cast | safe and easy casting from one type to another in Go | JSON Processing library
kandi X-RAY | cast Summary
kandi X-RAY | cast Summary
Cast is a library to convert between different go types in a consistent and easy way. Cast provides simple functions to easily convert a number to a string, an interface into a bool, etc. Cast does this intelligently when an obvious conversion is possible. It doesn’t make any attempts to guess what you meant, for example you can only convert a string to an int when it is a string representation of an int such as “8”. Cast was developed for use in [Hugo] a website engine which uses YAML, TOML or JSON for meta data.
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cast Examples and Code Snippets
Lines of Code : 67License : Non-SPDX (Apache License 2.0)
Copydef cast(x, dtype, name=None):
"""Casts a tensor to a new type.
The operation casts `x` (in case of `Tensor`) or `x.values`
(in case of `SparseTensor` or `IndexedSlices`) to `dtype`.
For example:
>>> x = tf.constant([1.8, 2.2], def _cast_transformer(parent, node, full_name, name, logs):
"""Transforms to_int and to_float to cast(..., dtype=...)."""
# Find out the dtype to cast to from the function name
dtype_str = name[3:]
# Special cases where the full dtype is not def cast_to_floatx(x):
"""Cast a Numpy array to the default Keras float type.
Args:
x: Numpy array or TensorFlow tensor.
Returns:
The same array (Numpy array if `x` was a Numpy array, or TensorFlow tensor
if `x` was a tensor Community Discussions
Trending Discussions on cast
QUESTION
I tried upgrading Android Gradle Plugin from 4.2.2 to 7.0.1 using the upgrade assistant which is available in Android Studio at Tools > AGP Upgrade Assistant. The only change it made was to my project-level build.gradle file:
...ANSWER
Answered 2021-Aug-24 at 16:35the Android Gradle Plugin documentation still says classpath 'com.android.tools.build:gradle:4.2.0' instead of 7.0.1.
You need to read further down the page, to this and this. That table is only relevant for pre-7.0.0 versions.
Is this a bug in Android Gradle Plugin 7.0.1?
Quite possibly. Or, perhaps beyond, as the Instantiatable Lint check has a history of problems.
If your scenario does not match one of those three August 2021 bugs, and you are in position to provide a reproducible test case, file a fresh issue! Beyond that, if a clean-and-rebuild is not clearing up your problem, you might need to simply disable the Instantiatable Lint check for the time being by adding the following to all of your build.gradle files at the application or library level (i.e. all except your project-level build.gradle):
QUESTION
In following program, struct C has two constructors : one from std::initializer_list and the other from std::initializer_list. Then an object of the struct is created with C{{1}}:
ANSWER
Answered 2022-Feb-12 at 23:30The wording could be clearer (which is unsurprising), but GCC and MSVC are correct here: the relevant rule ([over.ics.list]/7) checks only that
overload resolution […] chooses a single best constructor […] to perform the initialization of an object of type
Xfrom the argument initializer list
so the fact that the initialization of B from {1} would be ill-formed is irrelevant.
There are several such places where implicit conversion sequences are more liberal than actual initialization, causing certain cases to be ambiguous even though some of the possibilities wouldn’t actually work. If the programmer was confused and thought one of those near misses was actually a better match, it’s a feature that the ambiguity is reported.
QUESTION
Consider this code:
...ANSWER
Answered 2022-Feb-08 at 16:00- the class within which the member is declared is the class that a member function pointer will bind to.
->*on aDeriveddoesn't work with aBase::member function pointer unless theprivate BaseinDerivedis accessible to you (e.g. within a member function ofDerivedor in a function declared as friend ofDerived).- c-style casts allow you to convert
Derived*toBase*as well as member function pointers of those types, even thoughBaseis not accessible (this would be illegal for any c++-style cast), e.g.:
QUESTION
Given the following code, it seems that I cannot iterate over a Buf if it had been assigned to a variable, unless I cast it to a list, even though it's not a lazy sequence. What gives?
...ANSWER
Answered 2021-Dec-23 at 22:40The reason it fails, is that:
QUESTION
Let's say I have two data frames I want to bind:
...ANSWER
Answered 2021-Oct-25 at 20:17dplyr developers recommend rbindlist() for this apparently: https://github.com/tidyverse/dplyr/issues/1162
QUESTION
I am aware of how ODR, linkage, static, and extern "C" work with functions. But I am not sure about visibility of types since they cannot be declared static and there are no anonymous namespaces in C.
