def call(self, inputs):
if ragged_tensor.is_ragged(inputs):
integer_buckets = ragged_functional_ops.map_flat_values(
gen_math_ops.Bucketize, input=inputs, boundaries=self.bins)
# Ragged map_flat_values doesn't touch the non-values tensors in the
# ragged composite tensor. If this op is the only op a Keras model,
# this can cause errors in Graph mode, so wrap the tensor in an identity.
return array_ops.identity(integer_buckets)
elif isinstance(inputs, sparse_tensor.SparseTensor):
integer_buckets = gen_math_ops.Bucketize(input=inputs.values,
boundaries=self.bins)
return sparse_tensor.SparseTensor(
indices=array_ops.identity(inputs.indices),
values=integer_buckets,
dense_shape=array_ops.identity(inputs.dense_shape))
else:
return gen_math_ops.Bucketize(input=inputs, boundaries=self.bins)
def bucketize(inputs):
return gen_math_ops.Bucketize(input=inputs,
boundaries=self.bin_boundaries)