Exemplos de register em Python

Exemplo n.º 1

 def test_load(self):
     register(
         model_id='test_load',
         entry_point='rlcard.models.pretrained_models:LeducHoldemCFRModel')
     models.load('test_load')
     with self.assertRaises(ValueError):
         load('test_random_make')

Exemplo n.º 2

 def test_register(self):
     register(
         model_id='test_reg',
         entry_point='rlcard.models.pretrained_models:LeducHoldemCFRModel')
     with self.assertRaises(ValueError):
         register(model_id='test_reg',
                  entry_point=
                  'rlcard.models.pretrained_models:LeducHoldemCFRModel')

Exemplo n.º 3

''' Register rule-based models or pre-trianed models
'''

from rlcard.models.registration import register, load

register(
    model_id = 'leduc-holdem-nfsp',
    entry_point='rlcard.models.pretrained_models:LeducHoldemNFSPModel')

register(
    model_id = 'uno-rule-v1',
    entry_point='rlcard.models.uno_rule_models:UNORuleModelV1')

register(
    model_id = 'badugi-rule-v1',
    entry_point='rlcard.models.badugi_rule_models:BadugiRuleModelV1')

Exemplo n.º 4

Arquivo: __init__.py Projeto: GoooKuuu/NoLimitHoldem

from rlcard.models.registration import register, load
import subprocess
import sys
from distutils.version import LooseVersion

reqs = subprocess.check_output([sys.executable, '-m', 'pip', 'freeze'])
installed_packages = [r.decode().split('==')[0] for r in reqs.split()]

if 'tensorflow' in installed_packages:
    import tensorflow as tf
    if LooseVersion(tf.__version__) < LooseVersion('1.14.0') \
            or LooseVersion(tf.__version__) >= LooseVersion('2.0.0'):
        print('WAINING - RLCard supports Tensorflow >=1.14 and <2.0\nThe detected version is {} \nIf the models can not be loaded, please install Tensorflow via\n$ pip install rlcard[tensorflow]\n'.format(tf.__version__))
    register(
        model_id = 'leduc-holdem-nfsp',
        entry_point='rlcard.models.pretrained_models:LeducHoldemNFSPModel')

if 'torch' in installed_packages:
    register(
        model_id = 'leduc-holdem-nfsp-pytorch',
        entry_point='rlcard.models.pretrained_models:LeducHoldemNFSPPytorchModel')

register(
    model_id = 'leduc-holdem-cfr',
    entry_point='rlcard.models.pretrained_models:LeducHoldemCFRModel')

register(
    model_id = 'leduc-holdem-rule-v1',
    entry_point='rlcard.models.leducholdem_rule_models:LeducHoldemRuleModelV1')

Exemplo n.º 5

Arquivo: __init__.py Projeto: nacoyang/rlcard

''' Register rule-based models or pre-trianed models
'''

from rlcard.models.registration import register, load
import subprocess
import sys

reqs = subprocess.check_output([sys.executable, '-m', 'pip', 'freeze'])
installed_packages = [r.decode().split('==')[0] for r in reqs.split()]

if 'tensorflow' in installed_packages:
    register(
        model_id='leduc-holdem-nfsp',
        entry_point='rlcard.models.pretrained_models:LeducHoldemNFSPModel')
if 'torch' in installed_packages:
    register(model_id='leduc-holdem-nfsp-pytorch',
             entry_point=
             'rlcard.models.pretrained_models:LeducHoldemNFSPPytorchModel')

register(model_id='leduc-holdem-cfr',
         entry_point='rlcard.models.pretrained_models:LeducHoldemCFRModel')

register(
    model_id='leduc-holdem-rule-v1',
    entry_point='rlcard.models.leducholdem_rule_models:LeducHoldemRuleModelV1')

register(
    model_id='leduc-holdem-rule-v2',
    entry_point='rlcard.models.leducholdem_rule_models:LeducHoldemRuleModelV2')

register(model_id='uno-rule-v1',

Exemplo n.º 6

Arquivo: __init__.py Projeto: aditya140/rlcard

import subprocess
import sys
from packaging import version

reqs = subprocess.check_output([sys.executable, '-m', 'pip', 'freeze'])
installed_packages = [r.decode().split('==')[0] for r in reqs.split()]

if 'tensorflow' in installed_packages:
    import tensorflow as tf
    if version.parse(tf.__version__) < version.parse('1.14.0') \
            or version.parse(tf.__version__) >= version.parse('2.0.0'):
        print(
            'WAINING - RLCard supports Tensorflow >=1.14 and <2.0\nThe detected version is {} \nIf the models can not be loaded, please install Tensorflow via\n$ pip install rlcard[tensorflow]\n'
            .format(tf.__version__))
    register(
        model_id='leduc-holdem-nfsp',
        entry_point='rlcard.models.pretrained_models:LeducHoldemNFSPModel')

    register(model_id='uno-nfsp',
             entry_point='rlcard.models.pretrained_models:UnoNFSPModel')

if 'torch' in installed_packages:
    register(model_id='leduc-holdem-nfsp-pytorch',
             entry_point=
             'rlcard.models.pretrained_models:LeducHoldemNFSPPytorchModel')

register(model_id='leduc-holdem-cfr',
         entry_point='rlcard.models.pretrained_models:LeducHoldemCFRModel')

register(
    model_id='leduc-holdem-rule-v1',

Exemplo n.º 7

Arquivo: __init__.py Projeto: sjoerdapp/RL-tarot

""" Register rule-based models or pre-trianed models
"""

from rlcard.models.registration import register, load

register(model_id='tarot-rule-v1',
         entry_point='rlcard.models.tarot_rule_models:TAROTRuleModelV1')

register(model_id='tarot-bid-rule-v1',
         entry_point='rlcard.models.tarot_bid_rule_models:TAROTBIDRuleModelV1')

register(model_id='tarot-dog-rule-v1',
         entry_point='rlcard.models.tarot_dog_rule_models:TAROTDOGRuleModelV1')