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zsh: segmentation fault python src/toolkit/app.py #121047

Closed asittiwari07 closed 2 months ago

asittiwari07 commented 2 months ago

Crash report

What happened?

Translated Report (Full Report Below)

Process: jamfRemoteAssistLauncher [62386] Path: /Library/Application Support/JAMF/*/jamfRemoteAssistLauncher Identifier: jamfRemoteAssistLauncher Version: ??? Code Type: ARM-64 (Native) Parent Process: jamfRemoteAssistConnector [58007] Responsible: jamfRemoteAssistConnector [58007] User ID: 0

Date/Time: 2024-06-26 06:56:09.9438 +0530 OS Version: macOS 14.5 (23F79) Report Version: 12 Anonymous UUID: 6049761D-91BD-5C32-E7AB-D91A6A071340

Sleep/Wake UUID: D4443378-E4AF-48DB-A8F9-18BCD0203A7C

Time Awake Since Boot: 54000 seconds

System Integrity Protection: enabled

Crashed Thread: 2

Exception Type: EXC_CRASH (SIGABRT) Exception Codes: 0x0000000000000000, 0x0000000000000000

Termination Reason: Namespace SIGNAL, Code 6 Abort trap: 6 Terminating Process: jamfRemoteAssistLauncher [62386]

Application Specific Information: abort() called

Thread 0:: Dispatch queue: com.apple.main-thread 0 libsystem_kernel.dylib 0x18f0319ec __psynch_cvwait + 8 1 libsystem_pthread.dylib 0x18f06f55c _pthread_cond_wait + 1228 2 jamfRemoteAssistLauncher 0x1046d8cbc 0x104660000 + 494780 3 jamfRemoteAssistLauncher 0x104864194 0x104660000 + 2113940 4 dyld 0x18ece60e0 start + 2360

Thread 1: 0 libsystem_pthread.dylib 0x18f069d20 start_wqthread + 0

Thread 2 Crashed: 0 libsystem_kernel.dylib 0x18f036a60 __pthread_kill + 8 1 libsystem_pthread.dylib 0x18f06ec20 pthread_kill + 288 2 libsystem_c.dylib 0x18ef7ba30 abort + 180 3 libsystem_malloc.dylib 0x18ee8bdc4 malloc_vreport + 896 4 libsystem_malloc.dylib 0x18ee8f430 malloc_report + 64 5 libsystem_malloc.dylib 0x18eea9494 find_zone_and_free + 528 6 jamfRemoteAssistLauncher 0x1048439a0 0x104660000 + 1980832 7 jamfRemoteAssistLauncher 0x10480f7cc 0x104660000 + 1767372 8 jamfRemoteAssistLauncher 0x1048bc0fc 0x104660000 + 2474236 9 jamfRemoteAssistLauncher 0x104896f80 0x104660000 + 2322304 10 jamfRemoteAssistLauncher 0x104897e20 0x104660000 + 2326048 11 libsystem_pthread.dylib 0x18f06ef94 _pthread_start + 136 12 libsystem_pthread.dylib 0x18f069d34 thread_start + 8

Thread 3: 0 libsystem_pthread.dylib 0x18f069d20 start_wqthread + 0

Thread 4: 0 libsystem_pthread.dylib 0x18f069d20 start_wqthread + 0

Thread 5: 0 libsystem_kernel.dylib 0x18f03218c __unlink + 8 1 libsystem_kernel.dylib 0x18f032168 unlink + 16 2 jamfRemoteAssistLauncher 0x1048cce24 0x104660000 + 2543140 3 jamfRemoteAssistLauncher 0x1048c2e60 0x104660000 + 2502240 4 jamfRemoteAssistLauncher 0x1048bd06c 0x104660000 + 2478188 5 jamfRemoteAssistLauncher 0x1048a16a4 0x104660000 + 2365092 6 jamfRemoteAssistLauncher 0x1048a0fb0 0x104660000 + 2363312 7 jamfRemoteAssistLauncher 0x10485b6c4 0x104660000 + 2078404 8 jamfRemoteAssistLauncher 0x104867dac 0x104660000 + 2129324 9 jamfRemoteAssistLauncher 0x104866a0c 0x104660000 + 2124300 10 jamfRemoteAssistLauncher 0x104879b5c 0x104660000 + 2202460 11 libsystem_pthread.dylib 0x18f06ef94 _pthread_start + 136 12 libsystem_pthread.dylib 0x18f069d34 thread_start + 8

