pwinston

"""Testing reading zarr file with zarr vs. dask."""
import random
import subprocess
import time
from contextlib import contextmanager

import click
import dask.array as da
import numpy as np

pwinston

"""Testing reading zarr file with zarr vs. dask."""

import random
import time
from contextlib import contextmanager

import click
import dask.array as da
import numpy as np

pwinston

"""Shared Memory Test Client
"""
import json
import sys
from multiprocessing.shared_memory import ShareableList


def client(shared_name):
    print(f"Client: connecting to list {shared_name}")
    shared_list = ShareableList(name=shared_name)

pwinston

0 for 0.9646884955141247 seconds...
0 for 0.11369650717941382 seconds...
START
0 for 0.22684639879222868 seconds...
1 for 0.6087105797872412 seconds...
2 for 0.1083723869027553 seconds...
3 for 0.4503304613576756 seconds...
4 for 0.15777555608431404 seconds...
6 for 0.46535064391450154 seconds...
7 for 0.6102392954226735 seconds...

pwinston

import os

import dask.array as da
import time
import random
import threading
import numpy as np

data = da.random.randint(0, 255, (100,) * 3, chunks=(10,) * 3, dtype='uint8')

pwinston

{
    "active": [
        "chunk_loader",
        "vispy_rendering"
    ],
    "trace_sets": {
        "chunk_loader": [
            "napari.components.dims.Dims.set_point",
            "napari.components.viewer_model.ViewerModel._update_layers",
            "napari.layers.image._image_slice.ImageSlice.chunk_loaded",

pwinston

#!/usr/bin/env python
import contextlib
import time

import numpy as np
import dask.array as da


@contextlib.contextmanager
def perf_timer(name: str):

pwinston

#!/usr/bin/env python
import contextlib
import time

import numpy as np

from torchvision.datasets import MNIST
from torchvision import transforms
from torch.utils.data import Dataset
from torch import randn

pwinston

#!/usr/bin/env python
import contextlib
import time

import numpy as np

from torchvision.datasets import MNIST
from torchvision import transforms
from torch.utils.data import Dataset
from torch import randn

pwinston

#!/usr/bin/env python
import contextlib
import time

import numpy as np

from torchvision.datasets import MNIST
from torchvision import transforms
from torch.utils.data import Dataset
from torch import randn