0)

I0809 21:13:45.936227 7755 model_repository_manager.cc:1345] successfully loaded '5_predicttensorflow' version 1

I0809 21:13:48.051003 7755 model_repository_manager.cc:1345] successfully loaded '6_softmaxsampling' version 1

I0809 21:13:48.053905 7755 model_repository_manager.cc:1191] loading: ensemble_model:1

I0809 21:13:48.154655 7755 model_repository_manager.cc:1345] successfully loaded 'ensemble_model' version 1

I0809 21:13:48.154836 7755 server.cc:556]

+------------------+------+

| Repository Agent | Path |

+------------------+------+

+------------------+------+
I0809 21:13:48.154950 7755 server.cc:583]

+------------+-----------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

| Backend    | Path                                                            | Config                                                                                                                                                                       |

+------------+-----------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

| tensorflow | /opt/tritonserver/backends/tensorflow2/libtriton_tensorflow2.so | {"cmdline":{"auto-complete-config":"false","backend-directory":"/opt/tritonserver/backends","min-compute-capability":"6.000000","version":"2","default-max-batch-size":"4"}} |

| python     | /opt/tritonserver/backends/python/libtriton_python.so           | {"cmdline":{"auto-complete-config":"false","min-compute-capability":"6.000000","backend-directory":"/opt/tritonserver/backends","default-max-batch-size":"4"}}               |

+------------+-----------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
I0809 21:13:48.155064 7755 server.cc:626]

+---------------------+---------+--------+

| Model               | Version | Status |

+---------------------+---------+--------+

| 0_queryfeast        | 1       | READY  |

| 1_predicttensorflow | 1       | READY  |

| 2_queryfaiss        | 1       | READY  |

| 3_queryfeast        | 1       | READY  |

| 4_unrollfeatures    | 1       | READY  |

| 5_predicttensorflow | 1       | READY  |

| 6_softmaxsampling   | 1       | READY  |

| ensemble_model      | 1       | READY  |

+---------------------+---------+--------+
I0809 21:13:48.220270 7755 metrics.cc:650] Collecting metrics for GPU 0: Tesla P100-DGXS-16GB

I0809 21:13:48.221145 7755 tritonserver.cc:2138]

+----------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

| Option                           | Value                                                                                                                                                                                        |

+----------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

| server_id                        | triton                                                                                                                                                                                       |

| server_version                   | 2.22.0                                                                                                                                                                                       |

| server_extensions                | classification sequence model_repository model_repository(unload_dependents) schedule_policy model_configuration system_shared_memory cuda_shared_memory binary_tensor_data statistics trace |

| model_repository_path[0]         | /tmp/examples/poc_ensemble                                                                                                                                                                   |

| model_control_mode               | MODE_NONE                                                                                                                                                                                    |

| strict_model_config              | 1                                                                                                                                                                                            |

| rate_limit                       | OFF                                                                                                                                                                                          |

| pinned_memory_pool_byte_size     | 268435456                                                                                                                                                                                    |

| cuda_memory_pool_byte_size{0}    | 67108864                                                                                                                                                                                     |

| response_cache_byte_size         | 0                                                                                                                                                                                            |

| min_supported_compute_capability | 6.0                                                                                                                                                                                          |

| strict_readiness                 | 1                                                                                                                                                                                            |

| exit_timeout                     | 30                                                                                                                                                                                           |

+----------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
I0809 21:13:48.221966 7755 grpc_server.cc:4589] Started GRPCInferenceService at 0.0.0.0:8001

I0809 21:13:48.222192 7755 http_server.cc:3303] Started HTTPService at 0.0.0.0:8000

I0809 21:13:48.263075 7755 http_server.cc:178] Started Metrics Service at 0.0.0.0:8002

W0809 21:13:49.235705 7755 metrics.cc:468] Unable to get energy consumption for GPU 0. Status:Success, value:0

W0809 21:13:49.235771 7755 metrics.cc:507] Unable to get memory usage for GPU 0. Memory usage status:Success, value:0. Memory total status:Success, value:0

W0809 21:13:50.235922 7755 metrics.cc:468] Unable to get energy consumption for GPU 0. Status:Success, value:0