Thread 6: 0 libsystem_kernel.dylib 0x18f02e6a4 mach_absolute_time + 80 1 libsystem_kernel.dylib 0x18f0300d8 __commpage_gettimeofday_internal + 44 2 libsystem_c.dylib 0x18ef0bdd4 gettimeofday + 56 3 jamfRemoteAssistLauncher 0x1046d8c28 0x104660000 + 494632 4 jamfRemoteAssistLauncher 0x1048bb414 0x104660000 + 2470932 5 jamfRemoteAssistLauncher 0x1048bae04 0x104660000 + 2469380 6 jamfRemoteAssistLauncher 0x1048ac4a0 0x104660000 + 2409632 7 jamfRemoteAssistLauncher 0x1046e97b4 0x104660000 + 563124 8 libsystem_pthread.dylib 0x18f06ef94 _pthread_start + 136 9 libsystem_pthread.dylib 0x18f069d34 thread_start + 8

Thread 7: 0 libsystem_kernel.dylib 0x18f032780 __recvfrom + 8 1 jamfRemoteAssistLauncher 0x10470b518 0x104660000 + 701720 2 jamfRemoteAssistLauncher 0x1048a29d0 0x104660000 + 2370000 3 jamfRemoteAssistLauncher 0x1046e97b4 0x104660000 + 563124 4 libsystem_pthread.dylib 0x18f06ef94 _pthread_start + 136 5 libsystem_pthread.dylib 0x18f069d34 thread_start + 8

Thread 8: 0 libsystem_pthread.dylib 0x18f069d20 start_wqthread + 0

Thread 9: 0 libsystem_pthread.dylib 0x18f069d20 start_wqthread + 0

Thread 10: 0 libsystem_pthread.dylib 0x18f069d20 start_wqthread + 0

Thread 11: 0 libsystem_pthread.dylib 0x18f069d20 start_wqthread + 0

Thread 12: 0 libsystem_kernel.dylib 0x18f03261c __select_nocancel + 8 1 libsystem_dnssd.dylib 0x19bcde640 deliver_request + 692 2 libsystem_dnssd.dylib 0x19bcdde3c DNSServiceCreateConnection + 108 3 libsystem_info.dylib 0x18f0ad298 _mdns_search_ex + 584 4 libsystem_info.dylib 0x18f0afc68 mdns_addrinfo + 360 5 libsystem_info.dylib 0x18f0afab0 search_addrinfo + 176 6 libsystem_info.dylib 0x18f0a8b64 si_addrinfo + 1312 7 libsystem_info.dylib 0x18f0a859c getaddrinfo + 168 8 jamfRemoteAssistLauncher 0x104809afc 0x104660000 + 1743612 9 jamfRemoteAssistLauncher 0x1048025e4 0x104660000 + 1713636 10 jamfRemoteAssistLauncher 0x10480d144 0x104660000 + 1757508 11 libsystem_pthread.dylib 0x18f06ef94 _pthread_start + 136 12 libsystem_pthread.dylib 0x18f069d34 thread_start + 8

