Write frontend function to fire when the user selects to sort a particular column to send the necessary information to the backend. Write endpoint in backend to receive request and sort the particular column in dataset saved in backend using Pandas.

The workflow should be base on 'Projects'.
e.g - Firebase workflow

• Implement the project interface
• Change the current workflow

Upon trying to upload a CSV file under 50 lines and viewing it using visualizedata, I encounter the following error involving a duplicate primary key entry in the template_copies table.

This was reproduced by following the directions on the README file and restoring the database dump.

Traceback

MySQLdb._exceptions.IntegrityError: (1062, "Duplicate entry '1' for key 'PRIMARY'")

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\josep\Anaconda3\lib\site-packages\flask\app.py", line 2295, in wsgi_app
    response = self.handle_exception(e)
  File "C:\Users\josep\Anaconda3\lib\site-packages\flask_cors\extension.py", line 161, in wrapped_function
    return cors_after_request(app.make_response(f(*args, **kwargs)))
  File "C:\Users\josep\Anaconda3\lib\site-packages\flask_cors\extension.py", line 161, in wrapped_function
    return cors_after_request(app.make_response(f(*args, **kwargs)))
  File "C:\Users\josep\Anaconda3\lib\site-packages\flask\app.py", line 1741, in handle_exception
    reraise(exc_type, exc_value, tb)
  File "C:\Users\josep\Anaconda3\lib\site-packages\flask\_compat.py", line 35, in reraise
    raise value
  File "C:\Users\josep\Anaconda3\lib\site-packages\flask\app.py", line 2292, in wsgi_app
    response = self.full_dispatch_request()
  File "C:\Users\josep\Anaconda3\lib\site-packages\flask\app.py", line 1815, in full_dispatch_request
    rv = self.handle_user_exception(e)
  File "C:\Users\josep\Anaconda3\lib\site-packages\flask_cors\extension.py", line 161, in wrapped_function
    return cors_after_request(app.make_response(f(*args, **kwargs)))
  File "C:\Users\josep\Anaconda3\lib\site-packages\flask_cors\extension.py", line 161, in wrapped_function
    return cors_after_request(app.make_response(f(*args, **kwargs)))
  File "C:\Users\josep\Anaconda3\lib\site-packages\flask\app.py", line 1718, in handle_user_exception
    reraise(exc_type, exc_value, tb)
  File "C:\Users\josep\Anaconda3\lib\site-packages\flask\_compat.py", line 35, in reraise
    raise value
  File "C:\Users\josep\Anaconda3\lib\site-packages\flask\app.py", line 1813, in full_dispatch_request
    rv = self.dispatch_request()
  File "C:\Users\josep\Anaconda3\lib\site-packages\flask\app.py", line 1799, in dispatch_request
    return self.view_functions[rule.endpoint](**req.view_args)
  File "C:\Users\josep\Documents\GitHub\TensorMap\tensormap-server\app\resources\template_manipulation.py", line 358, in createExperiment
    db.session.commit()
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\orm\scoping.py", line 162, in do
    return getattr(self.registry(), name)(*args, **kwargs)
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\orm\session.py", line 1027, in commit
    self.transaction.commit()
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\orm\session.py", line 494, in commit
    self._prepare_impl()
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\orm\session.py", line 473, in _prepare_impl
    self.session.flush()
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\orm\session.py", line 2470, in flush
    self._flush(objects)
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\orm\session.py", line 2608, in _flush
    transaction.rollback(_capture_exception=True)
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\util\langhelpers.py", line 68, in __exit__
    compat.reraise(exc_type, exc_value, exc_tb)
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\util\compat.py", line 153, in reraise
    raise value
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\orm\session.py", line 2568, in _flush
    flush_context.execute()
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\orm\unitofwork.py", line 422, in execute
    rec.execute(self)
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\orm\unitofwork.py", line 589, in execute
    uow,
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\orm\persistence.py", line 245, in save_obj
    insert,
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\orm\persistence.py", line 1084, in _emit_insert_statements
    c = cached_connections[connection].execute(statement, multiparams)
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\engine\base.py", line 988, in execute
    return meth(self, multiparams, params)
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\sql\elements.py", line 287, in _execute_on_connection
    return connection._execute_clauseelement(self, multiparams, params)
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\engine\base.py", line 1107, in _execute_clauseelement
    distilled_params,
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\engine\base.py", line 1253, in _execute_context
    e, statement, parameters, cursor, context
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\engine\base.py", line 1473, in _handle_dbapi_exception
    util.raise_from_cause(sqlalchemy_exception, exc_info)
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\util\compat.py", line 398, in raise_from_cause
    reraise(type(exception), exception, tb=exc_tb, cause=cause)
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\util\compat.py", line 152, in reraise
    raise value.with_traceback(tb)
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\engine\base.py", line 1249, in _execute_context
    cursor, statement, parameters, context
  File "C:\Users\josep\Anaconda3\lib\site-packages\sqlalchemy\engine\default.py", line 580, in do_execute
    cursor.execute(statement, parameters)
  File "C:\Users\josep\Anaconda3\lib\site-packages\MySQLdb\cursors.py", line 209, in execute
    res = self._query(query)
  File "C:\Users\josep\Anaconda3\lib\site-packages\MySQLdb\cursors.py", line 315, in _query
    db.query(q)
  File "C:\Users\josep\Anaconda3\lib\site-packages\MySQLdb\connections.py", line 239, in query
    _mysql.connection.query(self, query)
sqlalchemy.exc.IntegrityError: (MySQLdb._exceptions.IntegrityError) (1062, "Duplicate entry '1' for key 'PRIMARY'")
[SQL: INSERT INTO template_copies (id, `fileName`, data) VALUES (%s, %s, %s)]
[parameters: ('1', 'user_keras_temp.py', b'import tensorflow as tf\r\nfrom tensorflow import keras\r\nfrom tensorflow.keras import layers\r\nimport numpy as np\r\nfrom sklearn.metrics import  ... (837 characters truncated) ... nt("MAE: ",mae)\r\n\r\nwith open("results.csv", "w") as f:\r\n    writer = csv.writer(f)\r\n    writer.writerows(zip(y_test,predictions))\r\n\r\n\r\n')]
(Background on this error at: http://sqlalche.me/e/gkpj)```

