TODO: Batching should be implemented at the renderer level, not inside the reconciler.
439897
function batchedUpdates(fn, a) {
    var previousIsBatchingUpdates = isBatchingUpdates;
    isBatchingUpdates = true;
    try {
      return fn(a);
    } finally {
      isBatchingUpdates = previousIsBatchingUpdates;
      if (!isBatchingUpdates && !isRendering) {
        performSyncWork();
      }
    }
  }
54614
function (nodes, batchOps, done) {
      self.db.batch(batchOps, function (err) {
        if (err) {
          nodes.forEach(rejectNode)
          return done(err)
        }
        done(null, nodes)
      })
    }
967881
def batching(size):
    """"""

    if size < 1:
        raise ValueError("batching() size must be at least 1")

    def batching_transducer(reducer):
        return Batching(reducer, size)

    return batching_transducer
469535
def _batchify(self, batch_data, batch_label, start=0):
        """"""
        i = start
        batch_size = self.batch_size
        try:
            while i < batch_size:
                label, s = self.next_sample()
                data = self.imdecode(s)
                try:
                    self.check_valid_image([data])
                    label = self._parse_label(label)
                    data, label = self.augmentation_transform(data, label)
                    self._check_valid_label(label)
                except RuntimeError as e:
                    logging.debug('Invalid image, skipping:  %s', str(e))
                    continue
                for datum in [data]:
                    assert i < batch_size, 'Batch size must be multiples of augmenter output length'
                    batch_data[i] = self.postprocess_data(datum)
                    num_object = label.shape[0]
                    batch_label[i][0:num_object] = nd.array(label)
                    if num_object < batch_label[i].shape[0]:
                        batch_label[i][num_object:] = -1
                    i += 1
        except StopIteration:
            if not i:
                raise StopIteration

        return i
685477
function executeBatch(bulkOperation, batch, options, callback) {
  function resultHandler(err, result) {
    // Error is a driver related error not a bulk op error, terminate
    if (((err && err.driver) || (err && err.message)) && !(err instanceof MongoWriteConcernError)) {
      return handleCallback(callback, err);
    }

    // If we have and error
    if (err) err.ok = 0;
    if (err instanceof MongoWriteConcernError) {
      return handleMongoWriteConcernError(batch, bulkOperation.s.bulkResult, false, err, callback);
    }
    handleCallback(
      callback,
      null,
      mergeBatchResults(false, batch, bulkOperation.s.bulkResult, err, result)
    );
  }

  bulkOperation.finalOptionsHandler({ options, batch, resultHandler }, callback);
}
1247166
function (renderer) {

        var _gl = renderer.gl;
        var cache = this._cache;

        cache.use(renderer.__uid__);

        var renderBuffer = cache.get(KEY_RENDERBUFFER);
        if (renderBuffer) {
            _gl.deleteRenderbuffer(renderBuffer);
        }
        var frameBuffer = cache.get(KEY_FRAMEBUFFER);
        if (frameBuffer) {
            _gl.deleteFramebuffer(frameBuffer);
        }
        cache.deleteContext(renderer.__uid__);

        // Clear cache for reusing
        this._textures = {};

    }
716211
public BatchCSVRecord transform(BatchCSVRecord batch) {
        BatchCSVRecord batchCSVRecord = new BatchCSVRecord();
        List<List<Writable>> converted =  execute(toArrowWritables(toArrowColumnsString(
                bufferAllocator,transformProcess.getInitialSchema(),
                batch.getRecordsAsString()),
                transformProcess.getInitialSchema()),transformProcess);
        int numCols = converted.get(0).size();
        for (int row = 0; row < converted.size(); row++) {
            String[] values = new String[numCols];
            for (int i = 0; i < values.length; i++)
                values[i] = converted.get(row).get(i).toString();
            batchCSVRecord.add(new SingleCSVRecord(values));
        }

        return batchCSVRecord;

    }
1313458
def on_backward_end(self, iteration:int, **kwargs)->None:
        ""
        if iteration == 0: return
        self._update_batches_if_needed()
        if iteration % self.stats_iters == 0: self._write_model_stats(iteration=iteration)
1102258
public static <K, V, R extends MutableMultimap<K, V>> MutableMultimap<K, V> groupBy(
            Iterable<V> iterable,
            Function<? super V, ? extends K> function,
            R concurrentMultimap,
            int batchSize,
            ForkJoinPool executor)
    {
        FJIterate.forEach(
                iterable,
                new PassThruProcedureFactory<Procedure<V>>(new MultimapPutProcedure<>(concurrentMultimap, function)),
                Combiners.<Procedure<V>>passThru(),
                batchSize,
                executor);
        return concurrentMultimap;
    }
548960
function (renderer) {

        var cache = this._cache;

        cache.use(renderer.__uid__);
        var chunks = cache.get('chunks');
        if (chunks) {
            for (var c = 0; c < chunks.length; c++) {
                var chunk = chunks[c];

                for (var k = 0; k < chunk.attributeBuffers.length; k++) {
                    var attribs = chunk.attributeBuffers[k];
                    renderer.gl.deleteBuffer(attribs.buffer);
                }