Thread 2 crashed with ARM Thread State (64-bit): x0: 0x0000000000000000 x1: 0x0000000000000000 x2: 0x0000000000000000 x3: 0x0000000000000000 x4: 0x0000000000000073 x5: 0x000000000000002e x6: 0x0000000000000001 x7: 0x0000000000000000 x8: 0x02e0e53ee7f669a6 x9: 0x02e0e53f8c7419a6 x10: 0x000000000000000a x11: 0x0000000000000000 x12: 0x0000000000000036 x13: 0x0000000000000000 x14: 0x0000000107900000 x15: 0x000000000000000c x16: 0x0000000000000148 x17: 0x000000020125d928 x18: 0x0000000000000000 x19: 0x0000000000000006 x20: 0x000000016b827000 x21: 0x000000000000100b x22: 0x000000016b8270e0 x23: 0x000000016b826dd0 x24: 0x0000000000000000 x25: 0x0000000000000000 x26: 0x000000016b79fcd0 x27: 0x000000016b827000 x28: 0x0000600000c84000 fp: 0x000000016b826720 lr: 0x000000018f06ec20 sp: 0x000000016b826700 pc: 0x000000018f036a60 cpsr: 0x40001000 far: 0x0000000000000000 esr: 0x56000080 Address size fault

Binary Images: 0x104660000 - 0x10495bfff jamfRemoteAssistLauncher () <2847cde0-2a27-35da-ab51-6c8271405858> /Library/Application Support/JAMF//jamfRemoteAssistLauncher 0x18f02d000 - 0x18f067ffb libsystem_kernel.dylib () <9b8b53f9-e2b6-36df-98e9-28d8fca732f2> /usr/lib/system/libsystem_kernel.dylib 0x18f068000 - 0x18f074fff libsystem_pthread.dylib () <386b0fc1-7873-3328-8e71-43269fd1b2c7> /usr/lib/system/libsystem_pthread.dylib 0x18ece0000 - 0x18ed68a17 dyld () <37bbc384-0755-31c7-a808-0ed49e44dd8e> /usr/lib/dyld 0x0 - 0xffffffffffffffff ??? () <00000000-0000-0000-0000-000000000000> ??? 0x18ef05000 - 0x18ef83ff7 libsystem_c.dylib () <05b44e93-dffc-3bd8-90ab-fd97cb73f171> /usr/lib/system/libsystem_c.dylib 0x18ee7d000 - 0x18eeb9ff7 libsystem_malloc.dylib () /usr/lib/system/libsystem_malloc.dylib 0x19bcdd000 - 0x19bce5fff libsystem_dnssd.dylib () <5b174353-095d-346a-9f28-14a42de6b305> /usr/lib/system/libsystem_dnssd.dylib 0x18f0a3000 - 0x18f0cfffb libsystem_info.dylib () <927ab7d1-ea20-36ce-a394-e86f5af9375b> /usr/lib/system/libsystem_info.dylib

External Modification Summary: Calls made by other processes targeting this process: task_for_pid: 0 thread_create: 0 thread_set_state: 0 Calls made by this process: task_for_pid: 0 thread_create: 0 thread_set_state: 0 Calls made by all processes on this machine: task_for_pid: 0 thread_create: 0 thread_set_state: 0

VM Region Summary: ReadOnly portion of Libraries: Total=779.5M resident=0K(0%) swapped_out_or_unallocated=779.5M(100%) Writable regions: Total=1.9G written=0K(0%) resident=0K(0%) swapped_out=0K(0%) unallocated=1.9G(100%)

                            VIRTUAL   REGION

REGION TYPE SIZE COUNT (non-coalesced) =========== ======= ======= Activity Tracing 256K 1 Kernel Alloc Once 32K 1 MALLOC 1.9G 45 MALLOC guard page 96K 6 STACK GUARD 56.2M 13 Stack 14.4M 14 VM_ALLOCATE 16K 1 AUTH 731K 171 AUTH_CONST 12.7M 312 DATA 3204K 300 DATA_CONST 15.8M 315 DATA_DIRTY 703K 106 __FONT_DATA 4K 1 LINKEDIT 533.2M 2 OBJC_RO 71.9M 1 __OBJC_RW 2199K 1 TEXT 246.3M 329 dyld private memory 272K 2 mapped file 31.4M 3 shared memory 48K 3 =========== ======= ======= TOTAL 2.8G 1627

