def pseudo_call(self, pseudo_inputs, params, state):
"""Computes shapes and types this layer would produce for the given inputs.
Args:
pseudo_inputs: A ShapeType instance (input data minus the actual values)
or a tuple of ShapeType instances, following the same conventions as
Layer.call's input arg.
params: Parameters for this layer.
state: start state.
Returns:
A ShapeType instance representing the shape and type of the output (if
this layer has one output) or a tuple of ShapeType instances (if this
layer has more than one output).
"""
try:
# Beware: using an actual RNG (as opposed to this ShapeType stub) would
# cause a large number of dropout masks to be computed and permanently
# stored in global memory.
rng = ShapeType(shape=(2, ), dtype=onp.uint32)
def call_on_input(x, params, state, rng):
return self.call(x, params=params, state=state, rng=rng)
params_shapes = nested_map(
params, lambda x: ShapeType(shape=x.shape, dtype=x.dtype))
s = backend.eval_on_shapes(call_on_input)(pseudo_inputs,
params_shapes, state,
rng)
return s
except Exception:
name, trace = self.__class__.__name__, _short_traceback(skip=3)
raise LayerError(name, 'pseudo_call', self._caller, pseudo_inputs,
trace)
def sizes(x):
"""Get a structure of sizes for a structure of nested arrays."""
def size(x):
try:
return x.size
except Exception: # pylint: disable=broad-except
return 0
return nested_map(x, size)
def shapes(x):
"""Get a structure of shapes for a structure of nested arrays."""
def shape(x):
try:
return tuple([int(i) for i in x.shape])
except Exception: # pylint: disable=broad-except
return []
return nested_map(x, shape)
