Grid searchΒΆ
That is an example of a grid_search configuration:
executors:
train:
type: catalyst
args:
config: catalyst.yml
grid:
- batch_size: [20, 40, 80]
- - num_workers: 2
lr: 0.01
- num_workers: 3
lr: 0.1
The user needs to specify parameter sets in a grid field.
MLComp considers all possible combinations of them and transfers each combination to an executor within a special parameter: additional_info.
Each parameter set can be specified with 4 different ways:
key: list
for example, batch_size: [20, 40, 80]
list of dicts
for example,
- - num_workers: 2 lr: 0.01 - num_workers: 3 lr: 0.1
_folder: path_to_folder
for example,
_folder: configs/
Each config in the folder must be a valid yml file.
File structure is the same as in number 4.
_file: list of files
for example,
_file: [file1.yml]
File structure is an ordinary dictionary. For example,
num_workers: 2 lr: 0.01 stages: stage2: optimizer_params: optimizer: Adam lr: 0.001 weight_decay: 0.0001