Full Report

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"jamfRemoteAssistLauncher", "procPath" : "\/Library\/Application Support\/JAMF\/*\/jamfRemoteAssistLauncher", "parentProc" : "jamfRemoteAssistConnector", "parentPid" : 58007, "coalitionName" : "com.jamf.remoteassist.connector", "crashReporterKey" : "6049761D-91BD-5C32-E7AB-D91A6A071340", "responsiblePid" : 58007, "responsibleProc" : "jamfRemoteAssistConnector", "codeSigningID" : "com.jamf.remoteassist.launcher", "codeSigningTeamID" : "483DWKW443", "codeSigningFlags" : 570503953, "codeSigningValidationCategory" : 6, "codeSigningTrustLevel" : 4294967295, "instructionByteStream" : {"beforePC":"fyMD1f17v6n9AwCRW+D\/l78DAJH9e8Go\/w9f1sADX9YQKYDSARAA1A==","atPC":"AwEAVH8jA9X9e7+p\/QMAkVDg\/5e\/AwCR\/XvBqP8PX9bAA1\/WcAqA0g=="}, "sleepWakeUUID" : "D4443378-E4AF-48DB-A8F9-18BCD0203A7C", "sip" : "enabled", "exception" : {"codes":"0x0000000000000000, 0x0000000000000000","rawCodes":[0,0],"type":"EXC_CRASH","signal":"SIGABRT"}, "termination" : 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CPython versions tested on:

3.10

Operating systems tested on:

macOS

Output from running 'python -VV' on the command line:

Python 3.10.11 (v3.10.11:7d4cc5aa85, Apr 4 2023, 19:05:19) [Clang 13.0.0 (clang-1300.0.29.30)]

ronaldoussoren commented 2 months ago

I don't see a reference to Python in the crash report, why do you think this issue is related to Python?

picnixz commented 2 months ago

I don't see a reference to Python in the crash report

I think it's because of src/toolkit/app.py but I highly suspect that this is not an issue from the core library itself. Unless we know what src/toolkit/app.py does, I don't think we can help.

asittiwari07 commented 2 months ago

I am running a Python code in Mac M3 Sonoma 14.5. And it gives me Segmentation fault 11. Can you guide me what us leading this fault? The code app.py is running a pytorch_lightning code. I crashes the moment it starts.

picnixz commented 2 months ago

Without the source code, we cannot help you. It might be an issue with pytorch_lightning and thus, the issue should be reported on their side (or it might also be an issue with what is written in that code).

asittiwari07 commented 2 months ago

I have run the same code on Windows and it worked, but failed in MacOs.

picnixz commented 2 months ago

You are still not giving me the code. Without the content of src/toolkit/app.py, we cannot help you at all. We don't know what your code is supposed to do.

asittiwari07 commented 2 months ago

`import pandas as pd import concurrent.futures from statsmodel import StatsForecastModels import neuralmodel as nm

from neuralmodel import NeuralForecastModels

from utilsforecast.evaluation import evaluate from utilsforecast.losses import smape, mape, mse, rmse, mae, rmae, mase

date_mapping = { "MM/DD/YYYY": "%m-%d-%Y", "DD/MM/YYYY": "%d-%m-%Y", "DD-MM-YYYY": "%d-%m-%Y", "MM-DD-YYYY": "%m-%d-%Y", "YYYY/MM/DD": "%Y-%m-%d", }

def rank_forecast(pred, evaluate):

