rust-bert 0.7.2

Ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
Documentation 
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// Copyright 2019 Guillaume Becquin
// 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.

use tch::nn::ModuleT;
use tch::Tensor;

#[derive(Debug)]
pub struct Dropout {
    dropout_prob: f64,
}

impl Dropout {
    pub fn new(p: f64) -> Dropout {
        Dropout { dropout_prob: p }
    }
}

impl ModuleT for Dropout {
    fn forward_t(&self, input: &Tensor, train: bool) -> Tensor {
        input.dropout(self.dropout_prob, train)
    }
}