tensor | A fast tensor library for c | Machine Learning library

 by   robclu C++ Version: Current License: GPL-2.0

kandi X-RAY | tensor Summary

kandi X-RAY | tensor Summary

tensor is a C++ library typically used in Artificial Intelligence, Machine Learning, Pytorch applications. tensor has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

Tensor is a c++ tensor expression library. It is designed with both speed and clarity of expression in mind. It it thus intended to provide high levels of performance but allow operations on tensors in the code to appear exactly as they do mathematically. Template metaprogramming is used to 'offload' any work which can be computed at compile time, to the compiler and expression templates are used to achieve the translation of the mathematically expressed code to high performance code. Tests have been written using the Boost Test library to verify the 'correctness' of all the implemented components. The tests also help to illustrate the usage of the various components of the library. The long term goal is to develop something along the lines of the tensor library in the python theano libray, but with support for any rank tensors with both CPU and GPU functionality.
Support
    Quality
      Security
        License
          Reuse

            kandi-support Support

              tensor has a low active ecosystem.
              It has 6 star(s) with 2 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              tensor has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of tensor is current.

            kandi-Quality Quality

              tensor has no bugs reported.

            kandi-Security Security

              tensor has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              tensor is licensed under the GPL-2.0 License. This license is Strong Copyleft.
              Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

            kandi-Reuse Reuse

              tensor releases are not available. You will need to build from source code and install.
              Installation instructions are not available. Examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
            Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of tensor
            Get all kandi verified functions for this library.

            tensor Key Features

            No Key Features are available at this moment for tensor.

            tensor Examples and Code Snippets

            Locate the tensor element of the given indices .
            pythondot img1Lines of Code : 122dot img1License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def locate_tensor_element(formatted, indices):
              """Locate a tensor element in formatted text lines, given element indices.
            
              Given a RichTextLines object representing a tensor and indices of the sought
              element, return the row number at which the   
            r Solve tensor product .
            pythondot img2Lines of Code : 94dot img2License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def lu_solve(lower_upper, perm, rhs, validate_args=False, name=None):
              """Solves systems of linear eqns `A X = RHS`, given LU factorizations.
            
              Note: this function does not verify the implied matrix is actually invertible
              nor is this condition ch  
            Wrap input tensor into a function .
            pythondot img3Lines of Code : 84dot img3License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def _wrap_2d_function(inputs, compute_op, dim=-1, name=None):
              """Helper function for ops that accept and return 2d inputs of same shape.
            
              It reshapes and transposes the inputs into a 2-D Tensor and then invokes
              the given function. The output wo  

            Community Discussions

            QUESTION

            attribute error and key error in the join operation of string
            Asked 2021-Jun-15 at 21:50

            There is a function given as follows

            ...

            ANSWER

            Answered 2021-Jun-15 at 21:34

            Your code doesn’t attempt to not fail if w isn’t a key in id2word, so it shouldn’t be too much of a surprise when it does fail. You could try changing

            Source https://stackoverflow.com/questions/67993679

            QUESTION

            I'm using bert pre-trained model for question and answering. It's returning correct result but with lot of spaces between the text
            Asked 2021-Jun-15 at 17:14

            I'm using bert pre-trained model for question and answering. It's returning correct result but with lot of spaces between the text

            The code is below :

            ...

            ANSWER

            Answered 2021-Jun-15 at 17:14

            You can just use the tokenizer decode function:

            Source https://stackoverflow.com/questions/67990545

            QUESTION

            Problem with FULLY_CONNECTED op in TF Lite
            Asked 2021-Jun-15 at 13:22

            I'd like to run a simple neural network model which uses Keras on a Rasperry microcontroller. I get a problem when I use a layer. The code is defined like this:

            ...

            ANSWER

            Answered 2021-May-25 at 01:08

            I had the same problem, man. I want to transplant tflite to the development board of CEVA. There is no problem in compiling. In the process of running, there is also an error in AddBuiltin(full_connect). At present, the only possible situation I guess is that some devices can not support tflite.

            Source https://stackoverflow.com/questions/67677228

            QUESTION

            SHAP DeepExplainer with TensorFlow 2.4+ error
            Asked 2021-Jun-14 at 14:52

            I'm trying to compute shap values using DeepExplainer, but I get the following error:

            keras is no longer supported, please use tf.keras instead

            Even though i'm using tf.keras?

            ...

            ANSWER

            Answered 2021-Jun-14 at 14:52

            TL;DR

            • Add tf.compat.v1.disable_v2_behavior() at the top for TF 2.4+
            • calculate shap values on numpy array, not on df

            Full reproducible example:

            Source https://stackoverflow.com/questions/66814523

            QUESTION

            What does Tensorflow LSTM return?
            Asked 2021-Jun-14 at 14:38

            I'm writing a German->English translator using an encoder/decoder pattern, where the encoder connects to the decoder by passing the state output of its last LSTM layer as the input state of the decoder's LSTM.

            I'm stuck, though, because I don't know how to interpret the output of the encoder's LSTM. A small example:

            ...

