コード例 #1
0
def _build_args(args):
    args["model"] = _parse_model_string(args["model"])
    args["loss"] = _parse_loss_string(args["loss"])
    a = fasttext.args()
    for (k, v) in args.items():
        setattr(a, k, v)
    a.output = ""  # User should use save_model
    a.saveOutput = 0  # Never use this
    if a.wordNgrams <= 1 and a.maxn == 0:
        a.bucket = 0
    return a
コード例 #2
0
ファイル: FastText.py プロジェクト: victorustc/fastText
def _build_args(args):
    args["model"] = _parse_model_string(args["model"])
    args["loss"] = _parse_loss_string(args["loss"])
    a = fasttext.args()
    for (k, v) in args.items():
        setattr(a, k, v)
    a.output = ""  # User should use save_model
    a.saveOutput = 0  # Never use this
    if a.wordNgrams <= 1 and a.maxn == 0:
        a.bucket = 0
    return a
コード例 #3
0
ファイル: FastText.py プロジェクト: whr94621/FastText
def _build_args(args):
    args["model"] = _parse_model_string(args["model"])
    args["loss"] = _parse_loss_string(args["loss"])
    a = fasttext.args()
    for (k, v) in args.items():
        setattr(a, k, v)
    a.test = ""  # Unused
    a.output = ""  # User should use save_model
    a.pretrainedVectors = ""  # Unsupported
    a.saveOutput = 0  # Never use this
    return a
コード例 #4
0
def _build_args(args):
    args["model"] = _parse_model_string(args["model"])
    args["loss"] = _parse_loss_string(args["loss"])
    a = fasttext.args()
    for (k, v) in args.items():
        setattr(a, k, v)
    a.test = ""  # Unused
    a.output = ""  # User should use save_model
    a.pretrainedVectors = ""  # Unsupported
    a.saveOutput = 0  # Never use this
    return a
コード例 #5
0
ファイル: FastText.py プロジェクト: wandb/fastText
def _build_args(args, manually_set_args):
    args["model"] = _parse_model_string(args["model"])
    args["loss"] = _parse_loss_string(args["loss"])
    if type(args["autotuneModelSize"]) == int:
        args["autotuneModelSize"] = str(args["autotuneModelSize"])

    a = fasttext.args()
    for (k, v) in args.items():
        setattr(a, k, v)
        if k in manually_set_args:
            a.setManual(k)
    a.output = ""  # User should use save_model
    a.saveOutput = 0  # Never use this
    if a.wordNgrams <= 1 and a.maxn == 0:
        a.bucket = 0
    return a