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Beyond Vision Adopts Innovative Safety Measures to Continue Critical Services
NIB Home » NIB-Connection » Associated Agency » Beyond Vision Adopts Innovative Safety Measures to Continue Critical Services
NIB Celebrates 82 Years August 10, 2020
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In a storied history spanning 117 years, Milwaukee-based Beyond Vision has witnessed two World Wars, the Great Depression of the 1930s, the social changes of the 1960s and 70s, and many other cataclysmic events.
The NIB associated nonprofit agency employing people who are blind or visually impaired has weathered it all. Founded in 1903, Beyond Vision provides a broad array of services from call center support to machining, assembly, and packaging, to supplying the federal government, military, and major corporations.
Coping with the global coronavirus pandemic, however, has been a special challenge.
Taking quick and decisive action to protect its employees from COVID-19 has allowed Beyond Vision to continue providing essential products to the federal government, U.S. military, and such major companies as Harley-Davidson, Caterpillar, and General Electric, among others.
"As soon as the threat posed by the coronavirus became evident, developing a clear and comprehensive response became our top priority," says President and CEO Jim Kerlin.
Kerlin and his leadership team crafted a COVID-19 Response Plan to ensure Beyond Vision follows guidelines established by the Centers for Disease Control and Prevention and the Occupational Safety and Health Administration. In addition, they benchmarked best practices from other NIB agencies.
In mid-March, when the coronavirus intensified, the organization implemented a work-from-home policy for as many positions as possible. Managers conducted daily Zoom briefings on employee safety and operations. Text messages, email, social media, and video messaging were used to keep employees updated.
"From the very beginning, we made a commitment to employee safety and well-being," says Senior Director of Relationships and Business Services Rob Buettner, who has Stargardt's Disease, which causes loss of central vision. "We made a conscious decision to trust our people and our culture, and that trust is the reason we have been able to weather this storm so far."
For employees who couldn't work from home, that commitment to safety includes several innovative approaches to maintain social distancing on the manufacturing floor, including moving workstations and splitting lunch shifts to reduce the number of staff in community areas.
In addition, personal protective equipment and masks are made available to all employees on site.
"As soon as we were able to acquire non-touch thermometers, we began doing temperature screening of all on-site employees," Buettner said.
To deal with vacancies of production team members who needed to self-isolate due to health concerns, temporary staff were hired to ensure Beyond Vision could continue to meet all customer needs.
Key to the organization's success has been its corps of dedicated and talented employees, about 60 of whom are blind, each with their own compelling story.
Among them is Sophia, who currently works in assembly and packaging, and has won praise her quality work in every position she has held. Diagnosed with retinitis pigmentosa in her twenties, she came to Beyond Vision after reading an article about the agency.
"Beyond Vision has not only provided me with a job, it has restored my dignity and given me a greater sense of self-respect," she says. "I appreciate how all of us have bonded together as a family to get through this pandemic."
Kerlin expresses pride in Sophia and everyone on his team and how well they have handled the crisis.
"It has been amazing to observe how the entire staff has grown through this experience," he says. "The leadership team and employees have stepped up from all parts of the company to be innovative. They really embody the team spirit and never-give-up-even-in-the-face-of-great-adversity attitude that's at the heart of our culture."
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\section{Introduction}
In recent years, we have witnessed the evolution of neural architectures from recurrent neural network (RNN) to long short-term memory (LSTM)~\cite{hochreiter1997long}, convolutional neural network (CNN), and transformer~\cite{vaswani2017attention}. Thanks to the increasing ability to capture contextual information due to better architectures, performance on language understanding and generation tasks has dramatically improved. Convolutional sequence model~\cite{gehring2017convolutional} and Transformer have been the most popular architectures for language representation learning.

\begin{figure}[t!]
\begin{center}
\includegraphics[width=0.8\linewidth,trim={0cm 0cm 0cm 0cm}]{Vanilla_Transformer-crop.pdf}
\end{center}
\caption{Sequential Transformer architectures have been widely adopted as encoders for many \emph{downstream} tasks. Each attention module contains one self-attention and one feed-forward network module.}
\label{Sequential}
\end{figure}

However, transformer and convolutional sequence model simply employ a sequential architecture in which information flows unidirectionally from earlier layers to later layers within the architecture,
and downstream tasks only have indirect access to early features through multiple layers
as shown in Fig.~\ref{Sequential}. We hypothesize that
earlier layers may benefit from processing information in light of the output of later layers, and that later layers may also benefit from more direct connections with earlier layers, as various layers may contain complementary information useful to down-stream tasks such as language understanding and decoding.
Introducing connections from later layers back to earlier layers is however difficult, as the directed acyclic graph structure of the models needs to be maintained in order to effectively train them and use them to perform inference.
Regarding the introduction of more direct connections from earlier layers to later layers, a naive approach %
is to use dense connections~\cite{huang2017densely} for all modules, but this results in a significant increase in model size and memory usage, making it difficult to deploy the learned model. Besides, since the dense connection increases the number of parameters, care must be taken to fairly compare performance with other models.

To solve these problems, we consider a multi-pass transformer (MPT) architecture in which the encoder stack of a transformer is repeated along a new multi-pass dimension, keeping the parameters tied, and information is allowed to proceed unidirectionally both towards deeper layers within an encoder stack and towards any layer of subsequent stacks. Subsequent stacks can thus have a chance to ``re-process'' an input in light of features obtained from later layers in a previous stack, and layers closer to the output of the stack may be more directly connected to earlier layers in the previous stack. Weights are shared between the same layers in different stacks, so that the number of parameters is not increased.

\begin{figure}[t!]
\begin{center}
\includegraphics[width=0.99\linewidth,trim={0cm 0cm 0cm 0cm}]{MPT_all_connections_outputs-crop.pdf}
\end{center}
\caption{Illustration of our proposed multi-pass transformer. The network consisting of the modules on the left side, referred to as the first-pass encoder stack or the inner stack, is copied to create a second-pass encoder stack, also referred to as the outer stack, sharing the same weights with the inner stack. The output of each layer in the inner stack is fed as input into one or more of the layers in the outer stack by adding it to their other inputs, similarly to a residual or skip connection. All possible such connections are here shown. In the soft connection case, a weight is learned for the residual connection between each layer pair. In the hard connection case, each layer can only be involved in a single residual connection, and the optimal connection pattern between inner and outer networks is found by random search. Information is propagated from top to bottom then from left to right.}
\label{Flow}
\end{figure}

The MPT architecture is illustrated in Fig.~\ref{Flow} for the case of a two-pass transformer. A single encoder stack, which can be considered as the first-pass encoder, is cloned to a second-pass encoder with identical weights, and connections between all layers of the two stacks are considered based on residual-like connections, i.e., the output of a layer in the first stack can be added to the input of a layer in the second stack. For simplicity, we will also refer to the first stack and its layers as the ``inner stack'' and ``inner layers'', and the second stack and its layers as the ``outer stack'' and ``outer layers''.
We consider two particular cases for these connections: in the soft connection case, a weighted combination of the outputs of all inner layers is added to the input of each outer layer, where the weights are learned during training together with the network parameters; in the hard connection case, the output of each inner layer is added to the input of a single outer layer, which can only receive information from that inner layer. The soft connection case adds a negligible amount of parameters to the network, while the hard connection case requires performing a discrete architecture search. We use random neural architecture search to find the best connection pattern, motivated by previous work exploring such methods to obtain a good CNN structure for image recognition~\cite{xie2019exploring} .

In this paper, we only consider modifications of the encoder part of the network, and leave the exploration of similar modifications to the decoder part to future work.

Our contribution can be summarized as follows:
\begin{itemize}[leftmargin=*]%
  \item We propose a novel multi-pass transformer which allows a transformer encoder to process an input in light of features obtained at various, including later, stages of the processing. MPT can outperform Large Transformer by reusing features from Base Transformer without increasing the number of parameters.
  \item By training for downstream tasks using either the output of the first or the second pass encoder, we simultaneously train two network architectures with different computation/performance trade-offs.
  \item We perform an extensive ablation study to validate the design of our proposed multi-pass transformer.
  \item In contrast with other architecture search methods which use recurrent controller~\cite{zoph2016neural}, complex reinforcement learning and evolution algorithm~\cite{so2019evolved}, we design a simple random architecture search on a carefully designed search space. We can outperform the Evolved Transformer that was searched by Google in a much larger search space, thus validating the effectiveness of our designed search space.

