implicit | Fast Python Collaborative Filtering for Implicit Feedback | Recommender System library
kandi X-RAY | implicit Summary
kandi X-RAY | implicit Summary
Fast Python Collaborative Filtering for Implicit Datasets.
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Top functions reviewed by kandi - BETA
- Calculate similar movies from the input data
- Fit the item recommender recommender
- Download the movielens dataset
- Create a logistic matrix factorization
- Benchmark times for a given play
- Check fitting errors
- Check if user_items are in CSR format
- Fit the model
- Calculate similar artists from lastfm
- Return the lastfm dataset
- Get a model by name
- Returns the contents of a file
- Generate a graphviz plot
- Convert to a CPU
- Suggest recommendations for a given user
- Generate the loss graph
- Benchmark implicit learning
- Benchmark the given factors
- Create an hdf5 dataset
- Generate anal speed graph
- Deprecated use recommend_all
- Compute the similarity scores for each user
- Calculate least squares least squares regression
- Generate recommendations for each user
- Benchmark accuracy
- Compute the item factor
implicit Key Features
implicit Examples and Code Snippets
:id: 2uA8X2izXH2b
from jax.lax import while_loop
def fixed_point(f, a, x_guess):
def cond_fun(carry):
x_prev, x = carry
return jnp.abs(x_prev - x) > 1e-6
def body_fun(carry):
_, x = carry
return x, f(a, x)
_, x_star = whi
Subject s = ReplaySubject.create();
s.subscribe(v -> System.out.println(v));
s.onNext(0);
s.onCompleted();
s.onNext(1);
s.onNext(2);
0
with unumpy.determine_backend(array_like, np.ndarray):
unumpy.arange(len(array_like))
def implicit_val_and_grad(f):
"""Returns a function which differentiates f with respect to variables.
The wrapped function returns the value and the gradient of f when called with
the same arguments. The gradient is with respect to all trainab
def implicit_grad(f):
"""Returns a function which differentiates f with respect to variables.
The wrapped function returns the gradient of f when called with the same
arguments. The gradient is with respect to all trainable TFE variables
acc
driver.get("https://www.personality-database.com/profile?pid=1&sort=hot")
wait = WebDriverWait(driver,30)
try:
# Close the footer add
wait.until(EC.element_to_be_clickable((By.XPATH,"//span[@id='ezmob-wrapper']/div/center/span/
>>> engine = sa.create_engine('mysql:///test', echo=True, future=True)
>>> engine._compiled_cache
{}
>>> conn = engine.connect()
2022-04-10
In [36]: integrate(x*(2*x - 1)**100, x).diff(x).factor()
Out[36]:
100
x⋅(2⋅x - 1)
In [34]: Integral(x*(2*x - 1)**100, x).transform(2*x-1, t).doit().subs(t, 2*x-1)
Out[34]:
102 101
df1.update(df2)
a b c
0 0 1.0 0
1 0 0.0 0
2 0 2.0 0
3 0 0.0 0
4 0 3.0 0
df1.update(df2.convert_dtypes())
a b c
0 0 1 0
1 0 0 0
2 0
m = df['time'].notna()
df = df[m | m.groupby(df['ID']).shift(-1,fill_value=False)]
print (df)
ID time country
0 0 NaT ITL
1 0 0 days 01:00:00 USA
3 0 NaT ESP
4 0 2 days 00:05:0
Community Discussions
Trending Discussions on implicit
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
In my version of clang and libc++ (near HEAD
), this static_assert
passes:
ANSWER
Answered 2022-Mar-26 at 23:21std::vector
and other containers (except std::array
) are specified to have a copy constructor. This is not specified to be conditional on whether or not the element type is copyable. Only instantiation of the copy constructor's definition is forbidden if the element type is not copyable.
As a result std::is_copy_constructible_v
on the container will always be true
. There is no way to test whether an instantiation of a definition would be well-formed with a type trait.
It would be possible to specify that the copy constructor is not declared or excluded from overload resolution if the element type is not copyable. However, that would come with a trade-off which is explained in detail in this blog post: https://quuxplusone.github.io/blog/2020/02/05/vector-is-copyable-except-when-its-not/.
In short, if we want to be able to use the container with an incomplete type, e.g. recursively like
QUESTION
Is use in a default member initializer still an odr-use, even if the default member initializer is not used by any constructor?
For example, is this program ill-formed because g
is odr-used and therefore its definition implicitly instantiated?
ANSWER
Answered 2022-Mar-13 at 00:25As stated in the comments, g
is odr-used. However, there is a definition for it available, so there is no non-diagnosable violation here; MSVC is wrong to accept it. (This is true even without the constructor declaration; the implicitly declared B::B()
is never defined, but the default member initializer is still an odr-use like it is here.)
QUESTION
Recently I have found the %$%
pipe operator, but I am missing the point regarding its difference with %>%
and if it could completely replace it.
