FM / layers

/usr/local/lib64/python3.6/site-packages/caffe2/python/layers/

/usr/local/lib64/python3.6/site-packages/caffe2/python/layers

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
adaptive_weight.py	5687	0644	edit dl rm
add_bias.py	1396	0644	edit dl rm
arc_cosine_feature_map.py	7345	0644	edit dl rm
batch_huber_loss.py	3523	0644	edit dl rm
batch_lr_loss.py	11577	0644	edit dl rm
batch_mse_loss.py	2333	0644	edit dl rm
batch_normalization.py	3823	0644	edit dl rm
batch_sigmoid_cross_entropy_loss.py	1483	0644	edit dl rm
batch_softmax_loss.py	4580	0644	edit dl rm
blob_weighted_sum.py	2219	0644	edit dl rm
bpr_loss.py	1499	0644	edit dl rm
bucket_weighted.py	2355	0644	edit dl rm
build_index.py	1937	0644	edit dl rm
concat.py	4849	0644	edit dl rm
constant_weight.py	1208	0644	edit dl rm
conv.py	5050	0644	edit dl rm
dropout.py	1410	0644	edit dl rm
fc.py	9296	0644	edit dl rm
fc_without_bias.py	1954	0644	edit dl rm
fc_with_bootstrap.py	12788	0644	edit dl rm
feature_sparse_to_dense.py	14361	0644	edit dl rm
functional.py	4875	0644	edit dl rm
gather_record.py	3260	0644	edit dl rm
homotopy_weight.py	4306	0644	edit dl rm
label_smooth.py	3507	0644	edit dl rm
last_n_window_collector.py	2392	0644	edit dl rm
layers.py	17412	0644	edit dl rm
layer_normalization.py	4291	0644	edit dl rm
margin_rank_loss.py	1951	0644	edit dl rm
merge_id_lists.py	1500	0644	edit dl rm
pairwise_similarity.py	3549	0644	edit dl rm
position_weighted.py	2066	0644	edit dl rm
random_fourier_features.py	3187	0644	edit dl rm
reservoir_sampling.py	3013	0644	edit dl rm
sampling_train.py	2210	0644	edit dl rm
sampling_trainable_mixin.py	1366	0644	edit dl rm
select_record_by_context.py	2381	0644	edit dl rm
semi_random_features.py	5809	0644	edit dl rm
sparse_dropout_with_replacement.py	3943	0644	edit dl rm
sparse_feature_hash.py	4618	0644	edit dl rm
sparse_itemwise_dropout_with_replacement.py	3944	0644	edit dl rm
sparse_lookup.py	22170	0644	edit dl rm
split.py	2257	0644	edit dl rm
tags.py	4114	0644	edit dl rm
uniform_sampling.py	2779	0644	edit dl rm
__init__.py	943	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/caffe2/python/layers/bpr_loss.py (1499B)

## @package bpr_loss
# Module caffe2.python.layers.bpr_loss

from caffe2.python import schema
from caffe2.python.layers.layers import (
    ModelLayer,
)
from caffe2.python.layers.tags import (
    Tags
)
import numpy as np

# ref: https://arxiv.org/pdf/1205.2618.pdf
class BPRLoss(ModelLayer):

def __init__(self, model, input_record, name='bpr_loss', **kwargs):
        super(BPRLoss, self).__init__(model, name, input_record, **kwargs)
        assert schema.is_schema_subset(
            schema.Struct(
                ('pos_prediction', schema.Scalar()),
                ('neg_prediction', schema.List(np.float32)),
            ),
            input_record
        )
        self.tags.update([Tags.EXCLUDE_FROM_PREDICTION])
        self.output_schema = schema.Scalar(
            np.float32,
            self.get_next_blob_reference('output'))

def add_ops(self, net):
        # formula:
        # loss = - SUM(Ln(Sigmoid(Simlarity(u, pos) - Simlarity(u, neg))))
        neg_score = self.input_record.neg_prediction['values']()

pos_score = net.LengthsTile(
            [
                self.input_record.pos_prediction(),
                self.input_record.neg_prediction['lengths']()
            ],
            net.NextScopedBlob('pos_score_repeated')
        )
        # https://www.tensorflow.org/api_docs/python/tf/math/log_sigmoid
        softplus = net.Softplus([net.Sub([neg_score, pos_score])])
        net.ReduceFrontSum(softplus, self.output_schema.field_blobs())

## @package bpr_loss # Module caffe2.python.layers.bpr_loss from caffe2.python import schema from caffe2.python.layers.layers import ( ModelLayer, ) from caffe2.python.layers.tags import ( Tags ) import numpy as np # ref: https://arxiv.org/pdf/1205.2618.pdf class BPRLoss(ModelLayer): def __init__(self, model, input_record, name='bpr_loss', **kwargs): super(BPRLoss, self).__init__(model, name, input_record, **kwargs) assert schema.is_schema_subset( schema.Struct( ('pos_prediction', schema.Scalar()), ('neg_prediction', schema.List(np.float32)), ), input_record ) self.tags.update([Tags.EXCLUDE_FROM_PREDICTION]) self.output_schema = schema.Scalar( np.float32, self.get_next_blob_reference('output')) def add_ops(self, net): # formula: # loss = - SUM(Ln(Sigmoid(Simlarity(u, pos) - Simlarity(u, neg)))) neg_score = self.input_record.neg_prediction['values']() pos_score = net.LengthsTile( [ self.input_record.pos_prediction(), self.input_record.neg_prediction['lengths']() ], net.NextScopedBlob('pos_score_repeated') ) # https://www.tensorflow.org/api_docs/python/tf/math/log_sigmoid softplus = net.Softplus([net.Sub([neg_score, pos_score])]) net.ReduceFrontSum(softplus, self.output_schema.field_blobs())