\end{itemize}

\section{Related Work}
\subsection{Neural Architecture}
Convolution neural network, recurrent neural network, long short-term memory, and transformer have been the fundamental building blocks for modern neural architectures. RNN utilizes a recurrent memory for temporal information propagation. CNN applies a learnable sliding window for local neighborhood information aggregation. Transformer utilizes fully-connected self-attention to learn pairwise information relationships. In recent years, self attention has been applied to representation learning~\cite{devlin2018bert}, vision language reasoning~\cite{Gao_2019_CVPR, Gao_2019_ICCV}, vision relationship learning~\cite{hu2018relation}, and video temporal information aggregation and reasoning~\cite{wang2018non,geng2020character,geng2020spatio}. Dense networks and residual connections~\cite{he2016deep} have been popular multi-path connection patterns for preventing the vanishing or exploding gradient problem. %
Besides residual and dense connections, Xception~\cite{chollet2017xception}, dual path~\cite{chen2017dual}, and FPN~\cite{lin2017feature} have also been quite popular. Most architectures in computer vision adopt a multi-path approach for efficient information flow. However, sequential architectures with limited information flow are typically adopted in natural language processing (NLP). The motivation for our proposed multi-pass transformer is to bring insights from the multi-path architecture design popular in computer vision to the transformer architecture originally introduced in NLP, and to go beyond the typically unidirectional multi-path architectures through a multi-pass extension.

\subsection{Neural Architecture Search}
AutoML~\cite{zoph2016neural} firstly proposed neural architecture search (NAS) to find optimal structures for image and language models. An RNN controller with a reward function is utilized to generate an optimal structure. After training 12,800 architectures on CIFAR,  state-of-the-art performance is achieved. The evolved transformer~\cite{so2019evolved} applied evolution search on a specifically designed space with a combination of self-attention and convolutional neural networks for machine translation. After searching, the evolved transformer showed that a model with a dual path consisting of convolutional neural network and self-attention can achieve better performance than a pure self-attention model. Reinforcement learning and evolutionary approaches have been widely used in many neural architecture search papers, and are believed to be better than random search. However, the randomly wired network~\cite{lin2017feature} showed that a random search on a well-designed space can outperform state-of-the-art models found by evolutionary algorithm.

\subsection{Multi-Stage Fusion in Computer Vision and Natural Language Processing}
Combination of residual and dense connections is the most popular multi-stage fusion mechanism applied in computer vision and natural language processing. Multi-stage fusion uses skip connections and multi-stage feature fusion to perform efficient information fusion of lower and deeper features. This can somewhat alleviate the vanishing or exploding gradient problem. Multi-stage fusion has been widely used as a feature pyramid in object detection. Recently, multi-stage feature fusion has also been applied to machine translation. Simple fusion mechanisms such as concatenation, addition, and recurrent fusion have been applied to fuse multi-stage features~\cite{wang2019exploiting}. However, the model cannot capture multi-stage information due to the limited capacity of such simple fusion mechanisms. Dynamic layer aggregation~\cite{dou2019dynamic} recently proposed a novel routing-by-agreement algorithm which can aggregate information from multiple layers by an expectation-maximization algorithm, achieving the state-of-the-art on machine translation.

\section{Proposed Method}
\subsection{Transformer for Machine Translation}
Transformer architectures have recently been widely used for sequence generation tasks.
The typical structure consists of encoder and decoder networks, which have deep feed-forward architectures including repeated blocks of self-attention and feed-forward layers with residual connections~\cite{he2016deep} and layer normalization~\cite{ba2016layer}.
The decoder network also features a source attention layer in each block to read the encoder's output. In this paper, we focus on modifying the encoder structure only, leaving the modification of the decoder to future work. Given a language pair, our aim is to translate a source sentence to a target sentence. The source sentence is tokenized by byte-pair encoding (BPE) and then transformed by a word embedding layer into a representation consisting of $L$ vectors of dimension $C$, where $L$ is the sentence length and $C$ the word embedding dimension. The position of each word is encoded into a position embedding space and added to the word embedding. The target sentence is similarly encoded into a word embedding representation, shifted to the right in order to force the decoder to only look at past outputs to predict the next output during training.

The continuous representation $S\in \mathbb R^{L\times C}$ of the source at the input of a self-attention module is translated via linear transforms into query, key, and value vector sequences, denoted respectively as $S^Q$, $S^K$, and $S^V$. By using an attention value between key and query, each word in the source can aggregate information from other words using self-attention. The attention outputs can be calculated as:
\begin{equation}
    \mathrm{Attention}(Q,K,V) = \mathrm{softmax}\Big(\frac{QK^T}{\sqrt{d_K}}\Big)V,
\end{equation}
where $Q$, $K$, and $V$ denote the query, key, and value vector sequences, and the attention value is modulated by the square root of the feature dimension $d_K$.
After the self-attention module aggregates information from other words, a position-wise feed-forward network layer (FFN) is used to fuse that information. Each $k$-th attention module of the transformer encoder is a combination of one self-attention layer and one FFN layer, processing the input $S^\text{in}_k$ as follows:
\begin{align}
    S^\text{mid}_k &= \mathrm{Attention}(S^{\text{in},Q}_k, S^{\text{in},K}_k, S^{\text{in},V}_k), \\
    S^\text{out}_k &= \mathrm{FFN}(S^\text{mid}_k).
\end{align}
where $S^\text{mid}_k$ stands for the intermediate feature inside the $k$-th module, and $S^\text{out}_k$ for the final output after FFN. These two notions of output features for a layer, intermediate and final, will be considered in the introduction of our proposed multi-pass transformer.
Several modules are stacked to acquire a good representation of the source sentence, and self-attention is typically implemented using multi-head attention.

The decoding stage is similar to the encoding stage, except that self-attention is performed on each target sentence's embedding representation $T$, and followed by source-attention and FFN. One layer of the decoding stage performs the following processing, where SA stands for self-attention, and $S_{N-1}$ denotes the output of the last encoder layer:
\begin{align}
    T^{\text{SA},Q} &= \mathrm{Attention}(T^Q, {T}^K, {T}^V),\\
    T^{\text{out}} &= \mathrm{FFN}(\mathrm{Attention}(T^{\text{SA},Q}, {S}^{K}_{N-1}, {S}^{V}_{N-1})).
\end{align}

We use the same word embedding transformation for the encoder and decoder. After getting the representation for the next word in the decoder, we use cross-entropy loss between the decoder word embedding and the learned representation to optimize the transformer model. We denote as $\mathcal{L}(S_{N-1},T)$ the loss computed from the output $S_{N-1}$ of the encoder, with target sequence $T$.

\subsection{Multi-Pass Transformer}
The core idea of the multi-pass transformer is feature reuse, namely feeding the output of inner layers from the first-pass encoder into the input of outer layers from a second-pass encoder. By feeding, we here mean that the output of a given inner layer is added to the original input of an outer layer without any transformation (other than potentially weighting), akin to a form of residual connection.
The first-pass and second-pass networks share parameters, and the expanded architecture thus has the same number of parameters as the base transformer architecture. Arguably the simplest connection pattern within such an architecture is that in which an output of the $k$-th attention module in the first-pass encoder is added to the input of the $k$-th attention module in the second-pass encoder. We use this setup as our default MPT architecture.
We consider in this paper two types of connections, soft and hard, which both include this simplest pattern as a particular case.

\textbf{Soft Connections:} In the soft connection case, a weighted combination of the outputs of all inner layers is added to the input of each outer layer, where the weights are learned during training together with the network parameters.
The output of the $k$-th outer layer, $\tilde{S}_k^\textrm{out}$, can be computed as
\begin{align}
\tilde{S}_k^\textrm{out} = \textrm{AttModule}\Big(\tilde{S}_{k-1}^\textrm{out} + \sum_{j=0}^{N-1} \alpha_{kj} S_j^\textrm{out}\Big),
\end{align}
where $\textrm{AttModule}(\cdot)$ denotes the attention module consisting of self-attention and feed-forward networks, $S_j^\textrm{out}$ is the output of the $j$-th inner layer,
and $\alpha_{kj}$ represents a weight for the connection from the $j$-th inner layer to the $k$-th outer layer.
We compute the connection weight via softmax as $\alpha_{kj}=\exp(w_{kj})/\sum_{j}\exp(w_{kj})$ with learnable parameters $w_{kj}$, to enforce $0 \leq \alpha_{kj} \leq 1$ and $\sum_j \alpha_{kj}=1$.
Our default architecture, with the simplest pattern mentioned above, corresponds to weights $\alpha_{kj}=\delta_{kj}$, where $\delta$ denotes the Kronecker delta.
Note that this approach adds $N^2$ parameters (with $N=6$ in our experiments) to the whole model, but this is negligible compared to the typical model size.

