def get_io() -> IO:
return IO(
{
"i": IOInput(
glob("../../data/tracks/*.wav"),
list,
has_input=True,
arg_name="input_files",
descr="Input .wav files",
alias="input_files",
is_generic=True,
),
"a": IOInput(
"../../data/analysis.json",
str,
has_input=True,
arg_name="analysis",
descr="Analysis JSON file",
alias="analysis",
),
"o": IOInput(
"../../data/preprocessed.pickle",
str,
has_input=True,
arg_name="output_file",
descr="File in which the features and outputs get placed",
alias="output_file",
),
"n": IOInput(
50, int, has_input=True, arg_name="interval", descr="Interval at which data is sent", alias="interval"
),
}
)
def get_io() -> IO:
return IO({
"i":
IOInput(
"./data/preprocessed.pickle",
str,
has_input=True,
arg_name="input_preprocessed",
descr="Input preprocessed file",
alias="input_preprocessed",
is_generic=True,
),
"iw":
IOInput(
"./data/weights.h5",
str,
has_input=True,
arg_name="input_weights",
descr="Input weights file",
alias="input_weights",
),
"it":
IOInput(
"./data/train_config.json",
str,
has_input=True,
arg_name="input_train",
descr="Input file for the train config",
alias="input_train",
),
"o":
IOInput(
"./data/annotated/",
str,
has_input=True,
arg_name="output_annotated",
descr="Directory where annotated files are stored",
alias="output_annotated",
),
"n":
IOInput(50,
int,
has_input=True,
arg_name="interval",
descr="Interval at which data is sent",
alias="interval"),
})
def get_io() -> IO:
return IO({
"p":
IOInput(1234,
int,
has_input=True,
arg_name="port",
descr="The port on which to host it",
alias="port"),
"n":
IOInput(50,
int,
has_input=True,
arg_name="interval",
descr="Interval at which data is sent",
alias="interval"),
})
def get_io() -> IO:
return IO(
{
"i": IOInput(
"./data/preprocessed.pickle",
str,
has_input=True,
arg_name="input_file",
descr="Input preprocessed file",
alias="input_file",
is_generic=True,
),
"ow": IOInput(
"./data/weights.h5",
str,
has_input=True,
arg_name="output_weights",
descr="File in which the weights gets stored",
alias="output_weights",
),
"ot": IOInput(
"./data/train_config.json",
str,
has_input=True,
arg_name="output_train",
descr="File in which the training config gets stored",
alias="output_train",
),
"s": IOInput(
80,
int,
has_input=True,
arg_name="split",
descr="The split between training and test sets",
alias="split",
),
"b": IOInput(32, int, has_input=True, arg_name="batch_size", descr="The batch size", alias="batch_size",),
"e": IOInput(10, int, has_input=True, arg_name="epochs", descr="The amount of epochs", alias="epochs",),
}
)