Exemple #1
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def main():
    import sys

    log.init(verbose=True)
    m = model.from_json(clgen.load_json_file(sys.argv[1]))
    s = sampler.from_json({
        "kernels": {
            "args": [
                "__global float*", "__global float*", "__global float*",
                "const int"
            ],
            "max_length":
            5000,
            "temperature":
            1
        },
        "sampler": {
            "batch_size": 1000,
            "max_batches": 1,
            "static_checker": False,
            "dynamic_checker": False
        }
    })

    print("Corpus size:", m.corpus.size)
    print("Vocab size: ", m.corpus.vocab_size)
    print()
    clgen.platform_info()
    print()

    outpath = "./benchmark-" + fs.basename(sys.argv[1])
    info = evaluate(m, s)
    clgen.write_file(outpath, clgen.format_json(info))
Exemple #2
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def main():
    import sys

    log.init(verbose=True)
    m = model.from_json(clgen.load_json_file(sys.argv[1]))
    s = sampler.from_json({
        "kernels": {
            "args": [
                "__global float*",
                "__global float*",
                "__global float*",
                "const int"
            ],
            "max_length": 5000,
            "temperature": 1
        },
        "sampler": {
            "batch_size": 1000,
            "max_batches": 1,
            "static_checker": False,
            "dynamic_checker": False
        }
    })

    print("Corpus size:", m.corpus.size)
    print("Vocab size: ", m.corpus.vocab_size)
    print()
    clgen.platform_info()
    print()

    outpath = "./benchmark-" + fs.basename(sys.argv[1])
    info = evaluate(m, s)
    clgen.write_file(outpath, clgen.format_json(info))
Exemple #3
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def main():
    log.init(verbose=True)

    m = model.from_json(clgen.load_json_file(sys.argv[1]))
    c = corpus.Corpus.from_json({"path": "~/data/github"})
    print("CLgen:      ", clgen.version())
    print("Corpus size:", c.size)
    print("Vocab size: ", c.vocab_size)

    m.train()

    p, _ = corpus.most_common_prototypes(c, 20)
    for i, row in enumerate(p):
        outpath = "./inference-p" + str(i + 1) + "-" + fs.basename(sys.argv[1])
        if fs.exists(outpath):
            continue

        _, prototype = row
        argspec = [' '.join(x.split()[:-1]) for x in prototype.split(',')]
        print("argspec", ','.join([str(x) for x in argspec]))
        s = sampler.from_json({
            "kernels": {
                "args": argspec,
                "max_length": 5000
            },
            "sampler": {
                "batch_size": 2000,
                "max_batches": 1,
                "static_checker": False,
                "dynamic_checker": False
            }
        })

        info = evaluate(m, s)
        clgen.write_file(outpath, clgen.format_json(info))
Exemple #4
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    def to_dist(self, distpath: str, author: str = None) -> str:
        """
        Create a dist file.

        Arguments:
            distpath (str): Path to dist file.
            author (str, optional): Author name.

        Returns:
            str: Path to generated distfile.
        """
        outpath = fs.abspath(distpath) + ".tar.bz2"
        if fs.exists(outpath):
            raise DistError("file {} exists".format(outpath))

        meta = self.meta
        if author is not None:
            meta["author"] = author
        log.debug(clgen.format_json(meta))

        try:
            tar = tarfile.open(outpath, 'w:bz2')

            # write meta
            metapath = mktemp(prefix="clgen-", suffix=".json")
            clgen.write_file(metapath, clgen.format_json(meta))
            log.debug("metafile:", metapath)

            # create tarball
            tar.add(metapath, arcname="meta.json")

            # pack contents:
            for path in meta["contents"]:
                abspath = fs.path(cache.ROOT, path)
                log.verbose("packing", abspath)
                tar.add(abspath, arcname=fs.path("contents", path))

            # tidy up
            fs.rm(metapath)
            tar.close()
        except Exception as e:
            tar.close()
            fs.rm(metapath)
            fs.rm(outpath)
            raise e

        return outpath
Exemple #5
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def main():
    log.init(verbose=True)

    m = model.from_json(clgen.load_json_file(sys.argv[1]))
    c = corpus.Corpus.from_json({"path": "~/data/github"})
    print("CLgen:      ", clgen.version())
    print("Corpus size:", c.size)
    print("Vocab size: ", c.vocab_size)

    m.train()

    p, _ = corpus.most_common_prototypes(c, 20)
    for i, row in enumerate(p):
        outpath = "./inference-p" + str(i + 1) + "-" + fs.basename(sys.argv[1])
        if fs.exists(outpath):
            print("skipped result for", outpath)
            continue
        else:
            print("starting result for", outpath)

        _, prototype = row
        argspec = [' '.join(x.split()[:-1]) for x in prototype.split(',')]
        print("argspec", ','.join([str(x) for x in argspec]))
        s = sampler.from_json({
            "kernels": {
                "args": argspec,
                "max_length": 5000
            },
            "sampler": {
                "batch_size": 2000,
                "max_batches": 1,
                "static_checker": False,
                "dynamic_checker": False
            }
        })

        info = evaluate(m, s)
        clgen.write_file(outpath, clgen.format_json(info))
Exemple #6
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def write_log(log, logpath):
    clgen.write_file(logpath, clgen.format_json(log))
Exemple #7
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def write_log(log, logpath):
    clgen.write_file(logpath, clgen.format_json(log))
Exemple #8
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 def __repr__(self) -> str:
     """
     String representation.
     """
     return "{hash}: {data}".format(hash=self.hash,
                                    data=clgen.format_json(self.opts))