W0809 21:13:50.235975 7755 metrics.cc:507] Unable to get memory usage for GPU 0. Memory usage status:Success, value:0. Memory total status:Success, value:0

0809 21:13:50.759203 8087 pb_stub.cc:749] Failed to process the request(s) for model '3_queryfeast', message: TypeError: init(): incompatible constructor arguments. The following argument types are supported:

1. c_python_backend_utils.InferenceResponse(output_tensors: List[c_python_backend_utils.Tensor], error: c_python_backend_utils.TritonError = None)
Invoked with: kwargs: tensors=[], error="<class 'TypeError'>, int() argument must be a string, a bytes-like object or a number, not 'NoneType', [<FrameSummary file /tmp/examples/poc_ensemble/3_queryfeast/1/model.py, line 105 in execute>, <FrameSummary file /usr/local/lib/python3.8/dist-packages/merlin/systems/dag/op_runner.py, line 38 in execute>, <FrameSummary file /usr/local/lib/python3.8/dist-packages/merlin/systems/dag/ops/feast.py, line 299 in transform>]"
At:

/tmp/examples/poc_ensemble/3_queryfeast/1/model.py(122): execute
I0809 21:13:50.763532 7755 server.cc:257] Waiting for in-flight requests to complete.

I0809 21:13:50.763625 7755 server.cc:273] Timeout 30: Found 0 model versions that have in-flight inferences

I0809 21:13:50.763644 7755 model_repository_manager.cc:1223] unloading: ensemble_model:1

I0809 21:13:50.763739 7755 model_repository_manager.cc:1223] unloading: 6_softmaxsampling:1

I0809 21:13:50.763802 7755 model_repository_manager.cc:1223] unloading: 5_predicttensorflow:1

I0809 21:13:50.763908 7755 model_repository_manager.cc:1223] unloading: 4_unrollfeatures:1

I0809 21:13:50.763913 7755 model_repository_manager.cc:1328] successfully unloaded 'ensemble_model' version 1

I0809 21:13:50.763978 7755 model_repository_manager.cc:1223] unloading: 3_queryfeast:1

I0809 21:13:50.764104 7755 tensorflow.cc:2368] TRITONBACKEND_ModelInstanceFinalize: delete instance state

I0809 21:13:50.764150 7755 model_repository_manager.cc:1223] unloading: 2_queryfaiss:1

I0809 21:13:50.764230 7755 model_repository_manager.cc:1223] unloading: 1_predicttensorflow:1

I0809 21:13:50.764315 7755 model_repository_manager.cc:1223] unloading: 0_queryfeast:1

I0809 21:13:50.764378 7755 server.cc:288] All models are stopped, unloading models

I0809 21:13:50.764423 7755 server.cc:295] Timeout 30: Found 7 live models and 0 in-flight non-inference requests

I0809 21:13:50.764469 7755 tensorflow.cc:2307] TRITONBACKEND_ModelFinalize: delete model state

I0809 21:13:50.764517 7755 tensorflow.cc:2368] TRITONBACKEND_ModelInstanceFinalize: delete instance state

I0809 21:13:50.764611 7755 tensorflow.cc:2307] TRITONBACKEND_ModelFinalize: delete model state

I0809 21:13:50.772376 7755 model_repository_manager.cc:1328] successfully unloaded '1_predicttensorflow' version 1

I0809 21:13:50.785538 7755 model_repository_manager.cc:1328] successfully unloaded '5_predicttensorflow' version 1

W0809 21:13:51.255108 7755 metrics.cc:468] Unable to get energy consumption for GPU 0. Status:Success, value:0

W0809 21:13:51.255165 7755 metrics.cc:507] Unable to get memory usage for GPU 0. Memory usage status:Success, value:0. Memory total status:Success, value:0

I0809 21:13:51.765027 7755 server.cc:295] Timeout 29: Found 5 live models and 0 in-flight non-inference requests

I0809 21:13:52.083639 7755 model_repository_manager.cc:1328] successfully unloaded '4_unrollfeatures' version 1

I0809 21:13:52.216577 7755 model_repository_manager.cc:1328] successfully unloaded '2_queryfaiss' version 1

I0809 21:13:52.326055 7755 model_repository_manager.cc:1328] successfully unloaded '6_softmaxsampling' version 1