\textbf{Hard Connections:} In the hard connection case, we consider configurations in which the output of one layer in the first-pass encoder is added to the input of one layer in the second-pass encoder, with the constraint that no two outputs can be added to the same input. This reduces the search space to the set of permutations on $\{0,\dots,N-1\}$, where $N$ denotes the number of layers in the inner network, resulting in a search space of size $N!$, down from $N^N$ without the above constraint. We denote the $i$-th hard MPT architecture using the image $[\tau^{(i)}_0,\dots,\tau^{(i)}_N]$ of the sequence $[0,\dots,N-1]$ via the associated $i$-th permutation. In the $i$-th hard MPT architecture, the output of layer $\tau^{(i)}_k$ in the first-pass encoder is added to the input of layer $k$ in the second-pass encoder. For example, for a base transformer architecture with $N=6$ layers, the MPT model denoted as $[0,4,1,5,2,3]$  is shown in Fig.~\ref{best}. Input to outer layer $0$ comes from inner layer $0$, that of outer layer $1$ comes from inner layer $4$, that of outer layer $2$ comes from inner layer $1$, and so on. Our default architecture, with the simplest pattern mentioned above, is another example of hard MPT architecture, which is denoted as $[0,1,2,3,4,5]$.
Because hand-designed connection patterns are likely not to be optimal because of the lack of theory to predict the performance of a model based on its architecture, we adopt architecture search to find an optimal architecture in the hard MPT case, as explained in more details in Section~\ref{sec:search}.

\begin{figure}[t!]
\begin{center}
\includegraphics[width=0.90\linewidth,trim={0cm 0cm 0cm 0cm}]{MPT_Best_Searched_Pattern_with_decoder-crop.pdf}
\end{center}
\caption{Best searched model for the hard connection case with $N=6$ attention layers, $[0, 4, 1, 5, 2, 3]$.}
\label{best}
\end{figure}

\textbf{Training procedure:} Both for the soft connection architecture and each hard connection architecture, we train the model by minimizing, for an input sequence $S$ and a target sequence $T$, the objective function $\mathcal{L}(\tilde{S}_{N-1},T)$ obtained by applying the decoder to the output $\tilde{S}_{N-1}$ of the second-pass encoder. Note that we also explored optimizing the network such that the outputs of both the first-pass and second-pass encoders could be used for downstream tasks, by minimizing the sum of $\mathcal{L}(S_{N-1},T)$ and $\mathcal{L}(\tilde{S}_{N-1},T)$ or by randomly minimizing either. Performance of the second-pass encoder output remained roughly the same in all cases. This could be useful in applications where a system may need to switch between regimes with low and high computation costs (keeping the same number of parameters), in which case it could adaptively use the output of the first-pass or second-pass encoders.

\if 0
\subsection{Random Sampling Training}
\label{sec:random_sampling_training}
One advantage of our multi-pass transformer is that we can randomly sample the feature to be used for downstream task from the last layer in either the inner or outer networks at training time. In effect, we use as objective function for an input sequence $S$ either $\mathcal{L}(S_{N-1},T)$ or $\mathcal{L}(\tilde{S}_{N-1},T)$.

As a side benefit at test time, this implies that our network simultaneously contains two models suitable for downstream tasks. By computing results using the second-pass encoder, we can achieve top performance, at the cost of more computing resources (but no extra parameters). By computing results using the first-pass encoder, we can save on computing resources, at the expense of a slightly lower performance as only part of the model is used in the calculation. %
\fi

\subsection{Routing patterns between layers}
\label{sec:routing_patterns}

As can be seen in Fig.~\ref{connection}, we consider four different routing patterns to infuse features from an inner layer to an outer layer. In pattern (a), the output feature of a transformer module is added into an outer network layer before the residual connection. By connecting before the residual, the information propagates to all the following layers. In pattern (b), the feature from the inner layer is infused into the outer layer after the residual connection. By doing so, information cannot propagate as directly to the following layers. In pattern (c), instead of adding the output of the feed-forward neural network into the outer network layer, we directly feed the information after self-attention into the outer network layer before the residual connection. In pattern (d), the information after self-attention is added into the outer network layer after the residual connection. The performance of (c) and (d) is expected to be worse than that of (a) and (b), because the information after self-attention has not been fully fused yet, and the model's learning ability is thus likely to be decreased. We compare these routing patterns in Section~\ref{sec:ablation}

\begin{figure}[t]
\begin{center}
\includegraphics[width=.99\linewidth,trim={0.0cm 0cm 0.1cm 0cm}]{MPT_routing_patterns-crop.pdf}
\end{center}
\caption{Four different routing patters (a), (b), (c) and (d) depending on whether a feature from an inner layer is taken at the output or from the middle of a transformer module, and whether it is added to the input of an outer layer before or after the residual connection.}
\label{connection}
\end{figure}

\subsection{Architecture Search for Hard MPT}
\label{sec:search}
For the base transformer architecture with 6 layers shown on the left side in Fig.~\ref{best}, there are 720 associated hard MPT architectures respecting the constraint we imposed, versus 46,656 without imposing the constraint. In previous research, reinforcement learning and evolution have been applied for architecture search. Here,  we use random search for its simplicity and efficiency. A naive approach would be a random search over all architectures. However, there is only one connection swap between neighboring structures in the search space: we hypothesize that one swap will in general not significantly affect the performance. By using this prior knowledge, we perform a coarse random search, and forgo search on neighbours of structures with bad results. We instead perform fine-grained search around models with good performance.

\section{Experiment}
\subsection{Experiment Setup}
We follow the same experiment setup previously used for the Transformer~\cite{vaswani2017attention}.
We perform an ablation study on the WMT 2014 English-German (En-De) dataset, which consists of 4.5 million sentence pairs. Byte-pair encoding was applied to generate a dictionary containing 32,000 tokens. We also evaluate our models on the significantly larger WMT 2014 English-French dataset, consisting of 36 million sentence pairs.
Sentences with approximately the same length are sampled into the same batch. A single Titan RTX GPU with 24 GB of memory is used to train each base transformer model during model search architecture. By utilizing single GPU training during architecture search, we can increase the overall training speed without communication between different GPUs. Training one base transformer requires about 48 hours. With 32 GPUs running in parallel, we were able to train 224 models in two weeks. All models shared the same set of hyper-parameters. Learning rate was set to 0.0008, with 10,752 tokens in each batch with a gradient accumulation step of 8 to simulate 8-GPU parallel training. Besides, weight decay was 0 with Adam optimization whose hyperparameters were set as (0.9, 0.98). We utilized the same learning schedule as other papers by using the inverse square root. Dropout ratio was set to $0.1$ for all experiments with label smoothing $0.1$. We utilized fp16 for training acceleration. Our Base transformer contained 6 layers of self-attention modules with 512 hidden dimensions by default. During evaluation, we averaged the model parameters of the last 5 checkpoints and ran a grid search for optimal beam size and length penalty in beam search. We found that beam size of 4 and length penalty of 0.2 were the optimal setup for our searched model.

\subsection{Ablation Study}
\label{sec:ablation}

We first validate various design choices in our proposed architectures. %
We compare our results with the performance of the baseline Base Transformer architecture. This model obtained a BLEU score of 27.3 in the original paper~\cite{vaswani2017attention}, while our reimplementation obtained 27.6.

\noindent \textbf{Comparing routing patterns:}
As shown in Fig.~\ref{connection}, several routing patterns can be considered for reusing features from inner layers in outer layers.
We utilize our default MPT architecture, which corresponds to the hard MPT architecture $[0, 1, 2, 3, 4, 5]$, and test its performance on routing patterns (a), (b), (c), and (d). As we hypothesised in Section~\ref{sec:routing_patterns}, Table~\ref{tab:result_ablation} shows that infusing information before the initiation of the residual connection leads to better performance. Furthermore, feeding the information obtained after the feed-forward layer is better than the feature obtained after the self-attention layer. We hypothesize that the feed-forward layer better fuses the information aggregated from other words. For all other experiments going forward, we use routing pattern (a).

\begin{table}[t]
\centering
\resizebox{\columnwidth}{!}{
\begin{tabular}{lc}
\toprule
\textbf{Model} & \textbf{BLEU}  \\
\midrule
Base Transformer \cite{vaswani2017attention} & 27.3 %
\\
Base Transformer (our implementation) & 27.6 %
\\
\midrule
MP Transformer [0,1,2,3,4,5] & 28.1 \\
\midrule
MP Transformer [0,1,2,3,4,5](a) & 28.1\\
MP Transformer [0,1,2,3,4,5](b) & 27.8\\
MP Transformer [0,1,2,3,4,5](c) & 27.5\\
MP Transformer [0,1,2,3,4,5](d) & 27.3\\
\midrule
MP Transformer [5,2,0,4,1,3] (Worst) & 27.6\\
MP Transformer Avg.&  27.9\\
MP Transformer [0,4,1,5,2,3] (Best) & 28.4\\
MP Transformer [Soft Connections] & 28.4 \\
\bottomrule
\end{tabular}}
\caption{Ablation study of our proposed approach on WMT 14 En-De. The proposed multi-pass transformer does not increase the number of parameters with respect to the original architecture (except in the soft connection case, but only by a negligible amount). All models thus share the same number of parameters. }
\label{tab:result_ablation}
\end{table}

\noindent \textbf{Effectiveness of Random NAS for hard connections:}
As shown in Table~\ref{tab:result_ablation}, random search can generate hard MPT architectures with significant variance, which validates the effectiveness of our carefully designed search space. The performance difference between the best and worst model is 0.8 (the best model obtains 28.4 while the worst model obtains 27.6), which is large. The best model is the hard MPT architecture with connection pattern $[0, 4, 1, 5, 2, 3]$, which is illustrated in Fig.~\ref{best}. By analysing good and bad models, we notice the following factors may influence the performance. As seen from the searched network, features from deeper layer in the inner network should be added to shallow features in the outer network, which can increase the longest information path existing in the model. However, we notice that infusing the final layer of the inner network to the first layer of the outer network results in significantly deteriorated performance; we hypothesize that the existence of too long a path results in training issues due to gradient instability. Conversely, performance also seems to improve when features from shallow layers in the first network are directly linked to deeper layers in the outer network. By doing so, our multi-pass transformer has both long path and short path information flows, which may be the reason for its good performance.

