list | C doubly linked list
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C doubly linked list
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def _as_shape_list(shapes,
dtypes,
unknown_dim_allowed=False,
unknown_rank_allowed=False):
"""Convert shapes to a list of tuples of int (or None)."""
del dtypes
if unknown_dim_allowed:
def flatten_metrics_in_order(logs, metrics_names):
"""Turns the `logs` dict into a list as per key order of `metrics_names`."""
results = []
for name in metrics_names:
if name in logs:
results.append(logs[name])
for key in sorted(lo
def _total_size(shape_values):
"""Given list of tensor shape values, returns total size.
If shape_values contains tensor values (which are results of
array_ops.shape), then it returns a scalar tensor.
If not, it returns an integer."""
resu
Community Discussions
Trending Discussions on list
QUESTION
I have been trying to learn about functional programming, but I still struggle with thinking like a functional programmer. One such hangup is how one would implement index-heavy operations which rely strongly on loops/order-of-execution.
For example, consider the following Java code:
...ANSWER
Answered 2022-Mar-07 at 21:17This is not an index-heavy operation, in fact you can do this with a one-liner with scanl1 :: (a -> a -> a) -> [a] -> [a]
:
QUESTION
I saw a video about speed of loops in python, where it was explained that doing sum(range(N))
is much faster than manually looping through range
and adding the variables together, since the former runs in C due to built-in functions being used, while in the latter the summation is done in (slow) python. I was curious what happens when adding numpy
to the mix. As I expected np.sum(np.arange(N))
is the fastest, but sum(np.arange(N))
and np.sum(range(N))
are even slower than doing the naive for loop.
Why is this?
Here's the script I used to test, some comments about the supposed cause of slowing done where I know (taken mostly from the video) and the results I got on my machine (python 3.10.0, numpy 1.21.2):
updated script:
...ANSWER
Answered 2021-Oct-16 at 17:42From the cpython source code for sum
sum initially seems to attempt a fast path that assumes all inputs are the same type. If that fails it will just iterate:
QUESTION
I have a project which was running well yesterday, but today I find this problem:
Could not resolve all files for configuration ':app:debugRuntimeClasspath'. Could not resolve com.google.android.gms:play-services-location:16.+. Required by: project :app > project :location > Failed to list versions for com.google.android.gms:play-services-location. > Unable to load Maven meta-data from https://google.bintray.com/exoplayer/com/google/android/gms/play-services-location/maven-metadata.xml. > Could not get resource 'https://google.bintray.com/exoplayer/com/google/android/gms/play-services-location/maven-metadata.xml'. > Could not GET 'https://google.bintray.com/exoplayer/com/google/android/gms/play-services-location/maven-metadata.xml'. Received status code 502 from server: Bad Gateway
acutely I'm using classpath 'com.android.tools.build:gradle:4.1.0'
with distributionUrl=https://services.gradle.org/distributions/gradle-6.5-bin.zip
I have followed this question
and I upgraded 'com.android.tools.build:gradle:4.1.0'
to classpath 'com.android.tools.build:gradle:4.2.0'
then I changed distributionUrl=https://services.gradle.org/distributions/gradle-6.5-bin.zip
to distributionUrl=https\://services.gradle.org/distributions/gradle-6.7.1-all.zip
but I still got the error.
my android/build.gradle:
...ANSWER
Answered 2021-Dec-01 at 09:09It looks like a temporary issue, the server with these libraries is down. I have the same problem now with Room:
QUESTION
I know about the zip
function (which will zip according to the shortest list) and zip_longest
(which will zip according to the longest list), but how would I zip according to the first list, regardless of whether it's the longest or not?
For example:
...ANSWER
Answered 2022-Mar-17 at 23:27Return only len(a)
elements from zip_longest
:
QUESTION
I have an array of positive integers. For example:
...ANSWER
Answered 2022-Feb-27 at 22:44This problem has a fun O(n) solution.
If you draw a graph of cumulative sum vs index, then:
The average value in the subarray between any two indexes is the slope of the line between those points on the graph.