df_tmp_transform_ = evaluate__.reset_index().T.reset_index()
headers = df_tmp_transform_.iloc[0]
df_tmp_rank_ = pd.DataFrame(df_tmp_transform_.values[1:], columns=headers)
df_tmp_rank_.rename(columns={"unique_id": "models"}, inplace=True)
df_tmp_rank_ = df_tmp_rank_[df_tmp_rank_["models"] != "best_model"].reset_index(
    drop=True
)
df_int_ = pd.DataFrame()
for id_ in pred__["unique_id"].unique():
    df_tmp_rank_[id_] = df_tmp_rank_[id_].astype(float)
    df_tmp_ = df_tmp_rank_[["models", id_]].sort_values(by=id_)
    df_tmp_pred = pd.DataFrame()
    rank = 1
    for mdl_ in df_tmp_["models"]:
        df_tmp_pred = pred__[pred__["unique_id"] == id_].reset_index(drop=True)[
            ["unique_id", "ds"]
        ]
        df_tmp_pred["model"] = mdl_
        df_tmp_pred["forecast"] = pred__[mdl_]
        df_tmp_pred["rank"] = rank
        df_int_ = pd.concat([df_int_, df_tmp_pred], ignore_index=True)
        rank += 1

return df_int_

def evaluate_cross_validation(df, metric): error_metric = globals()[metric] models = df.drop(columns=["uniqueid", "ds", "cutoff", "y"]).columns.tolist() evals = [] for cutoff in df["cutoff"].unique(): eval = evaluate( df[df["cutoff"] == cutoff], metrics=[errormetric], models=models ) evals.append(eval) evaluated = pd.concat(evals) evaluated = evaluated.groupby("unique_id").mean(numeric_only=True)

evaluated.insert(0, "best_model", evaluated.idxmin(axis=1))
return evaluated

def train_statistical_model(df, model_type, seasonal_length, date_format, data_frequency, forecast_horizon, ignore_neg_fcsts, error_metric, eval): stats = StatsForecastModels( model_type=[model_type], seasonal_length=seasonal_length, freq=data_frequency, date_format=date_format, ) stats.fit(df) df_pred = stats.predict(horizon=forecast_horizon, ignore_neg_fcsts=ignore_neg_fcsts) df_crossval = stats.crossvalidation(error_metric=error_metric, ) #ignore_neg_fcsts=ignore_neg_fcsts)

if eval:
    df_performance = evaluate_cross_validation(df_crossval, error_metric)
    df_rank = rank_forecast(df_pred, df_performance)
else:
    df_performance, df_rank = pd.DataFrame(), pd.DataFrame()

return df_pred, df_performance, df_rank, df_crossval

def train_neural_model(df, model_type, date_format, data_frequency, forecast_horizon, ignore_neg_fcsts, error_metric, eval): neural = nm.NeuralForecastModels( model_type=[model_type], forecast_horizon=forecast_horizon, freq=data_frequency, date_format=date_format, MDL_SPEED_MAPPING=nm.MDL_SPEED_MAPPING, NEURAL_MDL=nm.NEURAL_MDL, MDL_PARAMETERS=nm.MDL_PARAMETERS, ENSEMBLE_MAPPING=nm.ENSEMBLE_MAPPING, ) neural.fit(df) df_pred = neural.predict(horizon=forecast_horizon, ignore_neg_fcsts=ignore_neg_fcsts) df_crossval = neural.crossvalidation( error_metric=error_metric, ignore_neg_fcsts=ignore_neg_fcsts )

if eval:
    df_performance = evaluate_cross_validation(df_crossval, error_metric)
    df_rank = rank_forecast(df_pred, df_performance)
else:
    df_performance, df_rank = pd.DataFrame(), pd.DataFrame()

return df_pred, df_performance, df_rank, df_crossval

def run_forecast( seasonal_length, data_frequency, error_metric, ignore_neg_fcsts, date_format, forecast_horizon, df, model_type, ):