I0809 21:13:52.765186 7755 server.cc:295] Timeout 28: Found 2 live models and 0 in-flight non-inference requests

I0809 21:13:53.765316 7755 server.cc:295] Timeout 27: Found 2 live models and 0 in-flight non-inference requests

I0809 21:13:54.765444 7755 server.cc:295] Timeout 26: Found 2 live models and 0 in-flight non-inference requests

I0809 21:13:55.765592 7755 server.cc:295] Timeout 25: Found 2 live models and 0 in-flight non-inference requests

I0809 21:13:56.765726 7755 server.cc:295] Timeout 24: Found 2 live models and 0 in-flight non-inference requests

I0809 21:13:57.765862 7755 server.cc:295] Timeout 23: Found 2 live models and 0 in-flight non-inference requests

I0809 21:13:58.765989 7755 server.cc:295] Timeout 22: Found 2 live models and 0 in-flight non-inference requests

I0809 21:13:59.766122 7755 server.cc:295] Timeout 21: Found 2 live models and 0 in-flight non-inference requests

I0809 21:14:00.766270 7755 server.cc:295] Timeout 20: Found 2 live models and 0 in-flight non-inference requests

/usr/local/lib/python3.8/dist-packages/merlin/systems/dag/ops/feast.py:15: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.

Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations

ValueType.FLOAT: (np.float, False, False),

I0809 21:14:01.215903 7755 model_repository_manager.cc:1328] successfully unloaded '0_queryfeast' version 1

I0809 21:14:01.766404 7755 server.cc:295] Timeout 19: Found 1 live models and 0 in-flight non-inference requests

I0809 21:14:02.766541 7755 server.cc:295] Timeout 18: Found 1 live models and 0 in-flight non-inference requests

I0809 21:14:03.766678 7755 server.cc:295] Timeout 17: Found 1 live models and 0 in-flight non-inference requests

I0809 21:14:04.766810 7755 server.cc:295] Timeout 16: Found 1 live models and 0 in-flight non-inference requests

/usr/local/lib/python3.8/dist-packages/merlin/systems/dag/ops/feast.py:15: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.

Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations

ValueType.FLOAT: (np.float, False, False),

I0809 21:14:05.224965 7755 model_repository_manager.cc:1328] successfully unloaded '3_queryfeast' version 1

I0809 21:14:05.766953 7755 server.cc:295] Timeout 15: Found 0 live models and 0 in-flight non-inference requests

__________________________________ test_func ___________________________________
def test_func():
    with testbook(
        REPO_ROOT / "examples" / "scaling-criteo" / "02-ETL-with-NVTabular.ipynb",
        execute=False,
        timeout=180,
    ) as tb1:
        tb1.inject(
            """
            import os
            os.environ["BASE_DIR"] = "/tmp/input/criteo/"
            os.environ["INPUT_DATA_DIR"] = "/tmp/input/criteo/"
            os.environ["OUTPUT_DATA_DIR"] = "/tmp/output/criteo/"
            os.system("mkdir -p /tmp/input/criteo")
            os.system("mkdir -p /tmp/output/criteo")

            from merlin.datasets.synthetic import generate_data

            train, valid = generate_data("criteo", int(1000000), set_sizes=(0.7, 0.3))

            train.to_ddf().compute().to_parquet('/tmp/input/criteo/day_0.parquet')
            valid.to_ddf().compute().to_parquet('/tmp/input/criteo/day_1.parquet')
            """
        )


      tb1.execute()


tests/unit/examples/test_scaling_criteo_merlin_models.py:31:

/usr/local/lib/python3.8/dist-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

/usr/local/lib/python3.8/dist-packages/nbclient/util.py:85: in wrapped

return just_run(coro(*args, **kwargs))

/usr/local/lib/python3.8/dist-packages/nbclient/util.py:60: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

