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Rohit Dwivedula rohitdwivedula Microsoft Research Bangalore, India

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Repository of problems and solutions of labsheets used for Data Structures and Algorithms (CS F211) in Semester 2, 2020-21 at BITS Pilani - Hyderabad Campus.

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Predict the enzyme class of a given FASTA sequence using deep learning methods including CNNs, LSTM, BiLSTM, GRU, and attention models along with a host of other ML methods.

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MERN CRUD app created as a teaching aid for the course Software Engineering (IS F341) at BITS Hyderabad.

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Multiclass and multilabel classification of ECG signals using various deep learning models.

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A bunch of MIPS (assembly) programming exercises and problems done in college as a part of the course Computer Architecture (CS F342).

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Implementations of multiple genetic algorithm based (NSGA-II, NSGA-III, C-TAEA) and fuzzy optimization algorithms for optimisation of Best Management Practices (BMPs) in the Greater Hyderabad Municipal Corporation Area.

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Minimal full stack version modelled around Google+ and Facebook. Built with the LAMP stack, for college credit.

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A Java (Swing) based project to build a hotel booking app. The app lets users create accounts, book hotel tooms in various cities across India and cancel/modify their bookings. Built using pure Java + a mySQL Database towards partial credit towards CS F213, the Object Oriented Programming Course.

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Playing with stats for messenger chats. Mainly jc/old.

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C++ implementation of the binary tree drawing algorithm described in Tidier Drawings of Trees (1981)

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issue commentanyoptimization/pymoo-doc

Potential math rendering errors in `pymoo.org`

Can you please check again? (do not forget to delete the cache)

Hi, the 404s and the subsequent errors don't seem to be appearing right now.

rohitdwivedula

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issue openedanyoptimization/pymoo-doc

Potential math rendering errors in `pymoo.org`

There appear to be some errors in the math rendering on pymoo.org:

image

As soon as the page loads, the math shows up fine - for around ~15-30 seconds. However, after 30 seconds or so, the math ends up as shown in the above picture: [Math Processing Error]. I usually would assume that this was something wrong with my browser, but this happened on three different browsers on two different devices (Firefox mobile, Firefox Desktop, and Edge Desktop), both in regular mode and incognito/private browsing - so that probably rules out something being wrong with my browser specifically.

On going through the Javascript console on the browser, it looks like there are some JS libraries missing:

GET https://pymoo.org/_static/fonts/HTML-CSS/TeX/woff/MathJax_Main-Regular.woff?V=2.7.3 net::ERR_ABORTED 404 (Not Found)
/_static/fonts/HTML-CSS/TeX/woff/MathJax_Math-Italic.woff?V=2.7.3:1 GET https://pymoo.org/_static/fonts/HTML-CSS/TeX/woff/MathJax_Math-Italic.woff?V=2.7.3 net::ERR_ABORTED 404 (Not Found)
/_static/fonts/HTML-CSS/TeX/woff/MathJax_Size1-Regular.woff?V=2.7.3:1 GET https://pymoo.org/_static/fonts/HTML-CSS/TeX/woff/MathJax_Size1-Regular.woff?V=2.7.3 net::ERR_ABORTED 404 (Not Found)
/_static/fonts/HTML-CSS/TeX/otf/MathJax_Main-Regular.otf?V=2.7.3:1 GET https://pymoo.org/_static/fonts/HTML-CSS/TeX/otf/MathJax_Main-Regular.otf?V=2.7.3 net::ERR_ABORTED 404 (Not Found)
/_static/fonts/HTML-CSS/TeX/otf/MathJax_Math-Italic.otf?V=2.7.3:1 GET https://pymoo.org/_static/fonts/HTML-CSS/TeX/otf/MathJax_Math-Italic.otf?V=2.7.3 net::ERR_ABORTED 404 (Not Found)
/_static/fonts/HTML-CSS/TeX/otf/MathJax_Size1-Regular.otf?V=2.7.3:1 GET https://pymoo.org/_static/fonts/HTML-CSS/TeX/otf/MathJax_Size1-Regular.otf?V=2.7.3 net::ERR_ABORTED 404 (Not Found)

followed by this error:

