pytorch/caffe2/python/layers/dot_product.py
Aaron Markham 58f7f2b441 doxygen python block added
Summary: Closes https://github.com/caffe2/caffe2/pull/226

Differential Revision: D4793550

Pulled By: JoelMarcey

fbshipit-source-id: cc33e58186304fa8dcac2ee9115dcc271d785b1e
2017-03-29 06:46:16 -07:00

40 lines
1.4 KiB
Python

## @package dot_product
# Module caffe2.python.layers.dot_product
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from caffe2.python import core, schema
from caffe2.python.layers.layers import (
ModelLayer,
)
class DotProduct(ModelLayer):
def __init__(self, model, input_record, name='dot_product', **kwargs):
super(DotProduct, self).__init__(model, name, input_record, **kwargs)
assert isinstance(input_record, schema.Struct),\
"Incorrect input type. Excpected Struct, but received: {0}".\
format(input_record)
assert len(input_record.get_children()) == 2, (
"DotProduct accept 2 inputs")
assert len(set(input_record.field_types())) == 1, (
"Inputs should be of the same field type")
for field_name, field_type in input_record.fields.items():
assert isinstance(field_type, schema.Scalar),\
"Incorrect input type for {}. Excpected Scalar, but got: {}".\
format(field_name, field_type)
self.output_schema = schema.Scalar(
(input_record.field_types()[0].base, ()),
model.net.NextScopedBlob(name + '_output'))
def add_ops(self, net):
net.DotProduct(
self.input_record.field_blobs(),
self.output_schema(),
)