%$%
- The operator
%$%
could replace%>%
in many cases:
ANSWER
Answered 2022-Feb-08 at 23:14In addition to the provided comments:
%$% also called the Exposition pipe vs. %>%:
This is a short summary of this article https://towardsdatascience.com/3-lesser-known-pipe-operators-in-tidyverse-111d3411803a
"The key difference in using %$% or %>% lies in the type of arguments of used functions."
One advantage, and as far as I can understand it, for me the only one to use %$%
over %>%
is the fact that
we can avoid repetitive input of the dataframe name in functions that have no data as an argument.
For example the lm()
has a data argument. In this case we can use both %>%
and %$%
interchangeable.
But in functions like the cor()
which has no data argument:
QUESTION
In the following code struct A
has two implicit conversion operators to char
and int
, and an instance of the struct is compared for equality against integer constant 2
:
ANSWER
Answered 2022-Jan-21 at 19:00This is CWG 507. An example similar to yours was given, and the submitter explained that according to the standard, the overload resolution is ambiguous, even though this result is very counter-intuitive.
Translating to your particular example, when comparing operator==(int, int)
and operator==(float, int)
to determine which is the better candidate, we have to determine which one has the better implicit conversion sequence for the first argument (obviously in the second argument, no conversion is required). For the first argument of operator==(int, int)
, we just use A::operator int
. For the first argument of operator==(float, int)
, there is no way to decide whether to use A::operator int
or A::operator char
, so we get the "ambiguous conversion sequence". The overload resolution rules say that the ambiguous conversion sequence is no better or worse than any other user-defined conversion sequence. Therefore, the straightforward conversion from A{}
to int
(via A::operator int
) is not considered better than the ambiguous conversion from A{}
to float
. This means neither operator==
candidate is better than the other.
Clang is apparently following the letter of the standard whereas GCC and MSVC are probably doing something else because of the standard seeming to be broken here. "Which compiler is right" depends on your opinion about what the standard should say. There is no proposed resolution on the issues page.
I would suggest removing operator char
unless you really, really need it, in which case you will have to think about what else you're willing to give up.
QUESTION
Given the following code snippet:
...ANSWER
Answered 2022-Jan-10 at 16:12I think this is the open CWG issue 2077.
Basically,
QUESTION
Originally this is a problem coming up in mathematica.SE, but since multiple programming languages have involved in the discussion, I think it's better to rephrase it a bit and post it here.
In short, michalkvasnicka found that in the following MATLAB sample
...ANSWER
Answered 2021-Dec-30 at 12:23tic
/toc
should be fine, but it looks like the timing is being skewed by memory pre-allocation.
I can reproduce similar timings to your MATLAB example, however
On first run (
clear
workspace)- Loop approach takes 2.08 sec
- Vectorised approach takes 1.04 sec
- Vectorisation saves 50% execution time
On second run (workspace not cleared)
- Loop approach takes 2.55 sec
- Vectorised approach takes 0.065 sec
- Vectorisation "saves" 97.5% execution time
My guess would be that since the loop approach explicitly creates a new matrix via zeros
, the memory is reallocated from scratch on every run and you don't see the speed improvement on subsequent runs.
However, when HH
remains in memory and the HH=___
line outputs a matrix of the same size, I suspect MATLAB is doing some clever memory allocation to speed up the operation.
We can prove this theory with the following test:
QUESTION
The following code:
...ANSWER
Answered 2021-Dec-20 at 22:26It's all slightly mysterious. gcc behaves the same as clang.
The standard has this to say (emphasis mine):
Absent default member initializers, if any non-static data member of a union has a non-trivial default constructor, copy constructor, move constructor, copy assignment operator, move assignment operator, or destructor, the corresponding member function of the union must be user-provided or it will be implicitly deleted for the union.
But I think the wording is a bit wooly here. I think what they actually mean is that you must provide an initialiser for the member that has (in your example) a non-trivial constructor, like so:
QUESTION
Suppose I have a simple Duration
class:
ANSWER
Answered 2021-Dec-02 at 16:39You can turn Duration(int t_seconds)
into a template function that can accept an int
and set it to deprecated.
QUESTION
Let's assume I have the following feature defined in Cargo.toml
:
ANSWER
Answered 2021-Oct-13 at 03:05When RFC 3013, "Checking conditional compilation at compile time", is implemented, there will be warnings for a #[cfg]
referring to a feature name that is not declared by Cargo, just as you're asking for. However, the implementation only just got started (Sep 28, 2021).
The means of operation described in the RFC is just as you suggested, ‘cargo
would pass down the flags to rustc
’.
It may be worth noting that this will not check all conditions appearing in the source text; as described in the RFC:
This lint will not be able to detect invalid #[cfg] tests that are within modules that are not compiled, presumably because an ancestor mod is disabled.
So, it will not confirm that all #[cfg(feature)]
are valid on a single cargo check
— you will need to test with your various features or combinations of features. But those are the same combinations that you would need anyway to check for compile errors in all of the regular source code that could be enabled; once you do that, the lint will assure you that you don't have any #[cfg(feature)]
that are never enabled due to a typo.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install implicit
You can use implicit like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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