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https://www.tensorflo

In the solution for the pastebin/bitly system design, the write to cache flow is missing in the second diagram which refers to the scaling aspect. The cache has only a read arrow but not a write arrow. The diagram will be more intuitive if a write-through/write-back cache mechanism was indicated.

line 123@
X, Y = read_images(DATASET_PATH, MODE, batch_size)
line 66@
classes = sorted(os.walk(dataset_path).next()[1])
StopIteration

Is there a way Tensorflow git cloned repositories can run without overhead issues?

Repro:

@torch.jit.script
class Timebase:
    def __init__(
        self,
        numerator,  # type: int
        denominator,  # type: int
    ):
        # type: (...) -> None
        self.numerator = numerator  # type: int
        self.denominator = denominator  # type: int

Produces the error:

RuntimeError: Return type line '# type: (...) -> ...' not found on multiline 

• face_recognition version: 1.2.3
• Python version: 3.7
• Operating System: Pop!_OS 19.04
• CUDA + CuDNN version: 10.0

I'm trying to use the facerec_from_webcam_multiprocessing.py example with cuda support, but everytime I run it I get this error:

Width: 640, Height: 480, FPS: 30
Process Process-5:
Traceback (most recent call last):
  File "/usr/lib/python3.7/multiprocessing/proce

Target Leakage in mentioned steps in Data Preprocessing. Train/test split needs to be before missing value imputation. Else you will have a bias in test/eval/serve.

Description

The instructor in the above mentioned video has created a new version of the same tutorial, which can be found here

Why

It is always good to keep resources and tutorials up-to-date. The new video talks about namespaces, chroot and cgroups, and speaks about containers at a greater depth.

Is this something you're interest

数轴上放置了一些筹码，每个筹码的位置存在数组 chips 当中。

你可以对 任何筹码 执行下面两种操作之一（不限操作次数，0 次也可以）：

将第 i 个筹码向左或者右移动 2 个单位，代价为 0。
将第 i 个筹码向左或者右移动 1 个单位，代价为 1。
最开始的时候，同一位置上也可能放着两个或者更多的筹码。

返回将所有筹码移动到同一位置（任意位置）上所需要的最小代价。

示例 1：

输入：chips = [1,2,3]
输出：1
解释：第二个筹码移动到位置三的代价是 1，第一个筹码移动到位置三的代价是 0，总代价为 1。
示例 2：

输入：chips = [2,2,2,3,3]
输出：2
解释：第四和第五个筹码移动到位置二的代价都是 1，所以最小总代价为 2。
 

提示：

1 <= chips.length <= 1

In the PCA section there is the following quote:

We see that these 150 components account for just over 90% of the variance.

While not inaccurate (150 componen