/usr/local/lib/python3.8/dist-packages/nbclient/client.py:1022: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)

self = <testbook.client.TestbookNotebookClient object at 0x7f65cc8f51f0>

cell = {'id': '32708ad3', 'cell_type': 'code', 'metadata': {'execution': {'iopub.status.busy': '2022-08-09T21:14:27.065630Z',...ry: CUDA error at: /usr/include/rmm/mr/device/cuda_memory_resource.hpp:70: cudaErrorMemoryAllocation out of memory']}]}

cell_index = 27

exec_reply = {'buffers': [], 'content': {'ename': 'MemoryError', 'engine_info': {'engine_id': -1, 'engine_uuid': '84c7d311-ecc8-4de...e, 'engine': '84c7d311-ecc8-4def-b95b-149b125c2f69', 'started': '2022-08-09T21:14:27.065898Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(
        self.on_cell_error, cell=cell, cell_index=cell_index, execute_reply=exec_reply
    )
    if not cell_allows_errors:


      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)


E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E

E           import os

E           os.environ["BASE_DIR"] = "/tmp/input/criteo/"

E           os.environ["INPUT_DATA_DIR"] = "/tmp/input/criteo/"

E           os.environ["OUTPUT_DATA_DIR"] = "/tmp/output/criteo/"

E           os.system("mkdir -p /tmp/input/criteo")

E           os.system("mkdir -p /tmp/output/criteo")

E

E           from merlin.datasets.synthetic import generate_data

E

E           train, valid = generate_data("criteo", int(1000000), set_sizes=(0.7, 0.3))

E

E           train.to_ddf().compute().to_parquet('/tmp/input/criteo/day_0.parquet')

E           valid.to_ddf().compute().to_parquet('/tmp/input/criteo/day_1.parquet')

E

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mMemoryError�[0m                               Traceback (most recent call last)

E           Input �[0;32mIn [16]�[0m, in �[0;36m<cell line: 12>�[0;34m()�[0m

E           �[1;32m      8�[0m �[38;5;28;01mfrom�[39;00m �[38;5;21;01mmerlin�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mdatasets�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01msynthetic�[39;00m �[38;5;28;01mimport�[39;00m generate_data

E           �[1;32m     10�[0m train, valid �[38;5;241m=�[39m generate_data(�[38;5;124m"�[39m�[38;5;124mcriteo�[39m�[38;5;124m"�[39m, �[38;5;28mint�[39m(�[38;5;241m1000000�[39m), set_sizes�[38;5;241m=�[39m(�[38;5;241m0.7�[39m, �[38;5;241m0.3�[39m))

E           �[0;32m---> 12�[0m �[43mtrain�[49m�[38;5;241;43m.�[39;49m�[43mto_ddf�[49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mcompute�[49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mto_parquet�[49m�[43m(�[49m�[38;5;124;43m'�[39;49m�[38;5;124;43m/tmp/input/criteo/day_0.parquet�[39;49m�[38;5;124;43m'�[39;49m�[43m)�[49m

E           �[1;32m     13�[0m valid�[38;5;241m.�[39mto_ddf()�[38;5;241m.�[39mcompute()�[38;5;241m.�[39mto_parquet(�[38;5;124m'�[39m�[38;5;124m/tmp/input/criteo/day_1.parquet�[39m�[38;5;124m'�[39m)

E

E           File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:5535�[0m, in �[0;36mDataFrame.to_parquet�[0;34m(self, path, args, **kwargs)�[0m

E           �[1;32m   5532�[0m �[38;5;124;03m"""{docstring}"""�[39;00m

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E           File �[0;32m/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101�[0m, in �[0;36mannotate.call..inner�[0;34m(args, **kwargs)�[0m

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E           File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/io/parquet.py:609�[0m, in �[0;36mto_parquet�[0;34m(df, path, engine, compression, index, partition_cols, partition_file_name, partition_offsets, statistics, metadata_file_path, int96_timestamps, row_group_size_bytes, row_group_size_rows, args, **kwargs)�[0m

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E

E           File �[0;32m/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101�[0m, in �[0;36mannotate.call..inner�[0;34m(args, **kwargs)�[0m

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E

E           File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/io/parquet.py:69�[0m, in �[0;36m_write_parquet�[0;34m(df, paths, compression, index, statistics, metadata_file_path, int96_timestamps, row_group_size_bytes, row_group_size_rows, partitions_info, **kwargs)�[0m

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E           File �[0;32mcudf/_lib/parquet.pyx:287�[0m, in �[0;36mcudf._lib.parquet.write_parquet�[0;34m()�[0m

