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1. Top results related to what is theano in python?

   • What is In[] in python

     Top Answer

     Answered Feb 03, 2020 · 2 votes

     They identifies cells in an iPython/Jupyter notebook. Cells enclosing input prompts use In[x], where x is just a serial number you can use to refer to previous inputs. Out[x] is the cell containing the output of the corresponding In cell.

     Your example shows an input of 3 + 2, following by its value. print(3+2) is likewise an input, but the 5 is simply text written to standard output. As the input expression had the value None (the return value of the print function), no output cell was created.

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     1/5

   • What is the purpose of creating symbolic variables in Theano?

     Top Answer

     Answered Jun 04, 2015 · 5 votes

     The Theano web site opens with

     Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently.

     which seems like quite a good summary of what it does but perhaps not why it does it.

     One of the main features of Theano is its symbolic differentiation feature. That is, given a symbolic mathematical expression, Theano can automatically differentiate the expression with respect to some variable within the expression, i.e. it can automatically determine the gradient of the expression along some dimension(s) of interest.

     For example, if y=x**2 (where ** is the power operator) then the gradient of y with respect to x is dy/dx = 2*x. Theano can do this automatically:

     import theanoimport theano.tensorx = theano.tensor.scalar('x')y = x ** 2theano.printing.pp(y)dy_dx = theano.grad(y, x)theano.printing.pp(dy_dx)-

     If you run this code you'll see the output

     (x ** TensorConstant{2})((fill((x ** TensorConstant{2}), TensorConstant{1.0}) * TensorConstant{2}) * (x ** (TensorConstant{2} - TensorConstant{1})))-

     The fill operation just creates a tensor of the correct shape (a scalar in this case) filled with ones and TensorConstant{a} is just the number a so this can be simplified to

     (x ** 2) == x ** 2((1 * 2) * (x ** (2 - 1))) == (2 * (x ** 1)) == 2 * x-

     As expected.

     Clearly this is not particularly helpful for such a simple mathematical expression, but now imagine you're constructing an arbitrarily large and complex mathematical expression for which the gradient is not so immediately obvious, as is often the case in neural network research.

     But there's more. Theano can do the above for expressions that involve operations over not just scalars but also vectors, matrices, or any other tensor.

     Besides symbolic differentiation, Theano's symbolic approach offers other significant benefits:

     • Theano can compile symbolic mathematical expressions into executable code. It uses various techniques that can yield executable code that can run faster than plain Python code.
     • Theano programs can often be switched between running on CPU and GPU with no code changes whatsoever.
     • When running on CPU, Theano makes full use of numpy BLAS and OpenMP facilities, when available, to parallelize the execution over multiple CPU cores.
     • When running on GPU, Theano makes full use of of the many cores on modern GPUs to parallelize the most costly operations (most notably matrix multiplication).
     • Theano's compiler is an optimizing compiler in that it can change the expression (also known as the computation graph) using various transforms that maintain the semantics of the expression (it still computes the same results given the same inputs) but achieving various performance and, crucially, numerical stability gains.

     Plain Python does not offer any of the above and using numpy alone only offers some of the parallelization features (via BLAS and OpenMP).

     More on this topic in the Theano documentation.

     P.S. this is an expansion of @eickenberg brief comment to the question.

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     2/5

   • What is """ in python?

     Top Answer

     Answered Jun 28, 2014 · 6 votes

     """ is a string delimiter.

     From PEP 257

     A docstring is a string literal that occurs as the first statement in a module, function, class, or method definition. Such a docstring becomes the __doc__ special attribute of that object.

     Thus your string just after the method is a comment and can be used by other tools to document your code. If you use an unassigned string literal elsewhere it is just a comment to help those reading the code (except in a couple of cases mentioned in the previous link)

     From the python reference

     In triple-quoted strings, unescaped newlines and quotes are allowed (and are retained), except that three unescaped quotes in a row terminate the string. (A “quote” is the character used to open the string, i.e. either ' or ".)

     Thus includes the carriage returns/line feeds.

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     3/5

   • What is `\*` in Python function definition?

     Top Answer

     Answered Jan 31, 2024 · 2 votes

     A typo, up to 3.11 it's not there warnings.warn(message, category=None, stacklevel=1, source=None):

     warnings.warn(message, category=None, stacklevel=1, source=None)- Issue a warning, or maybe ignore it or raise an exception. The category argument, if given, must be a warning category class; it defaults to UserWarning. Alternatively, message can be a Warning instance, in which case category will be ignored and message.__class__ will be used. In this case, the message text will be str(message). This function raises an exception if the particular warning issued is changed into an error by the warnings filter. The stacklevel argument can be used by wrapper functions written in Python, like this:- def deprecation(message): warnings.warn(message, DeprecationWarning, stacklevel=2) This makes the warning refer to deprecation()’s caller, rather than to the source of deprecation() itself (since the latter would defeat the purpose of the warning message). source, if supplied, is the destroyed object which emitted a ResourceWarning. Changed in version 3.6: Added source parameter.

