Sacred - pass all parameters as one
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When using Sacred it is necessary to pass all variables from the experiment config, into the main function, for example
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
@ex.automain
def run(C, gamma):
iris = datasets.load_iris()
per = permutation(iris.target.size)
iris.data = iris.data[per]
iris.target = iris.target[per]
clf = svm.SVC(C, 'rbf', gamma=gamma)
clf.fit(iris.data[:90],
iris.target[:90])
return clf.score(iris.data[90:],
iris.target[90:])
As you can see, in this experiment there are 2 variables, C and gamma, and they are passed into the main function.
In real scenarios, there are dozens of experiment variables, and the passing all of them into the main function gets really cluttered.
Is there a way to pass them all as a dictionary? Or maybe as an object with attributes?
A good solution will result in something like follows:
@ex.automain
def run(config):
config.C # Option 1
config['C'] # Option 2
python python-sacred
asked Nov 22 '18 at 12:41
bluesummersbluesummers
2,57612650
add a comment |
0
When using Sacred it is necessary to pass all variables from the experiment config, into the main function, for example
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
@ex.automain
def run(C, gamma):
iris = datasets.load_iris()
per = permutation(iris.target.size)
iris.data = iris.data[per]
iris.target = iris.target[per]
clf = svm.SVC(C, 'rbf', gamma=gamma)
clf.fit(iris.data[:90],
iris.target[:90])
return clf.score(iris.data[90:],
iris.target[90:])
As you can see, in this experiment there are 2 variables, C and gamma, and they are passed into the main function.
In real scenarios, there are dozens of experiment variables, and the passing all of them into the main function gets really cluttered.
Is there a way to pass them all as a dictionary? Or maybe as an object with attributes?
A good solution will result in something like follows:
@ex.automain
def run(config):
config.C # Option 1
config['C'] # Option 2
python python-sacred
asked Nov 22 '18 at 12:41
bluesummersbluesummers
2,57612650
Not sure about sacred, but in python you can! this is what is often refered to **kwargs you can check here for some example: book.pythontips.com/en/latest/args_and_kwargs.html
– RomainL.
Nov 22 '18 at 12:52
Yep, I'm aware of that. The problem is that I am not the one passing the variables from thecfgfunction into therunfunction so I'm not responsible for sending them as positional / key-word arguments
– bluesummers
Nov 22 '18 at 12:55
add a comment |
0
0
0
When using Sacred it is necessary to pass all variables from the experiment config, into the main function, for example
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
@ex.automain
def run(C, gamma):
iris = datasets.load_iris()
per = permutation(iris.target.size)
iris.data = iris.data[per]
iris.target = iris.target[per]
clf = svm.SVC(C, 'rbf', gamma=gamma)
clf.fit(iris.data[:90],
iris.target[:90])
return clf.score(iris.data[90:],
iris.target[90:])
As you can see, in this experiment there are 2 variables, C and gamma, and they are passed into the main function.
In real scenarios, there are dozens of experiment variables, and the passing all of them into the main function gets really cluttered.
Is there a way to pass them all as a dictionary? Or maybe as an object with attributes?
A good solution will result in something like follows:
@ex.automain
def run(config):
config.C # Option 1
config['C'] # Option 2
python python-sacred
asked Nov 22 '18 at 12:41
bluesummersbluesummers
2,57612650
When using Sacred it is necessary to pass all variables from the experiment config, into the main function, for example
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
@ex.automain
def run(C, gamma):
iris = datasets.load_iris()
per = permutation(iris.target.size)
iris.data = iris.data[per]
iris.target = iris.target[per]
clf = svm.SVC(C, 'rbf', gamma=gamma)
clf.fit(iris.data[:90],
iris.target[:90])
return clf.score(iris.data[90:],
iris.target[90:])
As you can see, in this experiment there are 2 variables, C and gamma, and they are passed into the main function.
In real scenarios, there are dozens of experiment variables, and the passing all of them into the main function gets really cluttered.
Is there a way to pass them all as a dictionary? Or maybe as an object with attributes?
A good solution will result in something like follows:
@ex.automain
def run(config):
config.C # Option 1
config['C'] # Option 2
python python-sacred
python python-sacred
asked Nov 22 '18 at 12:41
bluesummersbluesummers
2,57612650
asked Nov 22 '18 at 12:41
bluesummersbluesummers
2,57612650
asked Nov 22 '18 at 12:41
bluesummersbluesummers
2,57612650
asked Nov 22 '18 at 12:41
bluesummersbluesummers
2,57612650
asked Nov 22 '18 at 12:41
bluesummersbluesummers
2,57612650
2,57612650
Not sure about sacred, but in python you can! this is what is often refered to **kwargs you can check here for some example: book.pythontips.com/en/latest/args_and_kwargs.html
– RomainL.
Nov 22 '18 at 12:52
Yep, I'm aware of that. The problem is that I am not the one passing the variables from thecfgfunction into therunfunction so I'm not responsible for sending them as positional / key-word arguments
– bluesummers
Nov 22 '18 at 12:55
add a comment |
Not sure about sacred, but in python you can! this is what is often refered to **kwargs you can check here for some example: book.pythontips.com/en/latest/args_and_kwargs.html
– RomainL.
Nov 22 '18 at 12:52
Yep, I'm aware of that. The problem is that I am not the one passing the variables from thecfgfunction into therunfunction so I'm not responsible for sending them as positional / key-word arguments
– bluesummers
Nov 22 '18 at 12:55
Not sure about sacred, but in python you can! this is what is often refered to **kwargs you can check here for some example: book.pythontips.com/en/latest/args_and_kwargs.html
– RomainL.