\noindent \textbf{Soft connections:} Interestingly, we can see that the performance of the MPT architecture with soft connections exactly matches that of the best hard MPT architecture on the En-De dataset, with 28.4. The optimal weights obtained on the En-De and En-Fr datasets are shown in Fig.~\ref{fig:soft_weights}. We note that these optimal weights fit very well with the above analysis regarding the performance trends in the hard connection case.

\begin{figure}[t!]
\begin{center}
\includegraphics[width=0.99\linewidth,trim={0cm 0cm 0cm 0cm}]{soft_connection_weights-crop.pdf}
\end{center} %
\caption{Soft connection weights obtained on the En-De and En-Fr datasets.} %
\label{fig:soft_weights}
\end{figure}

\begin{table*}
\centering
\setlength{\tabcolsep}{5.5pt}
\sisetup{table-format=2.1,round-mode=places,round-precision=1,table-number-alignment = center,detect-weight=true,detect-inline-weight=math}
\scalebox{0.9}{
\begin{tabular}{rSSSS}
\toprule
\multicolumn{1}{c}{\textbf{Model}} & \multicolumn{2}{c}{\textbf{BLEU}}  & \multicolumn{2}{c}{\textbf{Params $\times 10^6$}} \\
\cline{2-5}
& \text{EN-DE} & \text{EN-FR} & \text{EN-DE} & \text{EN-FR} \\
\midrule
Base Transformer (BT) \cite{vaswani2017attention} & 27.30 & 38.1 & 61.2 & 111.4 \\
Large Transformer \cite{vaswani2017attention} & 28.40 & %
41.8 & 213.0 & 310.9 \\
\midrule
The Evolved Transformer (ICML 2019) \cite{so2019evolved} & 28.20 & 41.3 & 64.1 & 221.2 \\
\midrule
Sentential Context Max Pooling (ACL 2019) \cite{wang2019exploiting} & 27.58 & & 106.9 & \\
Sentential Context Attention \cite{wang2019exploiting} & 27.81 & & 107.9  \\
Deep Sentential Context RNN \cite{wang2019exploiting} & 28.33 & 40.27 & 114.3 & 114.3 \\
\midrule
Linear Combination + BT (ACL 2019) \cite{dou2019dynamic} & 27.73 & & 102.7 & \\
Dynamic Combination + BT \cite{dou2019dynamic} & 28.33 & & 113.2 & \\
Dynamic Routing + BT ~\cite{dou2019dynamic} & 28.22 & & 125.8 & \\
EM Routing + BT ~\cite{dou2019dynamic} & 28.81 & & 144.8 & \\
\midrule
MSC Base Transformer (BT)~\cite{wei2020multiscale} & 27.68 & & 73.0 & \\
\midrule
6-layer Base Transformer (BT) & 27.6 & & 61.2 & \\
6+6-layer (tied weihts) Base Transformer (BT) & 27.8 & & 61.2 & \\
12-layer Base Transformer (BT) & 28.5 & & 79.8 & \\
MP Transformer [0,4,1,5,2,3] (Proposed) & 28.40 & 41.80 & 61.2 & 111.4 \\
MP Transformer [Soft Connections] (Proposed) & 28.43 & 41.56 & 61.2 & 111.4 \\
\bottomrule
\end{tabular}
}
\caption{Comparison with other state-of-the-art methods on English WMT14 En-De and En-Fr datasets. To compare with simple deep layer structures, a fully unconstrained
12-layer BT and with a model simply concatenating two 6-layer BTs with tied weights (but without feeding the original input to the 7th layer nor allowing extra direct connections between layers 1-6 and 7-12 as we propose) were tested for En-De.}
\label{tab:result_sota}
\end{table*}

\subsection{Comparison with State of the Art}
In this section, we compare our best soft and hard connection architectures with state-of-the-art extensions of the base transformer with similar settings on both the En-De and En-Fr datasets. For the En-Fr dataset, we train the soft MPT architecture, as well as the hard MPT architecture with the best connection pattern searched on the En-De dataset. Results are reported in Table~\ref{tab:result_sota}. Interestingly, both our architectures outperform all other models while using less parameters. We also observe that the best hard connection pattern found on En-De generalizes well to En-Fr, and even outperforms the soft connection architecture on that dataset. We now give more detailed accounts regarding how each of the other models relates to our proposed models.

\noindent\textbf{The Evolved Transformer~\cite{so2019evolved}:}
The evolved transformer performs architecture search on a much larger search space than us by using an evolutionary algorithm. An extensive architecture search is performed on the size of the self-attention heads, the number of layers, different cascades between convolution and self-attention, and dense-residual fusion and  architecture search is performed jointly on the encoder and decoder. The evolved transformer involves a much larger search space than our multi-pass transformer. In the proposed hard MPT architecture, we only perform random search on a much more restricted but carefully designed search space. The soft MPT architecture does not even need architecture search, directly estimating the best continuous connection pattern. Both our architectures can achieve better performance than the evolved transformer as shown in Table ~\ref{tab:result_sota}, which validates the effectiveness of our proposed multi-pass transformer.

\noindent\textbf{Sentential Context Transformer  ~\cite{wang2019exploiting}:}
The sentential context transformer proposes to fuse features from all layers in the encoder network by a simple fusion approach like addition, recurrent fusion, concatenation, or attention. Due to the simplicity of the proposed approaches, only partial information in the features from all layers can be captured. Furthermore, operators like concatenation and recurrent neural network significantly increase the number of parameters as seen in Table~\ref{tab:result_sota}. Our proposed models can achieve much better performance than the sentential model with much fewer parameters as shown in Table ~\ref{tab:result_ablation}. %

\noindent\textbf{Dynamic Layer Aggregation (DLA)~\cite{dou2019dynamic}:}
DLA shares the same design concept with the sentential context transformer by utilizing multi-layer information fusion, but proposes a much more efficient mechanism for layer information aggregation by utilizing the expectation-maximization (EM) algorithm. The EM-based routing-by-agreement algorithm achieves significantly better performance. However, the model has almost double the number of parameters compared to our models as shown in Table~\ref{tab:result_sota}. We consider dynamic layer aggregation as an orthogonal direction with respect to our proposed MPT, and we plan to combine the two approaches in the future.

\noindent\textbf{Multiscale Collaborative Deep Models (MSC)~\cite{wei2020multiscale}:}
In order to easily optimize parameters when training very deep NMT models, MSC applied a block-scale collaboration mechanism exploiting shortcut connections propagating gradients from the lower levels of the encoder to the decoder. To enhance source representations with spatial dependencies by contextual collaboration, Gated Recurrent Units (GRUs) were applied to summarize state information from the lower encoder blocks. Although the MSC with 6 layers (base) achieves 27.68 BLEU with 73M parameters, the performance is lower than MPT's 28.4 BLEU while requiring 1.2 times larger memory than MPT's 61.2M parameters.

\section{Discussion}
Our main goal is to maximize performance without increasing memory consumption, and we show that MPT can achieve comparable performance with SOTA methods while having a much lower memory consumption.

Although much deeper models can achieve higher BLEU scores, more memory consumption is required.  Even if a 12-layer BT could achieve similar performance, MPT would still be better than such a deeper BT in terms of memory consumption as shown in Table \ref{tab:result_sota}. To compare MPT with deeper networks, a fully unconstrained 12-layer BT and with a 6+6-layer model simply concatenating two 6-layer BTs with tied weights (but without feeding the original input to the 7th layer nor allowing extra direct connections between layers 1-6 and 7-12 as we propose) were tested on EN-DE. The unconstrained 12-layer BT obtained comparable performance to our method, with 28.5 BLEU, but using twice larger memory consumption for the encoder. The concatenated 6+6 layer model with tied weights obtained 27.8 without an improvement.

The best number of passes for MPT needs to be examined.  We did evaluate a 3-pass transformer, and found it performed comparably with 2-pass on EN-DE, with 28.4 BLEU. We applied 2-pass to all experiments in the paper. MPT can be applied to other tasks such as automatic speech recognition and the best number of passes may be task-dependent.

\section{Conclusion}
We proposed a multi-pass transformer for efficient multi-stage fusion of self-attention features, %
and explored both soft and hard connection variants, using random architecture search for the latter.
Multi-pass transformer can achieve comparable performance with Large Transformer while using the same number of parameters as Base Transformer. Our proposed multi-pass architecture can also be used with other architectures such as LSTM and CNN. Future work includes testing the performance of our approach on new architectures and tasks such as language understanding. We will also explore other orthogonal research directions such as efficient multiple layer aggregation, dynamic routing, and dense connection.

redpajama_set_name: RedPajamaArXiv


Join Pip at Trika Yoga, Bristol for Deep in Autumn Yin. Ride the transition into autumn and the shorter days that greet us and we let go, just as nature does we do too on the mat.We explore the autumn energies and elements and finish with a yoga nidra.
Making the most of the luxury of time: This is the longer juicier yin practice that we yearn for whenever the weekday 75 minute class has finished feeling too short!
Leave feeling rejuvenated, balanced and grounded.


