mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 12:21:27 +01:00
8286ce1e3a
Summary: Closes https://github.com/caffe2/caffe2/pull/1260 Differential Revision: D5906739 Pulled By: Yangqing fbshipit-source-id: e482ba9ba60b5337d9165f28f7ec68d4518a0902
68 lines
2.2 KiB
Python
68 lines
2.2 KiB
Python
# Copyright (c) 2016-present, Facebook, Inc.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
##############################################################################
|
|
|
|
## @package split
|
|
# Module caffe2.python.layers.split
|
|
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
from __future__ import unicode_literals
|
|
|
|
from caffe2.python import schema
|
|
from caffe2.python.layers.layers import (
|
|
ModelLayer,
|
|
)
|
|
|
|
|
|
class Split(ModelLayer):
|
|
|
|
def __init__(self, model, input_record, num_splits, axis=1,
|
|
name='split', **kwargs):
|
|
super(Split, self).__init__(model, name, input_record, **kwargs)
|
|
self.axis = axis
|
|
# Assume that first dimension is batch, so actual axis in shape is
|
|
# axis - 1
|
|
axis -= 1
|
|
assert axis >= 0
|
|
|
|
assert isinstance(input_record, schema.Scalar),\
|
|
"Incorrect input type. Excpected Scalar, but received: {0}".\
|
|
format(input_record)
|
|
|
|
input_shape = input_record.field_type().shape
|
|
assert len(input_shape) >= axis
|
|
assert input_shape[axis] % num_splits == 0
|
|
|
|
output_shape = list(input_shape)
|
|
output_shape[axis] = int(output_shape[axis] / num_splits)
|
|
|
|
data_type = input_record.field_type().base
|
|
|
|
output_scalars = [
|
|
schema.Scalar(
|
|
(data_type, output_shape),
|
|
self.get_next_blob_reference('output_{}'.format(i)),
|
|
)
|
|
for i in range(num_splits)
|
|
]
|
|
self.output_schema = schema.Tuple(*output_scalars)
|
|
|
|
def add_ops(self, net):
|
|
net.Split(
|
|
self.input_record.field_blobs(),
|
|
self.output_schema.field_blobs(),
|
|
axis=self.axis,
|
|
)
|