class Training(PyBioSchema):
setup = fields.Nested(Setup)
source = fields.ImportableSource(required=True)
required_kwargs = fields.List(fields.Str, missing=list)
optional_kwargs = fields.Dict(fields.Str, missing=dict)
dependencies = fields.Dependencies(required=True)
description = fields.Str(missing=None)
class ModelSpec(BaseSpec):
prediction = fields.Nested(Prediction)
inputs = fields.Tensors(InputArray, valid_magic_values=[MagicTensorsValue.any], many=True)
outputs = fields.Tensors(
OutputArray, valid_magic_values=[MagicTensorsValue.same, MagicTensorsValue.dynamic], many=True
)
training = fields.Nested(Training, missing=None)
@validates("outputs")
def validate_reference_input_names(self, data, **kwargs):
pass # todo validate_reference_input_names
# @validates_schema
def input_propagation_from_training_reader(self, data, **kwargs):
spec: nodes.ModelSpec = self.make_object(data, **kwargs)
if spec.training is None:
return
reader_axes = spec.training.setup.reader.spec.outputs
inputs = spec.inputs
class BaseSpec(PyBioSchema):
name = fields.Str(required=True)
format_version = fields.Str(required=True)
description = fields.Str(required=True)
cite = fields.Nested(CiteEntry, many=True, required=True)
authors = fields.List(fields.Str(required=True))
documentation = fields.Path(required=True)
tags = fields.List(fields.Str, required=True)
language = fields.Str(required=True)
framework = fields.Str(missing=None)
source = fields.ImportableSource(required=True)
required_kwargs = fields.List(fields.Str, missing=list)
optional_kwargs = fields.Dict(fields.Str, missing=dict)
test_input = fields.Path(missing=None)
test_output = fields.Path(missing=None)
thumbnail = fields.Path(missing=None)
class Setup(PyBioSchema):
samplers = fields.List(fields.Nested(Sampler, required=True), required=True)
preprocess = fields.Nested(Transformation, many=True, missing=list)
postprocess = fields.Nested(Transformation, many=True, missing=list)
losses = fields.Nested(Transformation, many=True, missing=list)
optimizer = fields.Nested(Optimizer, missing=None)
class Sampler(SpecWithKwargs):
spec = fields.SpecURI(SamplerSpec)
readers = fields.List(fields.Nested(Reader, required=True), required=True)
class Reader(SpecWithKwargs):
spec = fields.SpecURI(ReaderSpec)
transformations = fields.List(fields.Nested(Transformation), missing=list)
class Prediction(PyBioSchema):
weights = fields.Nested(Weights, missing=None)
dependencies = fields.Dependencies(missing=None)
preprocess = fields.Nested(Transformation, many=True, missing=list)
postprocess = fields.Nested(Transformation, many=True, missing=list)