Or rather, like I did. I've stopped going now because I was exceptionally poor at forming even the simplest sentences.
Can I ask — in the case of your last novel, where did you look to find the information you needed? So where did you go to learn a bit of Russian, read oral histories, etc? How did you decide that was what you'd need to know?
For the Russian, I signed up for a local evening class. I studied Russian for two years. I didn't expect to learn it very well, but I felt ridiculous writing a novel set in Russia without knowing anything about the language. The oral histories showed up on Amazon. The book was out of print — 'Women Against the Tsar', I believe it's called — and described the lives of several women anarcho-bolsheviks in the latter part of the nineteenth century. Another source of information was the writer Roger Morris, who was in the process of writing novels set in the same period of history (though a little earlier). I spoke to him about oral histories and sent him links to some websites…which reminds me, the web was a very useful sources of information. I popped into one or two forums related to Tsarist Russian military uniforms to ask the experts questions about materials, colours, etc. I also looked on memorabilia sites for clothes that had been owned by people in the time period of interest — these were very good quality pictures with lavish descriptions including the correct terminology (sometimes in Russian as well as English), which is quite important when writing prose.
Is it ridiculous writing about Russia without speaking the language? Try writing about Russia without having set foot on Russian soil.
Feel free to check out the full interview. This is part one.


I taught her a few baby signs by the time she was about 9 months old, so she knew how to tell me when she wanted to be nursed. During the first year she was exclusively breastfed. By the second year she had a diet consisting of breast milk and toddler appropriate foods. During her second year, she breastfed less than the year before.
Unfortunately, unwanted and unwelcomed advice on when I should wean her came from everywhere. People that have never breastfed a day in their lives will offer their advice about when's the best time to wean YOUR baby. Even people that have never had a child will somehow know when you've breastfed long enough. Unbelievable!
If you resist their unsolicited advice, people may even switch from asking when you plan to wean to trying to scare you into weaning.
You'll likely hear, "If you don't wean her soon, you won't be able to do it." You may even get the, "She's going to start biting you when she gets teeth," threat. It's funny how most people accept that a baby will start to walk when he or she is ready, and talk when he or she is ready, but they think that there is a magic age when all babies should stop being breastfed.
Once threats don't manage to scare you into submission, the attempts to shame you into weaning may begin. You'll get the loaded, "You STILL breastfeeding that child? How old is she?"
child might be driving, married, or doing something else that's totally ridiculous before you wean him or her.
Things were particularly challenging because breastfeeding, especially extended breastfeeding, is not necessarily encouraged in Black families.
Like many breastfed babies, my daughter lacked the "baby bloat" that frequently occurs in formula fed babies. My well-meaning grandmother asked me dozens of times if I was sure my baby was getting enough to eat. She'd ask me, "Are you sure you're making enough milk?"
She and other members of my family refused to believe that my baby could survive on just breast milk. I was constantly guarding against my family's threats to give my daughter "real food". formula.
After breastfeeding six children of her own out of necessity, my 85-year-old grandmother seemed to view my decision to voluntarily breast feed as something out-dated or odd.
breastfeeding, may feel that moms that do are judging them for their choice.
Contrary to the warnings, weaning for me was easy. Taking natural cues from my daughter during that second year, I breast fed less and less during the day time. Breastfeeding became more of a bonding and comfort activity for us at night. When I sensed that she was ready, I began telling her that mommy wouldn't have any more milk soon. My breast naturally responded by producing less milk because of the less frequent feedings.
My daughter's nursing slowed down to a few minutes only at bed time.
Over a three day period I cut the feedings down to quick bouts, which culminated in the end of what was one of the best experiences of my life. I am glad I never succumbed to the pressure to wean before we were ready, but it bothers me that such pressure exists.
Why are we so uncomfortable with extended breastfeeding?
Tanglela Walker-Craft is the creator of Go Pillow! a patented, multipurpose childcare item that allows moms hands-free breastfeeding with comfort and president of Simply Necessary Inc. After nursing her own daughter for two years, Walker-Craft, realized that there was not a product on the market that allowed mothers to have nursing privacy and cradling comfort when others were present. Existing nursing pillows were too bulky and cumbersome for travel and cover-ups on the market required too much manipulation. The GoPillow! satisfies the needs of both breast feeding and bottle feeding mothers and caregivers.


text:
By Julie Bort
As government agencies strive to do more with limited funds, a new class of computer peripherals is gaining visibility: the multifunction device. Because they combine the features of different office machines into one piece of equipment, multifunction devices offer inherent value. But buyers need to consider the performance trade-offs these machines make when compared with stand-alone units.
A popular choice in the consumer market, multifunction devices are gaining ground in the government sector as agencies increase their support for telecommuting and seek low-cost networked peripherals.
Multifunction devices, also known as "hydras," combine several features of stand-alone office machines into an all-in-one box at a fraction of the cost of purchasing those machines individually. A typical hydra is a printer/fax machine/copier and sometimes scanner, with prices starting at $595—barely the cost of a plain-paper fax alone. Some multifunction devices offer a smaller array of functions, such as a printing/copying or faxing/copying.
Yet despite their inherent value, hydras have not yet made strides into government markets. This situation is poised for change, many government resellers and buyers say. Multifunction devices have matured, the demand for home offices and telecommuters in the government is growing, and some of these machines can now be hooked into departmental networks.
"GTSI has identified this market as an opportunity," said Tony Colangelo, director of vendor relations for Government Technology Services Inc., a reseller in Chantilly, Va. "These products are now entering their second and third generations. Everybody recognizes that they are the next wave of product category because of their price/performance. Often, success in the consumer channels means success in government markets."
Vendors say the time is ripe for government buyers to begin evaluating these offerings, which are now available on several contracts. Multifunction devices can be found on the General Services Administration's Schedule A (workstations and related products), thanks to their ability to network and their scanners; on Schedule B/C (PC products and peripherals), thanks to their printers; and on Schedule 58 (telecommunication products), thanks to their fax cards.
SOHO Market Still Soft
Hydras fall fairly neatly into two groups: those aimed at the small office/home office (SOHO) and those that can be put on a network for departmental use.
SOHO hydra machines top out at about $3,000 and can be had for as little as $595—the price of Hewlett-Packard Co.'s OfficeJet, which is the best-selling hydra in the government market. On the low end, machines such as the OfficeJet typically print, fax and copy using ink-jet technology. The OfficeJet LX also scans via the 200-dots-per-inch (dpi) fax engine and the Eclipse FaxSE software that's included.
Midrange devices are those that print/fax/copy using laser technology, such as Brother International Corp.'s 4000ML for $879. Another is the Brother 5550ML, which includes a 200-by-400 dpi scanner and a 14.4 kilobit/sec modem and lists on Schedule B/C for $1,149.
High-end SOHO products include faster, color laser printers, along with faxing, coping and optional scanning and/or a modem, such as the MV715 by Ricoh Corp. with a proposed GSA price of $3,668.
A few SOHO products offer a subset of the basic print/scan/copy features. For instance, Lumina Office Products, Sunnyvale, Calif., offers the Lumina Series 2000. This device sits between a PC and a printer and empowers the printer with fax, scanner and copier abilities. The 2000 is available on the open market for $499, but GTSI will offer it on that reseller's newly awarded Schedule 58 when that contract is finalized.
Only a few SOHO products are available on government contracts. One reason is that many agencies, particularly the military, have not bought into the telecommuting/work-at-home trend. Additionally, when an agency does purchase a hydra for a small or home office, it is more likely to do so on the open market from a superstore, where prices are fiercely competitive.
"I haven't seen in the Department of the Navy or [the Defense Department] a real push for home offices or telecommuting yet, but we are in the exploration of what that might be. We have begun pushing to supply the home," said Cmdr. Craig B. Luigart, the program manager for the Navy's Information Network Project Office.
INPO was created in February to bring the Navy's disparate information systems and local-area networks into a single, cohesive, enterprisewide system. As part of the effort, Luigart purchased a number of multifunction devices for the home offices of members of his team. He bought these devices off the open market.
"Typically, those prices at the superstores are better than what we see under contract," Luigart said.
One drawback with SOHO devices is that the performance of the individual components is less than that of stand-alone machines. For instance, many devices use ink-jet printers rather than laser printers. They can make copies but can rarely collate them, and they do not provide other sophisticated features of stand-alone copiers. If they scan, it's at the fax engine's 200-dpi image quality rather than at 300 dpi to 400 dpi. The speed of these printers is also limited, with a relatively slow six pages per minute (ppm) for monochrome documents being a common specification.
"They aren't as fast as the bigger HP printers. The HP LaserJet 5Si is 24 pages per minute. They also can't send faxes that fast—not as fast as a large [departmental] fax machine. You're not going to use an OfficeJet if you already have a big scanner or printer," said Earl Frawley, the government manager of Westwood Computer Corp., a federal reseller in Springfield, N.J.
Departmental Uses Soar
In general, agencies are interested in higher performance than the SOHO multifunction devices provide. That's why a wider selection of midrange and high-end devices are available on federal contracts. At $6,000 to $27,000, these products are intended to be networked.
Departmental hydras are based on a single-function engine that has been supplemented with add-on cards and/or software to perform other tasks. For instance, the hydra may be a fax machine that also prints or a copier that can fax.
Choosing the right device depends on which function you plan to use most often.
Several departmental multifunction products are listed on government contracts. For instance, Cannon U.S.A. Inc.'s GP30F for $7,632 is a 30 ppm copier/printer/fax machine/scanner built on a copier engine. The functions of printing, faxing and scanning are added to the networked copier via optional add-on boards. Because it's a copier at its core, the GP30F offers most of the functions of a stand-alone copier, such as sorting, reduction and enlargement.
"The GP30F can be sold as a stand-alone copier, but we don't recommend that. It can be bought with the idea of adding other functions later," said Sheppard Lake, product marketing specialist for the Cannon U.S.A.'s Government Marketing Division, Arlington, Va. "The idea with the GP30F is that you don't have to sacrifice. The only thing it can't do is print and copy at the same time."
Another product in this category is the Tektronix Inc. Phaser family of 5 ppm color/14 ppm monochrome laser printers that can also perform color copying. These devices offer top-quality color printing and simple color copying.
"The printer is designed as a stand-alone device, but you can buy an optional copy station to make it work like a color copier. It is for supplementing regular printers on the network and adding color. The printers are [among] the fastest color printers on the marketplace. When you add copier features, it does not give up any printing speed at all. But if they need a lot of color copying, they'll need to go to a high-speed copier," said Joe Murray, federal sales manager of Tektronix's Color Printing and Imaging Division, Gaithersburg, Md.
Still, these devices are at an attractive price/performance point for functions that users want but don't necessarily need, users say.
The Navy, for example, is introducing LAN users to color printing via Tektronix devices which combine color printing and color copying. "We see a cost of $40,000 to $50,000 for a color copier alone. We're giving that [function] to them for about $6,000," Luigart said. "We're hitting eight to 10 times the number of people with the level of sophistication they need."
As value continues to be the government buyer's top priority, multifunction devices will unquestionably be looked at more closely. They give workers the basic capabilities they need at an affordable price.
Bort is a free-lance writer based in Westminster, Colo.