Uncaught TypeError: Cannot read properties of undefined (reading 'img')
    at GETWIDTHS (imageFonts.js?V=2.7.3:184)
    at Function.execute (MathJax.js?config=TeX-AMS-MML_HTMLorMML-full.js:243)
    at cb (MathJax.js?config=TeX-AMS-MML_HTMLorMML-full.js:225)
    at Object.Process (MathJax.js?config=TeX-AMS-MML_HTMLorMML-full.js:495)
    at Object.call (MathJax.js?config=TeX-AMS-MML_HTMLorMML-full.js:508)
    at Function.WAITEXECUTE (MathJax.js?config=TeX-AMS-MML_HTMLorMML-full.js:348)
    at cb (MathJax.js?config=TeX-AMS-MML_HTMLorMML-full.js:225)
    at Object.Execute (MathJax.js?config=TeX-AMS-MML_HTMLorMML-full.js:426)
    at Object.loadComplete (MathJax.js?config=TeX-AMS-MML_HTMLorMML-full.js:968)
    at Object.loadTimeout (MathJax.js?config=TeX-AMS-MML_HTMLorMML-full.js:979)

after which the math error shows up. Just thought I'd let you know - if this doesn't seem like a problem others are facing, please close this issue - thanks!

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adds: multiobjective code

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Update README.md

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update READMEs, cosmetic changes

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adds: sample data Sample .shp and other GIS files added. This data can be considered to be "mock data" to run the scripts. This is not the actual dataset used in the paper.

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commit sha 8f8fd79e3eea7a5c33502fbdcd14b6069d38c821

update fuzzy opt. code to support pymoo-0.5.0 Minor changes: - add command line argument to set deterministic seed - calculate ZL, ZU for all objectives directly from dataset

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adds: dependencies and installation instructions

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Rename `results` directory to `final_results` to make it clearer that the folder contains the results of the paper.

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Rename `results` directory to `final_results` to make it clearer that the folder contains the results of the paper.

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PR opened openai/triton

`tl.cdiv` and `triton.cdiv` both used
  • tl.cdiv is used in two places
  • triton.cdiv is used in two places
  • Should probably be triton.cdiv everywhere, since tl.cdiv throws an error.
  • Changed two occurrences of tl.cdiv -> triton.cdiv.
+2 -2

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commit sha 5343137f63936aaff6a13477793cbffdbdb2f050

`tl.cdiv` and `triton.cdiv` both used - `tl.cdiv` is used in two places - `triton.cdiv` is used in two places - Should probably be `triton.cdiv` everywhere, since `tl.cdiv` throws an error. - Changed two occurrences of `tl.cdiv` -> `triton.cdiv`.

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issue openedopenai/triton

Support for stacking decorators

Ideally, it would be nice if we could stack decorators @autotune and @heuristic. For example, in the softmax example, something like:

@triton.autotune(
    configs=[
        triton.Config({}, num_stages=3, num_warps=8),
        triton.Config({}, num_stages=4, num_warps=4),
        triton.Config({}, num_stages=5, num_warps=2),
    ],
    key=['n_cols'],
)
@triton.heuristics(
    values={
        'BLOCK_SIZE': lambda args: 2 ** int(math.ceil(math.log2(args[4])))
    }
)
@triton.jit
def softmax_kernel(
    output_ptr, input_ptr, output_row_stride, input_row_stride, n_cols, **meta
):

However, doing this results in an error:

TypeErrorTraceback (most recent call last)
<ipython-input-45-6bc6de21d479> in <module>
----> 1 softmax(x)

<ipython-input-43-0febc983c77f> in softmax(x)
     20         x.stride(0),
     21         y.stride(0),
---> 22         n_cols
     23     )
     24     return y

~/rohitd/venvs/t2-env/lib/python3.6/site-packages/triton/code_gen.py in __call__(self, *wargs, **kwargs)
    597 
    598     def __call__(self, *wargs, **kwargs):
--> 599         return self.kernel(*wargs, **kwargs, grid=self.grid)
    600 
    601 

~/rohitd/venvs/t2-env/lib/python3.6/site-packages/triton/code_gen.py in fun(*args, **meta)
    715                 for v, heur in values.items():
    716                     assert v not in meta
--> 717                     meta[v] = heur(*args, **meta)
    718                 return kernel(*args, **meta)
    719 

TypeError: <lambda>() got an unexpected keyword argument 'grid'

Reversing the order of the @autotune and @heuristic decorators like:

@triton.heuristics(
    values={
        'BLOCK_SIZE': lambda args: 2 ** int(math.ceil(math.log2(args[4])))
    }
)
@triton.autotune(
    configs=[
        triton.Config({}, num_stages=3, num_warps=8),
        triton.Config({}, num_stages=4, num_warps=4),
        triton.Config({}, num_stages=5, num_warps=2),
    ],
    key=['n_cols'],
)

leads to a different error:

