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
62 lines
2.1 KiB
Python
62 lines
2.1 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 elementwise_linear
|
|
# Module caffe2.python.helpers.elementwise_linear
|
|
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
from __future__ import unicode_literals
|
|
|
|
from caffe2.python import core
|
|
from caffe2.python.modeling.parameter_info import ParameterTags
|
|
|
|
|
|
def _elementwise_linear(
|
|
model, op_call, blob_in, blob_out, dim,
|
|
weight_init=None, bias_init=None, **kwargs
|
|
):
|
|
"""Elementwise_Linear"""
|
|
weight_init = weight_init or ('ConstantFill', {'value': 1.0})
|
|
bias_init = bias_init or ('ConstantFill', {'value': 0.0})
|
|
blob_out = blob_out or model.net.NextName()
|
|
if model.init_params:
|
|
weight = model.param_init_net.__getattr__(weight_init[0])(
|
|
[],
|
|
blob_out + '_w',
|
|
shape=[dim],
|
|
**weight_init[1]
|
|
)
|
|
bias = model.param_init_net.__getattr__(bias_init[0])(
|
|
[],
|
|
blob_out + '_b',
|
|
shape=[dim],
|
|
**bias_init[1]
|
|
)
|
|
else:
|
|
weight = core.ScopedBlobReference(
|
|
blob_out + '_w', model.param_init_net)
|
|
bias = core.ScopedBlobReference(
|
|
blob_out + '_b', model.param_init_net)
|
|
|
|
model.AddParameter(weight, ParameterTags.WEIGHT)
|
|
model.AddParameter(bias, ParameterTags.BIAS)
|
|
return op_call([blob_in, weight, bias], blob_out, **kwargs)
|
|
|
|
|
|
def elementwise_linear(model, *args, **kwargs):
|
|
return _elementwise_linear(
|
|
model, model.net.ElementwiseLinear, *args, **kwargs)
|