text:
Q: Cypher Query for all nodes that have shared relationships to the 2 or more sub-nodes? Created a GraphGist to help explain my issue:
https://gist.github.com/bconneen/e5c66e26883958c81ae6fc5c607fdfa9
Consider the following Neo4J model:
Applicant(firstName, lastName, uniqueId)
Phone(number)
IpAddress(ip)
BankAccount(routing,account)

Applicant--has->Phone,
Applicant--has->IpAddress,
Applicant--has-->BankAccount

All nodes are created using merge.  So if we process 100,000 applications relationships will be created where occasionally more than 1 Applicant shares one or more of Phone, IpAddress, BankAccount.
I want the nodes returned to be when 2 or more Applicants share 2 or more Phone, IpAddress or BankAccount. I want to write a query that returns All Applicants and their shared relationships. That meet the criteria.
Example:
Applicant(John Smith) has Phone (555-555-5555), has ipAddress (127.0.0.1), has BankAccount (ABCDEF)
Applicant(Jane Doe) has Phone(222-222-2222, has ipAddress (127.0.0.1), has BankAccount (ABCDEF)
Applicant(Steve Zahn) has Phone(555-555-5555), has ipAddress(127.2.2.2), has BankAccount(GHJKD)
Applicant(James Clay) has Phone(444-444-4444), has ipAddress(129.3.3.3), has BankAccount(ZYXWVU)
Query for All Applicants that share 2 or more Phone, IpAddress or Bank:
Applicant(John Smith) has Phone (555-555-5555), has ipAddress (127.0.0.1), has BankAccount (ABCDEF)
Applicant(Jane Doe) has Phone(222-222-2222, has ipAddress (127.0.0.1), has BankAccount (ABCDEF)
Query for All Applicants that share 1 or more Phone, IpAddress or Bank:
Applicant(John Smith) has Phone (555-555-5555), has ipAddress (127.0.0.1), has BankAccount (ABCDEF)
Applicant(Jane Doe) has Phone(222-222-2222, has ipAddress (127.0.0.1), has BankAccount (ABCDEF)
Applicant(Steve Zahn) has Phone(555-555-5555), has ipAddress(127.2.2.2), has BankAccount(GHJKD)

A: Using the data from your gist:
Query for all applicants that share 2 or more phone, ipaddress or bank
MATCH (applicant:Applicant)-[r]->(subelement)<-[r2]-(other:Applicant)
WITH applicant, other, collect(subelement) AS overlap
WHERE id(applicant) > id(other) AND size(overlap) > 1
RETURN applicant, other, overlap

redpajama_set_name: RedPajamaStackExchange


text:
Q: JNI API call resulting in JNI_EVERSION error I am having troubles getting the Java Native Interface (JNI) running on my OS. My minimal working example (derived from here and adjusted for my system) returns a version error, JNI_EVERSION (-3), upon calling JNI_CreateJavaVM(). My c-file looks like
// hello_world.c
#include <stdio.h>
#include <jni.h>

JNIEnv *create_vm(JavaVM **jvm)
{
  JNIEnv* env;
  JavaVMInitArgs args;
  JavaVMOption options;
  args.version = JNI_VERSION_1_8;
  args.nOptions = 1;
  options.optionString = "-Djava.class.path=./";
  args.options = &options;
  args.ignoreUnrecognized = 0;
  int rv;
  rv = JNI_CreateJavaVM(jvm, (void**)&env, &args);
  if (rv < 0 || !env)
      printf("Unable to Launch JVM %d\n",rv);
  else
      printf("Launched JVM! :)\n");
  return env;
}

int main(int argc, char *argv[])
{
  JavaVM *jvm;
  JNIEnv *env;
  env = create_vm(&jvm);
  return 0;
}

and my Makefile like
all: run

helloWorld.class: helloWorld.java
    /usr/bin/javac helloWorld.java

hello_world: hello_world.c
    gcc -o hello_world \
    -L /usr/lib/jvm/java-8-openjdk-amd64/jre/lib/amd64/server/ \
    -ljvm \
    -I /usr/lib/jvm/java-8-openjdk-amd64/include/ \
    -I /usr/lib/jvm/java-8-openjdk-amd64/include/linux/ \
    hello_world.c

run: helloWorld.class hello_world
    export LD_LIBRARY_PATH="/usr/lib/jvm/java-8-openjdk-amd64/jre/lib/amd64/server/"
    ./hello_world

clean:
    rm -f helloWorld.class hello_world

The resulting output from make is
/usr/bin/javac helloWorld.java
gcc -o hello_world \
-L /usr/lib/jvm/java-8-openjdk-amd64/jre/lib/amd64/server/ \
-ljvm \
-I /usr/lib/jvm/java-8-openjdk-amd64/include/ \
-I /usr/lib/jvm/java-8-openjdk-amd64/include/linux/ \
hello_world.c
export LD_LIBRARY_PATH="/usr/lib/jvm/java-8-openjdk-amd64/jre/lib/amd64/server/"
./hello_world
./hello_world: /usr/lib/jvm/java-1.5.0-gcj-6-amd64/lib/libjvm.so: no version information available (required by ./hello_world)
Unable to Launch JVM -3

The message "Unable to Launch JVM -3" is the program output with the JNI_EVERSION error. I think the line /usr/lib/jvm/java-1.5.0-gcj-6-amd64/lib/libjvm.so: no version information available (required by ./hello_world) gives a hint to the problem, but I do not really understand this issue and when I look into the shared object with readelf -h /usr/lib/jvm/java-1.5.0-gcj-6-amd64/lib/libjvm.so it features a line
 Version:                           1 (current)

A: I finally was able to get it running. Even though I don't know why, the export LD_LIBRARY_PATH command in the Makefile apparently didn't do its job. Upon checking the content of LD_LIBRARY_PATH on the command line I noticed that it contains
/usr/lib/jvm/java-1.5.0-gcj-6-amd64/lib