While making a neural network architecture, It should give an error when one tries to make two output node.

Right now it does not give any error.

@orionpax00 Need your update on this one also :)

• Implement the top NavBar
  • Add user profile and sign out

Sketch should be forward engineered to an implementation code in,

• Python

There is a small delay when loading ‘visualizedata’ page with all the rows of the uploaded data set. Create a loader to indicate the user that the dataset is being loaded into the page.

Currently when the react server runs on the browser, it throws warnings on the console, occuring due to inconsistent code use.

Screenshots:

Todos:

• Fix these warnings

Remarks: I am working on this issue

Develop various charts to display results generated during training like line plot to display loss and accuracy, Heatmaps to display correlation, etc.

Write unit tests for endpoints related to pre-processing using the unittest framework.

Current Behaviour: Currently when we upload a dataset, it's name is not showing up on the uploaded dataset panel.

Expected Behaviour: The uploaded dataset should appear with its name

Screenshots:

Remarks: I am working on it.

Make activation as function like sigmoid,tanh,linear etc.
It is coded in backend as function.

It is will be dropdown of all the function like this :

I need the confirmation @orionpax00 @ivantha @suleka96 @sumedhe

In the project readme, under the setting up frontend section, the instructions should be

cd TensorMap/tensormap-client 

instead of

cd TensorMap

since 'yarn install' and 'npm start' do not make sense in the main directory and would return an error.

Modify existing “viewdata” UI to show information of all uploaded datasets using MaterialTable. Write code to get information from “viewData” backend route and populate the table.

While making the neural network architecture,
It should give an error when one tries to make two input node.
Right now it does not give any error.

@orionpax00 Need your input regarding this :)

The steps in the readme.md are wrong. It says to yarn install and npm start but npm start won't be possible until package.json is not available in tensor map main directory.

• Upload data in .csv format
• Visualize a sample of uploaded data in tabular format i.e. head
• Row operations
  • TBD
• Column operations
  • TBD
• Clean operations
  • Drop / alter rows matching x criteria

• Privilege levels i.e Admin, User
• Add, Remove, Manage users
• Approve signed-up users
• Future :
  • Restrict resource usage for users
  • User resource usage summaries

Fork and clone the TensorMap GitHub repository. Follow the instructions in the README.md and set up both frontend and backend. Take screenshots of the running server console and the web browser with TensorMap homepage.