                if (chunk.indicesBuffer) {
                    renderer.gl.deleteBuffer(chunk.indicesBuffer.buffer);
                }
            }
        }
        if (this.__vaoCache) {
            var vaoExt = renderer.getGLExtension('OES_vertex_array_object');
            for (var id in this.__vaoCache) {
                var vao = this.__vaoCache[id].vao;
                if (vao) {
                    vaoExt.deleteVertexArrayOES(vao);
                }
            }
        }
        this.__vaoCache = {};
        cache.deleteContext(renderer.__uid__);
    }
146645
public void compileBatch(String []files)
    throws IOException, ClassNotFoundException
  {
    if (_compileParent) {
      try {
        if (_loader instanceof Make)
          ((Make) _loader).make();
      } catch (Exception e) {
        throw new IOException(e);
      }
    }

    if (files.length == 0)
      return;

    // only batch a number of files at a time

    int batchCount = _maxBatch;
    if (batchCount < 0)
      batchCount = Integer.MAX_VALUE / 2;
    else if (batchCount == 0)
      batchCount = 1;

    IOException exn = null;

    ArrayList<String> uniqueFiles = new ArrayList<String>();
    for (int i = 0; i < files.length; i++) {
      if (! uniqueFiles.contains(files[i]))
        uniqueFiles.add(files[i]);
    }
    files = new String[uniqueFiles.size()];
    uniqueFiles.toArray(files);

    LineMap lineMap = null;
    
    _compilerService.compile(this, files, lineMap);

    /*
    synchronized (LOCK) {
      for (int i = 0; i < files.length; i += batchCount) {
        int len = files.length - i;

        len = Math.min(len, batchCount);

        String []batchFiles = new String[len];

        System.arraycopy(files, i, batchFiles, 0, len);

        Arrays.sort(batchFiles);

        try {
          compileInt(batchFiles, null);
        } catch (IOException e) {
          if (exn == null)
            exn = e;
          else
            log.log(Level.WARNING, e.toString(), e);
        }
      }
    }

    if (exn != null)
      throw exn;
      */
  }
1234461
@Override
    public Matrix<T> repmat(final int rowRepeats, final int colRepeats) {
        N.checkArgument(rowRepeats > 0 && colRepeats > 0, "rowRepeats=%s and colRepeats=%s must be bigger than 0", rowRepeats, colRepeats);

        final T[][] c = N.newArray(arrayType, rows * rowRepeats);

        for (int i = 0, len = c.length; i < len; i++) {
            c[i] = N.newArray(componentType, cols * colRepeats);
        }

        for (int i = 0; i < rows; i++) {
            for (int j = 0; j < colRepeats; j++) {
                N.copy(a[i], 0, c[i], j * cols, cols);
            }
        }

        for (int i = 1; i < rowRepeats; i++) {
            for (int j = 0; j < rows; j++) {
                N.copy(c[j], 0, c[i * rows + j], 0, c[j].length);
            }
        }

        return new Matrix<T>(c);
    }
1168870
@Override
    public Matrix<T> repelem(final int rowRepeats, final int colRepeats) {
        N.checkArgument(rowRepeats > 0 && colRepeats > 0, "rowRepeats=%s and colRepeats=%s must be bigger than 0", rowRepeats, colRepeats);

        final T[][] c = N.newArray(arrayType, rows * rowRepeats);

        for (int i = 0, len = c.length; i < len; i++) {
            c[i] = N.newArray(componentType, cols * colRepeats);
        }

        for (int i = 0; i < rows; i++) {
            final T[] fr = c[i * rowRepeats];

            for (int j = 0; j < cols; j++) {
                N.copy(Array.repeat(a[i][j], colRepeats), 0, fr, j * colRepeats, colRepeats);
            }

            for (int k = 1; k < rowRepeats; k++) {
                N.copy(fr, 0, c[i * rowRepeats + k], 0, fr.length);
            }
        }

        return new Matrix<T>(c);
    }
1061334
private int[] convertBatch(int[] batch) {
        int[] conv = new int[batch.length];
        for (int i=0; i<batch.length; i++) {
            conv[i] = sample[batch[i]];
        }
        return conv;
    }
848864
def before_render(self):
        
        super(BatchFolderContentsView, self).before_render()

        if self.context.portal_type == "BatchFolder":
            self.request.set("disable_border", 1)
1352410
public void updateBatch(V batch) {

        if (intervalCheck.check()) {
            rolling();
        }
        synchronized (this) {
            unflushed = updater.updateBatch(batch, unflushed);
        }

    }
177534
def mergeCombiners(self, iterator, limit=None):
        
        if limit is None:
            limit = self.memory_limit
        # speedup attribute lookup
        comb, hfun, objsize = self.agg.mergeCombiners, self._partition, self._object_size
        c, data, pdata, batch = 0, self.data, self.pdata, self.batch
        for k, v in iterator:
            d = pdata[hfun(k)] if pdata else data
            d[k] = comb(d[k], v) if k in d else v
            if not limit:
                continue

            c += objsize(v)
            if c > batch:
                if get_used_memory() > limit:
                    self._spill()
                    limit = self._next_limit()
                    batch /= 2
                    c = 0
                else:
                    batch *= 1.5

        if limit and get_used_memory() >= limit:
            self._spill()