def zero_batch_step(self, data, **kwargs):
axes = data["axes"]
shape = data["shape"]
if not isinstance(shape, MagicShapeValue):
if axes is None:
raise PyBioValidationException("Axes field required when shape is specified")
assert isinstance(axes, str), type(axes)
bidx = axes.find("b")
if isinstance(shape, tuple):
# exact shape (with batch size 1)
if bidx != -1 and shape[bidx] != 1:
raise PyBioValidationException("Input shape has to be one in the batch dimension.")
elif isinstance(shape, nodes.InputShape):
step = shape.step
if bidx != -1 and shape.min[bidx] != 1:
raise PyBioValidationException("Input shape has to be one in the batch dimension.")
if bidx != -1 and step[bidx] != 0:
raise PyBioValidationException(
"Input shape step has to be zero in the batch dimension (the batch dimension can always be "
"increased, but `step` should specify how to increase the minimal shape to find the largest "
"single batch shape)"
)
else:
raise PyBioValidationException(f"Unknown shape type {type(shape)}")
def _deserialize(
self,
value: typing.Any,
attr: typing.Optional[str],
data: typing.Optional[typing.Mapping[str, typing.Any]],
**kwargs,
):
if isinstance(value, str):
try:
value = nodes.MagicShapeValue(value)
except ValueError as e:
raise PyBioValidationException(str(e)) from e
if value in self.valid_magic_values:
return value
else:
raise PyBioValidationException(
f"Invalid magic value: {value.value}")
elif isinstance(value, list):
if any(not isinstance(v, int) for v in value):
raise PyBioValidationException(
"Encountered non-integers in shape")
return tuple(value)
elif isinstance(value, dict):
return self._load(value, data)
else:
raise PyBioValidationException(
f"Invalid input type: {type(value)}")
def _deserialize(
self,
value: typing.Any,
attr: typing.Optional[str],
data: typing.Optional[typing.Mapping[str, typing.Any]],
**kwargs,
):
if isinstance(value, str):
try:
value = nodes.MagicTensorsValue(value)
except ValueError as e:
raise PyBioValidationException(str(e)) from e
if value in self.valid_magic_values:
return value
else:
raise PyBioValidationException(
f"Invalid magic value: {value.value}")
elif isinstance(value, list):
return self._load(value, data, many=True)
# if all(isinstance(v, str) for v in value):
# return namedtuple("CustomTensors", value)
# else:
# return self._load(value, data, many=True)
else:
raise PyBioValidationException(
f"Invalid input type: {type(value)}")
def _deserialize(self, *args, **kwargs) -> nodes.URI:
uri_str = super()._deserialize(*args, **kwargs)
uri = urlparse(uri_str)
if uri.fragment:
raise PyBioValidationException(
f"Invalid URI: {uri}. Got URI fragment: {uri.fragment}")
if uri.params:
raise PyBioValidationException(
f"Invalid URI: {uri}. Got URI params: {uri.params}")
return nodes.URI(scheme=uri.scheme,
netloc=uri.netloc,
path=uri.path,
query=uri.query)
def _deserialize(self, *args, **kwargs) -> str:
axes_str = super()._deserialize(*args, **kwargs)
valid_axes = "bczyx"
if any(a not in valid_axes for a in axes_str):
raise PyBioValidationException(
f"Invalid axes! Valid axes are: {valid_axes}")
return axes_str
def _deserialize(self, value, attr, data, **kwargs):
uri = urlparse(value)
if uri.query:
raise PyBioValidationException(
f"Invalid URI: {uri}. Got URI query: {uri.query}")
if uri.fragment:
raise PyBioValidationException(
f"Invalid URI: {uri}. Got URI fragment: {uri.fragment}")
if uri.params:
raise PyBioValidationException(
f"Invalid URI: {uri}. Got URI params: {uri.params}")
return nodes.SpecURI(spec_schema=self.schema,
scheme=uri.scheme,
netloc=uri.netloc,
path=uri.path,
query="")
def matching_lengths(self, data, **kwargs):
min_ = data["min"]
step = data["step"]
if min_ is None or step is None:
return
if len(min_) != len(step):
raise PyBioValidationException(
f"'min' and 'step' have to have the same length! (min: {min_}, step: {step})"
)
def matching_halo_length(self, data, **kwargs):
shape = data["shape"]
halo = data["halo"]
if halo is None:
return
elif isinstance(shape, tuple) or isinstance(shape, nodes.OutputShape):
if len(halo) != len(shape):
raise PyBioValidationException(f"halo {halo} has to have same length as shape {shape}!")
elif not isinstance(shape, MagicShapeValue):
raise NotImplementedError
def axes_and_shape(self, data, **kwargs):
axes = data["axes"]
shape = data["shape"]
if not isinstance(shape, MagicShapeValue) and shape and axes is None:
raise PyBioValidationException("Axes may not be 'null', when shape is specified")
def matching_lengths(self, data, **kwargs):
scale = data["scale"]
offset = data["offset"]
if len(scale) != len(offset):
raise PyBioValidationException(f"scale {scale} has to have same length as offset {offset}!")