# Define a helper function to train the models in parallel
def train_models(model_type, eval=True):
    if model_type == "Statistical":
        return train_statistical_model(df, model_type, seasonal_length, date_format, data_frequency, forecast_horizon, 
                                       ignore_neg_fcsts, error_metric, eval=eval)
    elif model_type == "Machine-Learning":
        return train_neural_model(df, model_type, date_format, data_frequency, forecast_horizon, ignore_neg_fcsts, 
                                  error_metric, eval=eval)

if model_type in ["Statistical & Machine-Learning", "Test"]:
    if model_type=="Test":
        type1 = "Test"
        type2 = "Test"
    else:
        type1 = "Statistical"
        type2 = "Machine-Learning"

    with concurrent.futures.ThreadPoolExecutor() as executor:
        future_s = executor.submit(train_statistical_model, df, type1, seasonal_length, date_format, data_frequency, forecast_horizon, ignore_neg_fcsts, error_metric, eval=False)
        future_n = executor.submit(train_neural_model, df, type2, date_format, data_frequency, forecast_horizon, ignore_neg_fcsts, error_metric, eval=False)

        df_pred_s, _, _, df_crossval_s = future_s.result()
        df_pred_n, _, _, df_crossval_n = future_n.result()

    df_pred = df_pred_s.merge(df_pred_n, on=["unique_id", "ds"], how="inner")
    df_crossval_s["y"] = df_crossval_s["y"].astype("Float32")
    df_crossval_n["y"] = df_crossval_n["y"].astype("float32")
    df_crossval = pd.merge(df_crossval_s, df_crossval_n, on=["unique_id", "ds", "cutoff", "y"], how="inner")
    ensemble_col_ = [
        col
        for col in df_pred.columns
        if (("ensemble" not in col) & ("ds" not in col) & ("unique_id" not in col))
    ]
    df_pred["Stats & ML ensemble"] = df_pred[ensemble_col_].mean(axis=1)
    df_performance = evaluate_cross_validation(df_crossval, error_metric)
    df_rank = rank_forecast(df_pred, df_performance)

    return df_pred, df_performance, df_rank, df_crossval
else:
    return train_models(model_type)

if name == "main": df = pd.read_csv('./src/data/FakeProjectDailyData__.csv')

df_pred, df_performance, df_rank, df_crossval = run_forecast(
    seasonal_length=12,
    data_frequency="D",
    error_metric="rmse",
    ignore_neg_fcsts=False,
    date_format="DD-MM-YYYY",
    forecast_horizon=13,
    df=df,
    model_type="Machine-Learning",
)

print(df_pred)

`

asittiwari07 commented 2 months ago

The problem happens when i run the neuralmodel, which is open source package called Nixtla which is a pytorch Lightning based Models like NHITS, RNN etc. The input data is like, Col 1 unique ID's, col2 is Dates and Col3 is values, The code runs fine in windows machine, but have segmentation fault in MacOs M3 Sonoma 14.5. For your reference attaching the nixtla link i used https://nixtlaverse.nixtla.io/neuralforecast/index.html. if you need some other code then please do let me know, i will be able to attach.

picnixz commented 2 months ago

Mmh, so it's something related to a third-party library (probably). I would suggest you open an issue on neuralmodel but you need to include the python traceback, not the system traceback. Like, if you run python src/toolkit/app.py, do you simply get a message like "Segmentation fault" or do you get more?

By the way, I see that there is some ThreadPoolExecutor being used, so before that I'd suggest you try to remove whatever parallelization code being used. I suspect that the issue is with this neuralmodel library or maybe with statsmodel (I don't know what is being implemented out there). Could you try to reproduce a crash with a smaller example and with that library? in addition, could we get the Python output (like, if there's an exception being thrown before the segmentation fault or something like that).

asittiwari07 commented 2 months ago

I have tried this without the ThreadPoolExecutor and it still does not work. I simply get "Segmentation fault" without anything else. The stats model run without any issue but the problem is only with neural model. I can also send you the neural model code if needed, Its simple code.

ambv commented 2 months ago

This is not an issue related to CPython. Please use StackOverflow or discuss.python.org to find help with third-party libraries.