Nov 22 '18 at 12:52
Not sure about sacred, but in python you can! this is what is often refered to **kwargs you can check here for some example: book.pythontips.com/en/latest/args_and_kwargs.html
– RomainL.
Nov 22 '18 at 12:52
Yep, I'm aware of that. The problem is that I am not the one passing the variables from the
cfg function into the run function so I'm not responsible for sending them as positional / key-word arguments– bluesummers
Nov 22 '18 at 12:55
Yep, I'm aware of that. The problem is that I am not the one passing the variables from the
cfg function into the run function so I'm not responsible for sending them as positional / key-word arguments– bluesummers
Nov 22 '18 at 12:55
add a comment |
2 Answers
2
active
oldest
votes
1
Yes, you can use the special value _config value for that:
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
@ex.automain
def run(_config):
C = _config['C']
gamma = _config['gamma']
answered Mar 4 at 11:44
QlausQlaus
739312
add a comment |
1
Most elegant solution I could find
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
params = {'C': C, 'gamma': gamma}
@ex.automain
def run(params):
iris = datasets.load_iris()
per = permutation(iris.target.size)
iris.data = iris.data[per]
iris.target = iris.target[per]
clf = svm.SVC(params['C'], 'rbf', gamma=params['gamma'])
clf.fit(iris.data[:90],
iris.target[:90])
return clf.score(iris.data[90:],
iris.target[90:])
answered Dec 4 '18 at 17:17
bluesummersbluesummers
2,57612650
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
1
Yes, you can use the special value _config value for that:
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
@ex.automain
def run(_config):
C = _config['C']
gamma = _config['gamma']
answered Mar 4 at 11:44
QlausQlaus
739312
add a comment |
1
Yes, you can use the special value _config value for that:
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
@ex.automain
def run(_config):
C = _config['C']
gamma = _config['gamma']
answered Mar 4 at 11:44
QlausQlaus
739312
add a comment |
1
1
1
Yes, you can use the special value _config value for that:
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
@ex.automain
def run(_config):
C = _config['C']
gamma = _config['gamma']
answered Mar 4 at 11:44
QlausQlaus
739312
Yes, you can use the special value _config value for that:
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
@ex.automain
def run(_config):
C = _config['C']
gamma = _config['gamma']
answered Mar 4 at 11:44
QlausQlaus
739312
answered Mar 4 at 11:44
QlausQlaus
739312
answered Mar 4 at 11:44
QlausQlaus
739312
answered Mar 4 at 11:44
QlausQlaus
739312
739312
add a comment |
add a comment |
1
Most elegant solution I could find
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
params = {'C': C, 'gamma': gamma}
@ex.automain
def run(params):
iris = datasets.load_iris()
per = permutation(iris.target.size)
iris.data = iris.data[per]
iris.target = iris.target[per]
clf = svm.SVC(params['C'], 'rbf', gamma=params['gamma'])
clf.fit(iris.data[:90],
iris.target[:90])
return clf.score(iris.data[90:],
iris.target[90:])
answered Dec 4 '18 at 17:17
bluesummersbluesummers
2,57612650
add a comment |
1
Most elegant solution I could find
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
params = {'C': C, 'gamma': gamma}
@ex.automain
def run(params):
iris = datasets.load_iris()
per = permutation(iris.target.size)
iris.data = iris.data[per]
iris.target = iris.target[per]
clf = svm.SVC(params['C'], 'rbf', gamma=params['gamma'])
clf.fit(iris.data[:90],
iris.target[:90])
return clf.score(iris.data[90:],
iris.target[90:])
answered Dec 4 '18 at 17:17
bluesummersbluesummers
2,57612650
add a comment |
1
1
1
Most elegant solution I could find
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
params = {'C': C, 'gamma': gamma}
@ex.automain
def run(params):
iris = datasets.load_iris()
per = permutation(iris.target.size)
iris.data = iris.data[per]
iris.target = iris.target[per]
clf = svm.SVC(params['C'], 'rbf', gamma=params['gamma'])
clf.fit(iris.data[:90],
iris.target[:90])
return clf.score(iris.data[90:],
iris.target[90:])
answered Dec 4 '18 at 17:17
bluesummersbluesummers
2,57612650
Most elegant solution I could find
ex = Experiment('iris_rbf_svm')
@ex.config
def cfg():
C = 1.0
gamma = 0.7
params = {'C': C, 'gamma': gamma}
@ex.automain
def run(params):
iris = datasets.load_iris()
per = permutation(iris.target.size)
iris.data = iris.data[per]
iris.target = iris.target[per]
clf = svm.SVC(params['C'], 'rbf', gamma=params['gamma'])
clf.fit(iris.data[:90],
iris.target[:90])
return clf.score(iris.data[90:],
iris.target[90:])
answered Dec 4 '18 at 17:17
bluesummersbluesummers
2,57612650
answered Dec 4 '18 at 17:17
bluesummersbluesummers
2,57612650
answered Dec 4 '18 at 17:17
bluesummersbluesummers
2,57612650
answered Dec 4 '18 at 17:17
bluesummersbluesummers
2,57612650
2,57612650
add a comment |
add a comment |
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Not sure about sacred, but in python you can! this is what is often refered to **kwargs you can check here for some example: book.pythontips.com/en/latest/args_and_kwargs.html
– RomainL.
Nov 22 '18 at 12:52
Yep, I'm aware of that. The problem is that I am not the one passing the variables from the
cfgfunction into therunfunction so I'm not responsible for sending them as positional / key-word arguments– bluesummers
Nov 22 '18 at 12:55