            ANSWER

            Answered 2021-Jun-14 at 14:38

            An LSTM cell in Keras gives you three outputs:

            • an output state o_t (1st output)
            • a hidden state h_t (2nd output)
            • a cell state c_t (3rd output)

            and you can see an LSTM cell here:

            The output state is generally passed to any upper layers, but not to any layers to the right. You would use this state when predicting your final output.

            The cell state is information that is transported from previous LSTM cells to the current LSTM cell. When it arrives in the LSTM cell, the cell decides whether information from the cell state should be deleted, i.e. we will "forget" some states. This is done by a forget gate: This gate takes the current features x_t as an input and the hidden state from the previous cell h_{t-1}. It outputs a vector of probabilities that we multiply with the last cell state c_{t-1}. After determining what information we want to forget, we update the cell state with the input gate. This gate takes the current features x_t as an input and the hidden state from the previous cell h_{t-1} and produces an input which is added to the last cell state (from which we have already forgotten information). This sum is the new cell state c_t. To get the new hidden state, we combine the cell state with a hidden state vector, which is again a vector of probabilities that determines which information from the cell state should be kept and which should be discarded.

            As you have correctly interpreted, the first tensor is the output of all hidden states.

            The second tensor is the hidden output, i.e. $h_t$, which acts as the short-term memory of the neural network The third tensor is the cell output, i.e. $c_t$, which acts as the long-term memory of the neural network

            In the keras-documentation it is written that

            Source https://stackoverflow.com/questions/67970519

            QUESTION

            Error failed to convert a NumPy array to a Tensor
            Asked 2021-Jun-14 at 02:18

            I have the data in the following format. I am using a neural network to predict three parameters downtime, latency and accuracy using neural network regression.

            ...

            ANSWER

            Answered 2021-Jun-14 at 00:47

            I can't run your code so I created something similar and I get this error when pre_norms has values NaN.

            I get pre_norms with NaN because predictors has columns No_Model,Technique which have strings and predictors-predictors.mean()/predictors.std()) convert them to NaN

            Solution could be removing columns No_Model,Technique but this create empty data - so it is useless.

            I don't know you full code but you should check what you have in variables and if you have NaN then you have wrong calculations.

            Source https://stackoverflow.com/questions/67962668

            QUESTION

            AttributeError: 'numpy.ndarray' object has no attribute 'op'
            Asked 2021-Jun-13 at 18:26

            I am have a time series data and I am trying to build and train an LSTM model over it. I have 1 input and 1 Output corresponding to my model. I am trying to build a Many to Many model where Input length is exactly equal to output length.

            The shape of my inputs are X --> (1700,70,401) (examples, Timestep, Features)

            Shape of my output is Y_1-->(1700,70,3) (examples, Timestep, Features)

            Now When I am trying to approach this problem via sequential API everything is running fine.

            ...

            ANSWER

            Answered 2021-Jun-13 at 18:26

            I made a mistake in the code itself while executing the Model part of in the functional API version.

            Source https://stackoverflow.com/questions/67880921

            QUESTION

            Force BERT transformer to use CUDA
            Asked 2021-Jun-13 at 09:57

            I want to force the Huggingface transformer (BERT) to make use of CUDA. nvidia-smi showed that all my CPU cores were maxed out during the code execution, but my GPU was at 0% utilization. Unfortunately, I'm new to the Hugginface library as well as PyTorch and don't know where to place the CUDA attributes device = cuda:0 or .to(cuda:0).

            The code below is basically a customized part from german sentiment BERT working example

            ...

            ANSWER

            Answered 2021-Jun-12 at 16:19

            You can make the entire class inherit torch.nn.Module like so:

            Source https://stackoverflow.com/questions/67948945

            QUESTION

            UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach()
            Asked 2021-Jun-12 at 23:00

            I'm new on PyTorch and I'm trying to code with it so I have a function called OH which tack a number and return a vector like this

            ...

            ANSWER

            Answered 2021-Apr-30 at 23:19

            the problem is that you are receiving a tensor on the act function on the Network and then save it as a tensor just remove the tensor in the action like this

            Source https://stackoverflow.com/questions/67341208

            QUESTION

            Selecting values from tensor based on an index tensor
            Asked 2021-Jun-12 at 15:56

            I have two matrices. Matrix A is contains some values and matrix B contains indices. The shape of matrix A and B is (batch, values) and (batch, indices), respectively.

            My goal is to select values from matrix A based on indices of matrix B along the batch dimension.

            For example:

            ...

            ANSWER

            Answered 2021-Jun-12 at 15:56

            You can achieve this with the tf.gather function.

            Source https://stackoverflow.com/questions/67950502

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install tensor

            You can download it from GitHub.

            Support

            Please see Tensor Documentation for documentation and usage examples.
            Find more information at:

            Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items

            Find more libraries
            CLONE
          • HTTPS

            https://github.com/robclu/tensor.git

          • CLI

            gh repo clone robclu/tensor

          • sshUrl

            git@github.com:robclu/tensor.git

          • Stay Updated

            Subscribe to our newsletter for trending solutions and developer bootcamps

            Agree to Sign up and Terms & Conditions

            Share this Page

            share link