E

E           File �[0;32mcudf/_lib/parquet.pyx:397�[0m, in �[0;36mcudf._lib.parquet.write_parquet�[0;34m()�[0m

E

E           �[0;31mMemoryError�[0m: std::bad_alloc: out_of_memory: CUDA error at: /usr/include/rmm/mr/device/cuda_memory_resource.hpp:70: cudaErrorMemoryAllocation out of memory

E           MemoryError: std::bad_alloc: out_of_memory: CUDA error at: /usr/include/rmm/mr/device/cuda_memory_resource.hpp:70: cudaErrorMemoryAllocation out of memory
/usr/local/lib/python3.8/dist-packages/nbclient/client.py:916: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-08-09 21:14:18,839 - distributed.preloading - INFO - Import preload module: dask_cuda.initialize

2022-08-09 21:14:18,839 - distributed.preloading - INFO - Import preload module: dask_cuda.initialize

/usr/local/lib/python3.8/dist-packages/cudf/core/frame.py:384: UserWarning: The deep parameter is ignored and is only included for pandas compatibility.

warnings.warn(

/usr/local/lib/python3.8/dist-packages/cudf/core/frame.py:384: UserWarning: The deep parameter is ignored and is only included for pandas compatibility.

warnings.warn(

/usr/local/lib/python3.8/dist-packages/cudf/core/frame.py:384: UserWarning: The deep parameter is ignored and is only included for pandas compatibility.

warnings.warn(

/usr/local/lib/python3.8/dist-packages/cudf/core/frame.py:384: UserWarning: The deep parameter is ignored and is only included for pandas compatibility.

warnings.warn(

/usr/lib/python3.8/multiprocessing/resource_tracker.py:216: UserWarning: resource_tracker: There appear to be 24 leaked semaphore objects to clean up at shutdown

warnings.warn('resource_tracker: There appear to be %d '

=========================== short test summary info ============================

FAILED tests/unit/examples/test_building_deploying_multi_stage_RecSys.py::test_func

FAILED tests/unit/examples/test_scaling_criteo_merlin_models.py::test_func - ...

=================== 2 failed, 1 passed in 166.78s (0:02:46) ====================

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/Merlin/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_merlin] $ /bin/bash /tmp/jenkins15926205296964477430.sh

[nvidia-merlin-bot]

Click to view CI Results

GitHub pull request #532 of commit 209f2e7da1bbb6e0802fe357160c8cfdfbd5ecf7, no merge conflicts.
Running as SYSTEM
Setting status of 209f2e7da1bbb6e0802fe357160c8cfdfbd5ecf7 to PENDING with url https://10.20.13.93:8080/job/merlin_merlin/336/console and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_merlin
using credential systems-login
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/Merlin # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/Merlin
 > git --version # timeout=10
using GIT_ASKPASS to set credentials login for merlin-systems
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/Merlin +refs/pull/532/*:refs/remotes/origin/pr/532/* # timeout=10
 > git rev-parse 209f2e7da1bbb6e0802fe357160c8cfdfbd5ecf7^{commit} # timeout=10
Checking out Revision 209f2e7da1bbb6e0802fe357160c8cfdfbd5ecf7 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 209f2e7da1bbb6e0802fe357160c8cfdfbd5ecf7 # timeout=10
Commit message: "Merge branch 'main' into alaiacano/install-tox"
 > git rev-list --no-walk fc1877ac2d8ccfbae97e5c3232538cae3c6c492a # timeout=10
[merlin_merlin] $ /bin/bash /tmp/jenkins4957005427105048996.sh
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.2, pluggy-1.0.0
rootdir: /var/jenkins_home/workspace/merlin_merlin/merlin
plugins: anyio-3.6.1, xdist-2.5.0, forked-1.4.0, cov-3.0.0
collected 3 items
tests/unit/test_version.py .                                             [ 33%]

tests/unit/examples/test_building_deploying_multi_stage_RecSys.py .      [ 66%]

tests/unit/examples/test_scaling_criteo_merlin_models.py .               [100%]
======================== 3 passed in 218.71s (0:03:38) =========================

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/Merlin/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_merlin] $ /bin/bash /tmp/jenkins7838691889047864485.sh