TypeErrorTraceback (most recent call last)
<ipython-input-49-6bc6de21d479> in <module>
----> 1 softmax(x)

<ipython-input-47-0febc983c77f> in softmax(x)
     20         x.stride(0),
     21         y.stride(0),
---> 22         n_cols
     23     )
     24     return y

~/rohitd/venvs/t2-env/lib/python3.6/site-packages/triton/code_gen.py in __call__(self, *wargs, **kwargs)
    597 
    598     def __call__(self, *wargs, **kwargs):
--> 599         return self.kernel(*wargs, **kwargs, grid=self.grid)
    600 
    601 

~/rohitd/venvs/t2-env/lib/python3.6/site-packages/triton/code_gen.py in __call__(self, *args, **meta)
    629             if key not in self.cache:
    630                 timings = {config: self._bench(*args, config=config, **meta) \
--> 631                         for config in self.configs}
    632                 self.cache[key] = builtins.min(timings, key=timings.get)
    633             config = self.cache[key]

~/rohitd/venvs/t2-env/lib/python3.6/site-packages/triton/code_gen.py in <dictcomp>(.0)
    629             if key not in self.cache:
    630                 timings = {config: self._bench(*args, config=config, **meta) \
--> 631                         for config in self.configs}
    632                 self.cache[key] = builtins.min(timings, key=timings.get)
    633             config = self.cache[key]

~/rohitd/venvs/t2-env/lib/python3.6/site-packages/triton/code_gen.py in _bench(self, config, *args, **meta)
    622         current = dict(meta, **config.meta)
    623         kernel_call = lambda: self.kernel(*args, num_warps=config.num_warps, num_stages=config.num_stages, **current)
--> 624         return triton.testing.do_bench(kernel_call)
    625 
    626     def __call__(self, *args, **meta):

~/rohitd/venvs/t2-env/lib/python3.6/site-packages/triton/testing.py in do_bench(fn, warmup, rep, grad_to_none, percentiles)
    109 
    110     # Estimate the runtime of the function
--> 111     fn()
    112     torch.cuda.synchronize()
    113     start_event = torch.cuda.Event(enable_timing=True)

~/rohitd/venvs/t2-env/lib/python3.6/site-packages/triton/code_gen.py in <lambda>()
    621         # augment meta-parameters with tunable ones
    622         current = dict(meta, **config.meta)
--> 623         kernel_call = lambda: self.kernel(*args, num_warps=config.num_warps, num_stages=config.num_stages, **current)
    624         return triton.testing.do_bench(kernel_call)
    625 

~/rohitd/venvs/t2-env/lib/python3.6/site-packages/triton/code_gen.py in fun(*args, **meta)
    715                 for v, heur in values.items():
    716                     assert v not in meta
--> 717                     meta[v] = heur(*args, **meta)
    718                 return kernel(*args, **meta)
    719 

TypeError: <lambda>() got an unexpected keyword argument 'num_warps'

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startedopenai/triton

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PR opened openai/triton

@heuristics decorator docs.

Change: @heuristics decorator to @triton.heuristics. This code example shows up in the documentation as well.

Error when using just @heuristics:

NameError                             Traceback (most recent call last)
<ipython-input-7-1ac8acb536e2> in <module>
      7 #     key=['n_cols'],
      8 # )
----> 9 @heuristics(values={'BLOCK_SIZE': lambda args: 2 ** int(math.ceil(math.log2(args[4])))})
     10 @triton.jit
     11 def softmax_kernel(

NameError: name 'heuristics' is not defined
+1 -1

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commit sha e505f79af6d63abf8ea06305dc11ec7ea47052e1

Update code_gen.py Change: `@heuristics` decorator to `@triton.heuristics`. This code example shows up in the [documentation](https://triton-lang.org/python-api/generated/triton.heuristics.html) as well. Error when using just `@heuristics`: ``` NameError Traceback (most recent call last) <ipython-input-7-1ac8acb536e2> in <module> 7 # key=['n_cols'], 8 # ) ----> 9 @heuristics(values={'BLOCK_SIZE': lambda args: 2 ** int(math.ceil(math.log2(args[4])))}) 10 @triton.jit 11 def softmax_kernel( NameError: name 'heuristics' is not defined ```

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