After setting
LD_LIBRARY_PATH="/usr/lib/jvm/java-8-openjdk-amd64/jre/lib/amd64/server/"

and rerunning make, I was able to launch the JVM


Visiting the site gives you an airy and smile-worthy feeling, it is warm and inviting. The third time this was about to happen, Theseus convinced his father to send him along as one of them. As everybody knows, the Athenian prince killed the Bull-Man (Bull being the symbol of Crete) and Athens set on her way to gradually becoming the new thalassocrat Greek state. Even spiders have been tested with the effects of drugs. Below are want happens to the spider in how they make their spider webs when on drugs. Just as the name implies, this clutch carries emergency supplies. Made with a potholder and zip lock bags, every gal should have one. See how easy this clutch is to make by going to Eighteen25 for the directions. Healthy eating is a habit so does taking care of your face as well. What we eat reflects on our body. So does our skin reflect, how we care about it. Using natural and organic products makes your skin look healthy and fresh than chemical based products. You can buy cheap knit hats at most discount stores such as Family Dollar, Big Lots, and Dollar General. The ones in the photo were at Dollar Tree for just one dollar each. Thanks for the whack on the side of the noggin. Our church can use a number of these that have been underutilized before. I can even see combinations of some, such as entertainment sales at the flea market baazar. Great lens, even better this time around! The fifth anniversary marks a special milestone for couples. After five years, the couple is no longer considered newlywed. Tradition says that couples give each other gifts made of wood on to mark their five years of marriage. Some couples who adhere to this tradition often give each other wood gifts such as a wooden clock, a music box, or a wood picture frame with a photo of the couple together.
There's no benefit to using the same stock images that have been copied and pasted all over the interwebs. Creating your own gets a boost. You can also brand the images with a name or website, as in many of the images above. Nobody grows old merely by living a number of years. We grow old by deserting our ideals. I showered under stinging chilly water released by the toilet handle and changed my clothes. By observation, I had learned the dirty clothes were absorbed quickly into the floor. I'd also gotten the hang of dressing in the weird material while slightly damp. After writhing into my Jell- jammies I tried to climb into bed. I had a sinking feeling I would have to take my damned clothes off to get into the freaking thing so I shucked the garment off when nothing happened. Grocery Rewards: Check with your local supermarket for grocery rewards that are paid to your school in supplies or other forms of rewards. This is a great way to 'double dip' with grocery label programs like Box Tops and Labels for Education rewards. Planned gifts to Lawrenceville include bequests, life-income arrangements, and other deferred gifts. Making a planned gift to Lawrenceville qualifies you for membership in the John Cleve Green Society. The mirror was shaped like the mirror in my apartment's bathroom and it reflected things. The resemblance ended there; the lens of the Hubble Telescope isn't half as well polished. My fingers didn't even leave prints when I touched it and its warm surface rumbled softly with a vibration like the faraway purr of a giant cat.
There are two ways to earn money as a Thirty-One Consultant: sales and leadership. Sales is obviously required in order to be a consultant, but leadership is optional for those who are interested in earning even more while mentoring others. They have made some changes/improvements and their traffic has doubled in the last 3 weeks. Twenty five years, where did the time go? Kids, jobs, the rat race. That kind of commitment deserves a thoughtful present. Hi, Jennifer! Glad you like the ideas here – and I hope you find just the right gifts for everyone on your list this year! Very Interesting. We've always had a pack of Tarot cards lying around at home and for some reason they seem to fascinate everybody. Nice to know you're keen on the fraudsters. Good tips and advice. Christmas has become excessively commercial which can take the fun out of it a bit. Simple or homemade gifts are often the best. Wrist watches make fantastic gifts because a good quality watch will last a lifetime and the birthday boy/girl will remember who gave it to them each time they look at it. Chocolate gifts from mousepads, diamond ring, candy, vases, sheets and more. Women love chocolate. Even the sight of chocolate will put a smile on her face. Collectors: Do some research to find out what is missing from his collection and see if you can locate a good find to add to it. Give him a book on the topic (some of these are very expensive and are used as major sources for research and appraising collectors' items). Buy tickets and a weekend trip for a convention of collectors in his field.
Their home delivery makes sure that the gifts reach the given address on the given date and time. By sending flowers to Hyderabad or cakes to Hyderabad you can have 100% satisfaction for delivery. The websites for cakes and gifts is very easy to browse. Now you can celebrate warm wishes with your loved ones happily. Customers can now look through and place online order to send cakes to Hyderabad, flowers to Hyderabad or gifts to Hyderabad. I have always had a love of making gift baskets whether it be for a friend or family member or even a teacher! I felt it was a way to give them a gift that reflects their personal style and let's them know how truly special they are to you. Nice lens but I don't think you could do this with Australian bank notes as they are all plastic. I truly enjoed you site. Wonderful, heartfelt sentiments. Thank you for sharing! niceeee….very impressed. i don't know there is another use of money. innovative! In this fast moving world, the traditional process of delivering the gift through some courier or speed post is a time-consuming and tedious too. What do you give the person that has everything? You give him or her an experience: a river-rafting trip, a hot-air balloon ride, lessons in rock climbing or Thai cooking, a wildflower tour, driving a Lamborghini, a ride on a harbor tour boat, a whale-watching cruise, a Sierra Club week-long hike, a fishing trip. Many children adore museums, which are much more child-friendly (and more expensive) than the museums of yesteryear; their parents may be able to put a family membership card for a museum or zoo to good use.
Christmas is definitely one of our favourite times here at Everything But Flowers; which is why we select our Christmas gifts range each year to ensure that we cover every possible friend or family member you're looking to buy gifts for. If we can't find a gift in our online store for a friend or family member; we know you won't be able to either; which is why we make sure there's a gift idea for everyone we know so we know your gift ideas will all be here available for sale and delivery direct to the door of people you care about. Christmas gifts are some of the most fun to buy throughout the year; just take a look at our amazing range; we're sure you'll be impressed. Hi Riley, I get the feeling that a lot of her trouble is psychology. For some reason she feels guilty for taking money, yet she wants to do the readings. A part of her mind is yelling, 'Are you faking it? Is this real? What she needs to do is sit down and give it a rest for a while, sort out her health, and most important don't do readings just for the money. For two reasons. one you are so desperate for the money you may read the palms wrong, and secondly she will feel guilty and then ill. round and round we go! to read palms, tarot etc you have to be relaxed. concentrate on the person what you are feeling etc, and never feel guilty for being paid! why should she do it for nothing? me confident and say 10 dollars/pounds and then as she gets more experienced put the money up! tell her good luck! eBay is another popular alternative to Amazon that offers a wealth of products from a large range of sellers.


text:
Bad Blood Review
Xavier Samuel
Stop me if you've heard this one before. A crime writer (Xavier Samuel) is stalked by an unknown figure. He has a dark secret that he's keeping from his fiancé, one that if it were let out his world would be shaken to its core. His previous book, Die Softly, is based on the murder of his wife. There's a possibility that a long lost sibling may be involved. If it all sounds wannabe Stephen King, then that's too high praise for Bad Blood.
Written and directed by David Pulbrook (Last Dance), and based on a story by Patrick Edgeworth, one can't help ask the question – why? What point is there to tell this story? The core concept of a writer who is challenged by his work, and is in turn, threatened by a possible fan, is one that has been dragged through cinematic mud at a tiring frequency. Every tenth Stephen King story tells the story of a writer troubled by something, and Bad Blood feels like the worst elements of every one of those stories thrown into a blender, with the remaining good parts sifted out, leaving chunks of clunky dialogue and wet wads of what appear to be 'characters'.
Xavier Samuel has regularly felt like he's an actor on the cusp of doing something great. Where he was effective in The Loved Ones, he was outshone by Robin McLeavy. Where he could have had his own comedy hit with A Few Good Men, he instead was unfortunately in a tired, unwelcome outdated laugh-free event. It seems only Whit Stillman has been able to help Samuel deliver a performance of worth in Love & Friendship. Here, Samuel regularly looks tired and exhausted, reading his lines like a high school student relegated to doing drama just to make up the credits. Is there more to Xavier Samuel than this? I hope so.
Morgan Griffin plays Carrie, fiancé to Xavier Samuel's Vincent, and fortunately for Griffin she manages to walk away from this with some kind of integrity. Granted, she is given little of consequence to do. Other supporting actors will do well to leave this effort off their show reel.
This is a somnambulistic, turgid event of a film where pivotal plot points occur with as much energy as a tired, pointless analogy. Yes, this is a film that lacks a budget, but as many other Australian films have shown, a lack of a budget does not have to restrict the artistic desires of the director. Made with the support of the South Australian Film Corporation, Bad Blood should be better than it is. As an advertisement for the South Australian film industry, this is a poor one.
Thrillers should thrill, or at least give the impression that they have the idea of 'thrilling' an audience on their mind. Here, the thrills are non-existent, and the plot twists so obviously sign posted in advance that when they do arrive you can't help but say 'duh'. Even though Bad Blood draws from a deep pool of Stephen King lore, it lacks an ounce of the personality within those texts. For a film to meet a basic level of quality, it needs to hit a few points – characters that feel like they have a heartbeat, a story that feels like it has a purpose, and direction that feels like it has something to say. When a film fails to hit any of these marks, you can't help but wish they'd not tried at all.
Andrew F Peirce· April 15, 2019 ·4 min read
Missing Link Review – A Weak Entry in Laika Studios Filmography
Director: David Pulbrook
Cast: Xavier Samuel, Morgan Griffin, Tessa Fowler
Writer: David Pulbrook, based on a story by Patrick Edgeworth
australian cinemaaustralian filmBad BloodDavid PulbrookDramaMorgan GriffinReviewThrillerXavier Samuel
Glass Review
Judy & Punch Review – A Proudly Feminist Film About Insidious Violence
Saint Frances Review – A Proudly Feminist, Eagerly Sweet Millennial Coming-of-Age Film
Island of the Hungry Ghosts – Adelaide Film Festival Review
Previous Top 100 Mondo Posters – Part Six – 50-41
Next Top 100 Mondo Posters – Part Seven – 40-31
Charlie Says Review – A Muddied Character Study that Feels Incomplete


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redpajama_set_name: RedPajamaGithub


Sam Rodriguez is the President of the National Hispanic Christian Leadership Conference, the world's largest Hispanic Christian organization serving as a representative voice for the more than 100 million Hispanic Evangelicals assembled in over 40,118 U.S. churches and over 450,000 churches spread throughout the Spanish-speaking diaspora.
– What's the biggest challenge pastors face today?
– How are churches embracing the hope in Christ?