The first highest-average-prefix will end at the point that makes the highest angle from 0. The next highest-average-prefix must then have a smaller average, and it will end at the point that makes the highest angle from the first ending. Continuing to the end of the array, we find that...
These segments of highest average are exactly the segments in the upper convex hull of the cumulative sum graph.
Find these segments using the monotone chain algorithm. Since the points are already sorted, it takes O(n) time.
QUESTION
Just today, whenever I run terraform apply
, I see an error something like this: Can't configure a value for "lifecycle_rule": its value will be decided automatically based on the result of applying this configuration.
It was working yesterday.
Following is the command I run: terraform init && terraform apply
Following is the list of initialized provider plugins:
...ANSWER
Answered 2022-Feb-15 at 13:49Terraform AWS Provider is upgraded to version 4.0.0 which is published on 10 February 2022.
Major changes in the release include:
- Version 4.0.0 of the AWS Provider introduces significant changes to the aws_s3_bucket resource.
- Version 4.0.0 of the AWS Provider will be the last major version to support EC2-Classic resources as AWS plans to fully retire EC2-Classic Networking. See the AWS News Blog for additional details.
- Version 4.0.0 and 4.x.x versions of the AWS Provider will be the last versions compatible with Terraform 0.12-0.15.
The reason for this change by Terraform is as follows: To help distribute the management of S3 bucket settings via independent resources, various arguments and attributes in the aws_s3_bucket
resource have become read-only. Configurations dependent on these arguments should be updated to use the corresponding aws_s3_bucket_*
resource. Once updated, new aws_s3_bucket_*
resources should be imported into Terraform state.
So, I updated my code accordingly by following the guide here: Terraform AWS Provider Version 4 Upgrade Guide | S3 Bucket Refactor
The new working code looks like this:
QUESTION
This code:
...ANSWER
Answered 2022-Feb-04 at 21:21I suspect this may have been an accident, though I prefer the new behavior.
The new behavior is a consequence of a change to how the bytecode for *
arguments works. The change is in the changelog under Python 3.9.0 alpha 3:
bpo-39320: Replace four complex bytecodes for building sequences with three simpler ones.
The following four bytecodes have been removed:
- BUILD_LIST_UNPACK
- BUILD_TUPLE_UNPACK
- BUILD_SET_UNPACK
- BUILD_TUPLE_UNPACK_WITH_CALL
The following three bytecodes have been added:
- LIST_TO_TUPLE
- LIST_EXTEND
- SET_UPDATE
On Python 3.8, the bytecode for f(*a, a.pop())
looks like this:
QUESTION
This is a React web app. When I run
...ANSWER
Answered 2021-Nov-13 at 18:36I am also stuck with the same problem because I installed the latest version of Node.js (v17.0.1).
Just go for node.js v14.18.1
and remove the latest version just use the stable version v14.18.1
QUESTION
In the following code, I create two lists with the same values: one list unsorted (s_not), the other sorted (s_yes). The values are created by randint(). I run some loop for each list and time it.
...ANSWER
Answered 2021-Nov-15 at 21:05Cache misses. When N
int objects are allocated back-to-back, the memory reserved to hold them tends to be in a contiguous chunk. So crawling over the list in allocation order tends to access the memory holding the ints' values in sequential, contiguous, increasing order too.
Shuffle it, and the access pattern when crawling over the list is randomized too. Cache misses abound, provided there are enough different int objects that they don't all fit in cache.
At r==1
, and r==2
, CPython happens to treat such small ints as singletons, so, e.g., despite that you have 10 million elements in the list, at r==2
it contains only (at most) 100 distinct int objects. All the data for those fit in cache simultaneously.
Beyond that, though, you're likely to get more, and more, and more distinct int objects. Hardware caches become increasingly useless then when the access pattern is random.
Illustrating:
QUESTION
One of my friends asked me about this piece of code:
...ANSWER
Answered 2021-Oct-21 at 20:47The answer is in the PEP of the generator expressions, in particular the session Early Binding vs Late biding:
After much discussion, it was decided that the first (outermost) for-expression should be evaluated immediately and that the remaining expressions be evaluated when the generator is executed.
So basically the array
in:
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