In particular, I would like to know the validity of the following code if compiled as C and C++
...ANSWER
Answered 2021-Oct-20 at 09:43For C. The program is valid. The only requirement that applies here is "strict aliasing rule" saying that the object can be accessed only via a l-value of a compatible type (+ a few exception described in 6.5p7).
The compatibility of structures/unions defined in separate translation units is defined in 6.2.7p1.
... two structure, union, or enumerated types declared in separate translation units are compatible if their tags and members satisfy the following requirements: If one is declared with a tag, the other shall be declared with the same tag. If both are completed anywhere within their respective translation units, then the following additional requirements apply: there shall be a one-to-one correspondence between their members such that each pair of corresponding members are declared with compatible types; if one member of the pair is declared with an alignment specifier, the other is declared with an equivalent alignment specifier; and if one member of the pair is declared with a name, the other is declared with the same name. For two structures, corresponding members shall be declared in the same order. For two structures or unions, corresponding bit-fields shall have the same widths. For two enumerations, corresponding members shall have the same values.
Therefore the structures are not compatible in the example.
However, it is not an issue because the f object is created and accessed via locally defined type. UB would be invoked if the object was created with Foo type defined in one translation unit and accessed via other Foo type in the other translation unit:
QUESTION
I'm studying functional composition and have an example:
...ANSWER
Answered 2021-Oct-14 at 12:23Because of its definition. The method Function#compose is defined as this:
QUESTION
It is well known that ordinary functions that differ only in their return type cannot be overloaded in C++.
But this limitation does not hold for overloaded function templates, for example:
...ANSWER
Answered 2021-Sep-30 at 08:42Why does the language make such exception for the templates?
You mean this?
signature [defns.signature.templ]
⟨function template⟩ name, parameter-type-list, enclosing namespace (if any), return type, template-head, and trailing requires-clause (if any)
Yes, the return type is there. It's what always made possible things like
QUESTION
I'm looking for a way to store a small multidimensional set of data which is known at compile time and never changes. The purpose of this structure is to act as a global constant that is stored within a single namespace, but otherwise globally accessible without instantiating an object.
If we only need one level of data, there's a bunch of ways to do this. You could use an enum or a class or struct with static/constant variables:
ANSWER
Answered 2021-Sep-06 at 09:45How about something like:
QUESTION
It seems to me that Pandas ExtensionArrays would be one of the cases where a simple example to get one started would really help. However, I have not found a simple enough example anywhere.
ExtensionArray
To create an ExtensionArray, you need to
- Create an
ExtensionDtypeand register it - Create an
ExtensionArrayby implementing the required methods.
There is also a section in the Pandas documentation with a brief overview.
Example implementationsThere are many examples of implementations:
- Pandas' own internal extension arrays
- Geopandas'
GeometryArray - Pandas documentation has a list of projects with extension data types
- e.g. CyberPandas'
IPArray
- e.g. CyberPandas'
- Many others around the web, for example Fletcher's
StringSupportingExtensionArray
Despite having studied all of the above, I still find extension arrays difficult to understand. All of the examples have a lot of specifics and custom functionality that makes it difficult to work out what is actually necessary. I suspect many have faced a similar problem.
I am thus asking for a simple and minimal example of a working ExtensionArray. The class should pass all the tests Pandas have provided to check that the ExtensionArray behaves as expected. I've provided an example implementation of the tests below.
To have a concrete example, let's say I want to extend ExtensionArray to obtain an integer array that is able to hold NA values. That is essentially IntegerArray, but stripped of any actual functionality beyond the basics of ExtensionArray.
I have used the following fixtures & tests to test the validity of the solution. These are based on the directions in the Pandas documentation
...ANSWER
Answered 2021-Sep-20 at 00:21There were too many issues trying to get NullableIntArray to pass the test suite, so I've created a new example (AngleDtype + AngleArray) that currently passes 398 tests (fails 2).
(pandas 1.3.2, numpy 1.20.2, python 3.9.2)
AngleArray stores either radians or degrees depending on its unit (represented by AngleDtype):
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