- Putin, who denies that Russia interfered in the 2016 election, or US intelligence agencies, which have concluded that Russian agents hacked into the Democratic National Committee computer server and released hacked DNC emails to help Trump's election chances. "The evidence is overwhelming and the president needs to say that and act like it".
He also said he merely wanted to know what agreements Trump and Putin supposedly reached over the course of their two-hour sit-down.
Trump's own director of national intelligence, Dan Coats, said during the Aspen Security Forum on Thursday that he didn't "know what happened in that meeting".
There was a significant danger that left to his own devices, he might have been persuaded by President Putin to do the same in the Baltic states and Poland, which would have provoked an immediate crisis between the United States and its North Atlantic Treaty Organisation allies.
"And instead, the president did not show the strength that an American president, I believe, should have shown at that moment", Menendez said. Any expression of concern about Russian interference seems, in President Trump's mind, to delegitimize his electoral victory, and consequently his presidency.
Contrasting Putin's background as a former KGB agent who uses "penny-ante spy tactics" with Trump's as a former businessman, Bossert said, "We spend our time trying to have productive meetings with foreign leaders".
"You didn't collude with the Russians, or at least I haven't seen any evidence, but Mr. President, they meddled in the elections".
Trump on Wednesday again reignited the controversy when he replied "no" when asked if Russian Federation is still targeting the United States, directly contradicting the current Director of National Intelligence Dan Coats.
Mr Coats has been under scrutiny since he said he wished Mr Trump had not met one-on-one with the Russian leader and expressed dismay that the president had publicly undermined U.S. intelligence agencies.
While some prominent Republicans in Congress this week pushed back on Trump or criticized Russian President Vladimir Putin, not Barletta. "It's offensive, and it doesn't frankly reflect well on President Trump", Rice said. On both questions, those who say they "strongly disapprove" of Trump's performance outnumber those who say they "strongly approve" by better than 2 to 1. I don't mind him dealing with Russian Federation, I just want to deal with Russian Federation from a position of strength.
Trump's public doubting of Russia's culpability for interference in 2016 - though he tried to "clarify" his remarks a day later - sparked bipartisan condemnation in Washington and sparked congressional lawmakers to look once again for ways to tighten sanctions on the longtime US foe. Chris Van Hollen to address election security and Russian Federation that recently picked up some additional support in the Senate as lawmakers continue to warn of future attempts by Moscow to interfere in USA elections. Marco Rubio of Florida, said on CNN's "State of the Union" that he believed the warrants to monitor Page were justified. But this is unlikely to lead to any major change in how he approaches either Trump personally or the relationship with the United States overall.
That contradicted the views of United States intelligence agencies so more clarifications had to follow . Marco Rubio and Chris Van Hollen will hold Russian Federation accountable for election meddling.
He broke that down to "two or three separate trade wars" and said "none of it is good for trade". China could retaliate in unconventional ways that could stump the U.S., Mr. deLisle pointed out.
A separate 10 percent would be invested into tourism projects on Ulleungdo Island, including a museum centered around the ship. But the divers have insisted they keep up to half of the treasure haul and give the other half to Russian Federation .


text:
Sella group
Title: Sella group
Subject: Alta Badia, Gardena Pass, Pordoi Pass, Maratona dles Dolomites, Ladin language
Corvara in Badia and the Sella group
The Sella group (German: Sellagruppe, Ladin: Mëisules or L Sela) is a plateau-shaped massif in the Dolomites mountains of northern Italy. The Sella lies north of the Marmolada and to the east of the Langkofel. The highest peak is Piz Boè at 3,151 m (10,338 ft) above sea level.
The Sella lies between the four Ladin valleys of Badia, Gherdëina, Fascia, and Fodom and is divided between the provinces of South Tyrol, Trentino and Belluno. It can be driven around by car crossing the Campolongo Pass, Pordoi Pass, Sella Pass, and Gardena Pass. In winter it is possible to ski around the entire massif by using the Sella Ronda ski lift carousel. Also each winter the alpine touring ski Sellaronda Skimarathon race is held, which leads around the entire Sella and covers 42 km of mountain trails. The same trails can be mastered by Mountain bike during the summer.
Other peaks in the massif are the Cima Pisciadù 2,985 m (9,793 ft), the Boèseekofel 2,910 m (9,550 ft), the four Sellatürme 2,696 m (8,845 ft) and Sass Pordoi 2,952 m (9,685 ft), whose summit can be reached by funicular from Pordoi Pass. During winter the summit is the starting point for many alpine ski tours, of which the most famous are the descent through the Val Mesdì and the descent from the Pordoischarte.
Sella group in the evening
The Sella group seen from Sella Pass
The Sella group seen from Val Gardena
Each year the course of the annual single-day seven mountain passes crossing Maratona dles Dolomites Bicycle Race goes around the Sella group.
360-degree panorama of the Sella Group, Marmolada and Fedaia lake
360-degree panorama of the Sella Group from Cima Rocca
Commons category without a link on Wikidata
Mountain ranges of the Alps
Trentino-Alto Adige/Südtirol geography stubs
Veneto geography stubs
Ladin language
Rhaeto-Romance languages, Spanish language, South Tyrol, Trentino, Italian language
Trentino-Alto Adige/Südtirol, Italy, Bolzano, Sëlva, Merano
Google Books, Trentino-Alto Adige/Südtirol, Trento, Malè, Italy
Italy, FIS Alpine Ski World Cup, Corvara, South Tyrol, Sella group, South Tyrol
Gardena Pass
Italy, South Tyrol, Sëlva, Sella group, Pizes de Cir
Pordoi Pass
Italy, Dolomites, Alps, Sella group, Fausto Coppi


text:
Özgür Gündem main trial held in Istanbul
Human Rights Association co-chair Eren Keskin, who is tried in the main trial of Özgür Gündem newspaper, said that she would not make any further statement as she did not believe that there would be an objective trial.
Thursday, 24 Dec 2020, 15:15
The third hearing in the main trial of Özgür Gündem newspaper, which was closed down through a governmental decree (KHK), was held in Istanbul on Thursday. Human Rights Association (IHD) co-chair Eren Keskin and journalist İnan Kızılkaya, who are accused of "violating the unity and the integrity of the state", being a "member of a terrorist organization" and spreading "terrorist propaganda" were present as journalists Kemal Sancılı and Zana (Bilir) Kaya did not attend the hearing.
'NO OBJECTIVE TRIAL'
Keskin, who is standing trial for her participation in the chief-editor-on-duty campaign in solidarity with Turkey's most oppressed Özgur Gündem newspaper, stated that the conditions of the charges are not justified in the file. She said she would not make any further statements because she did not believe that there would be an objective trial.
İnan Kızılkaya denied the accusations and demanded acquittal, defending that his activities should be evaluated within the scope of freedom of press and expression.
The defense lawyers said that the application made to the Constitutional Court (AYM) regarding the closure of the newspaper in 2016 is at the decision stage and demanded the court to wait for it.
TRIAL POSTPONED
After the defence, the court decided to evaluate the lawyers' request and allow a member of the court to examine the file and adjourned the hearing to 15 February.
Explosion kills 8 soldiers and a civilian in Shengal


Create a luscious lawn with Bradfords. Choose from a range of artificial grass styles, for commercial and domestic use, or grow your own with our lawn seeds. Find everything you need to complete the project from start to finish!


text:
Q: Using a user-uploaded document to add contect in ElasticSearch? I was wondering whether there is a way I can feed additional text (from a document) to get more accurate results?
For example, a user can upload a PDF that contains text that s/he thinks is relevant to the search. Then use something like TF-IDF to extract important words and feed them to something like a should query along with the actual query in a must query. Has anyone tried something like this? Has it worked? Any better way to achieve this?
I believe it can be done with the More Like This query, but not sure how.


text:
(3833) Калингаста () — медленно вращающийся астероид, относящийся к группе астероидов, пересекающих орбиту Марса. Он был открыт 27 сентября 1971 года американскими астрономами Джеймсом Гибсоном и Карлосом Сеско в обсерватории Эль-Леонсито и назван в честь аргентинского департамента Калингаста, на территории которого расположена обсерватория.

См. также
 Список астероидов (3801—3900)
 Классификации малых планет

Примечания

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redpajama_set_name: RedPajamaWikipedia