Setup the project and test all template manipulation related endpoints in the backend using Postman and sample JSON structures documented in this link.

The Popover that comes on double clicking any node on the Neural Network Diagrams should come immediately on Drop event. Moreover, it must be customised according to the layer the user has dragged. For E.g.- For Input Layer, it should ask for Input shape along with output activation and shape.

Thanks.

I refactored the Upload Data Construct with few validations (Not rendering error messages as of now). Instead of using hard-coded options on select menu, we can use the following
this.acceptedDatasetFormats = [ { type: "Select File Type", value: "null", }, { type: "Comma Seprated Values (CSV)", value: "csv", }, ];
This array can be fetched from server later on.
Hope I can submit a PR for the above after the appropriate review and contribute more significantly to the project in future.

Thanks a lot.

Currently, the component that represents node is implemented using default factory of Storm React Diagrams, for this task you have to create a custom component by extending default component with Material UI Styling

Current Behaviour: Currently, in the project, there are multiple ways being followed to perform ajax request to the server. For eg., Dashboard.jsx uses fetch, ViewData.jsx uses vanilla JS' XMLHttpRequest().

Expected: One format should be followed throughout the project.

Remarks: I am working on it.

Current Behaviour: Currently, the code is written to redirect to visualize the data after successful upload, but redirection is not working, instead throwing error on console.

Expected Behaviour: It should redirect to corresponding page.

Code Screenshot:

Error Screenshot:

Remarks: I am working on this issue

Current Behaviour: Currently, /visualize route is not working properly, giving undefined in params, and is throwing errors

Expected: The uploaded csv should be available to visualize

Screenshots:

Remarks: I am working on it

Create a professional logo for the TensorMap project

@charithccmc As scorelab's TensorMap is a machine learning and deep learning related application so it is good to develop backend in Django rather than nodejs (as written on idea page of gsoc'19)

When I run the command npm start it gives this error.
My system environment -
nodejs - 8.10.0
Elementary OS 05.1
Chromium browser - 79.0.3945.79

I followed the readme.md completely and after I ran npm start it opens the localhost:3000 and gives the above output.

Hello Everyone,

According to the Official GSOC-2019 list of project ideas of Score Lab, there is one Idea which is on Implement the TensorMap Web Application. I want to work on this Idea and want to take part in GSoC-2019. I have already introduced myself on Gitter.

I was setting up the project by following the methods mentioned and found that ,I had to follow one extra step to set up the project on my machine. It was probably due to some node version issue,but it will be really good if this thing was already present in readme.

Setup the project and test all data pre-processing related endpoints in the backend by performing data pre-processing related actions in the frontend. Identify which endpoints are performing what task and what kind of data is sent to the backend and what data is returned to the frontend.

Dependabot should be configured to receive new dependency updates and security patches.

[1]Colors in Dropdown section is not showing,

solved by #94

Issue: The code was recently upgraded to material-ui 4, but some part of code are still throwing errors, and require updation.

Screenshots:

Remarks: I am working on it.

Setup project then find an issue in the project and open an issue in the project’s GitHub page

ERROR 1273 (HY000) at line 60: Unknown collation: 'utf8mb4_0900_ai_ci' while restoring dump,

Works with following result when replaced 'utf8mb4_0900_ai_ci'` to 'utf8mb4_unicode_ci'

Is this an acceptable workaround?

Currently the request addresses are directly hardcoded to 'http://localhost:5000'. The hardcode should be changed to use the baseURL.

• Call the API with the JSON containing the architecture depicted by the sketch

Solved by #94

I chose the file type to be csv and then uploaded a csv file....After uploading when we again choose other file to upload it says that file type is not supported even though I added a csv type only.

• Update weights separately
• Update parameters of each node
• Define layers
• Display runtime data

This is my logo.

Encountered an import error while running the Backend server.

Error: no module named 'tensorflow.keras'

Solved this using tensorflow.python.keras instead of the above statement.

Setup project and add necessary layer information into the “code_layers” table.

• OAuth backend support with JWT Tokens
• SignIn
  • Forget password
• SignUp
  • Email