     Try it:

     def func(\*):- pass-

     Result:

     ERROR!File "<string>", line 1 def func(\*): ^SyntaxError: unexpected character after line continuation character

     and :

     def func(po = 4):- print('po = ' , po) passa = func( 3)a = func(po = 3)def func(*, po = 4): print('po = ' , po) passa = func(po = 3)a = func(3)

     output :

     ERROR!po = 3po = 3po = 3Traceback (most recent call last): File "<string>", line 18, in <module>TypeError: func() takes 0 positional arguments but 1 was given>

     See What does a bare asterisk do in a parameter list? What are "keyword-only" parameters? for explanation :

     Bare * is used to force the caller to use named arguments

     and PEP 570 :

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     4/5

   • What is dag in python? How is it used?

     Top Answer

     Answered Jun 04, 2018 · 0 votes

     @ denotes a decorator function. What this means is that before your XYZ function gets called, it will first call the dag.cellfn function with 2 arguments, a reference to XYZ and dag.CanSet. The decorated function (dag.cellfn) will do whatever it was written to do and eventually call the reference function (XYZ).

     Decorators are often used to minimize code repetition, say you want to wrap every one of your functions with a try/catch. The decorator will let you write the try/catch once and then execute any function inside it.

     You should read the python documentation for decorators.

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     5/5

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2. www.geeksforgeeks.org › theano-in-pythonTheano in Python - GeeksforGeeks

   www.geeksforgeeks.org › theano-in-python

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   Dec 27, 2023 · Theano is a Python library that allows us to evaluate mathematical operations including multi-dimensional arrays efficiently. It is mostly used in building Deep Learning Projects . Theano works way faster on the Graphics Processing Unit (GPU) rather than on the CPU.

3. machinelearningmastery.com › introduction-pythonIntroduction to the Python Deep Learning Library Theano

   machinelearningmastery.com › introduction-python

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   Aug 19, 2019 · Theano is a Python library for fast numerical computation that can be run on the CPU or GPU. It is a key foundational library for Deep Learning in Python that you can use directly to create Deep Learning models or wrapper libraries that greatly simplify the process.

4. People also ask

   What is Theano Python?

   • Theano is a Python library for fast numerical computation that can be run on the CPU or GPU. It is a key foundational library for Deep Learning in Python that you can use directly to create Deep Learning models or wrapper libraries that greatly simplify the process. In this post you will discover the Theano Python library.

   Introduction to the Python Deep Learning Library Theano

   machinelearningmastery.com/introduction-python-deep-learning-library-theano/

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   How does Theano work?

   • Symbolic Differentiation: Theano is smart enough to automatically create symbolic graphs for computing gradients. Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Some Theano implementations are as follows.

   Theano in Python - GeeksforGeeks

   www.geeksforgeeks.org/theano-in-python/

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   What makes Theano different from NumPy?

   • Theano features: tight integration with NumPy: a similar interface to NumPy’s. numpy.ndarrays are also used internally in Theano-compiled functions. transparent use of a GPU: perform data-intensive computations up to 140x faster than on a CPU (support for float32 only).

   Theano · PyPI

   pypi.org/project/Theano/

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   How to install Theano Python library?

   • To install Theano, You need to run this command in your terminal. Several symbols we will need to use are in the tensor subpackage of Theano. We often import such packages with a handy name, let’s say, T. Why Theano Python Library ? Theano is a sort of hybrid between numpy and sympy, an attempt is made to combine the two into one powerful library.

   Theano in Python - GeeksforGeeks

   www.geeksforgeeks.org/theano-in-python/

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5. theano.readthedocs.ioWelcome — Theano 0.8.2 documentation

   theano.readthedocs.io

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   Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Theano features: tight integration with NumPy – Use numpy.ndarray in Theano-compiled functions.

6. pypi.org › project › TheanoTheano · PyPI

   pypi.org › project › Theano

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   Nov 23, 2010 · Theano is a Python library that allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is built on top of NumPy. Theano features: tight integration with NumPy: a similar interface to NumPy’s. numpy.ndarrays are also used internally in Theano-compiled functions.

7. www.devopsschool.com › blog › what-is-theano-and-howWhat is Theano and How it works? An Overview and Its Use ...

   www.devopsschool.com › blog › what-is-theano-and-how

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   Mar 28, 2022 · Theano is a Python library that allows us to evaluate mathematical operations including multi-dimensional arrays so efficiently. It is mostly used in building Deep Learning Projects. It works a way more faster on Graphics Processing Unit (GPU) rather than on CPU.

8. en.wikipedia.org › wiki › Theano_(software)Theano (software) - Wikipedia

   en.wikipedia.org › wiki › Theano_(software)

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   Theano is a Python library and optimizing compiler for manipulating and evaluating mathematical expressions, especially matrix-valued ones. In Theano, computations are expressed using a NumPy -esque syntax and compiled to run efficiently on either CPU or GPU architectures.

9. flexiple.com › python › theano-beginner-guideTheano Python Tutorial for Beginners - Flexiple

   flexiple.com › python › theano-beginner-guide

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   Dec 19, 2023 · What is Theano? Theano is an open-source Python library designed for efficient numerical computations. Theano translates Python code into optimized machine code, leveraging powerful libraries like NumPy and exploiting the capabilities of modern CPUs and GPUs.