| mx.apply |
Apply symbol to the inputs. |
| mx.callback.early.stop |
Early stop with different conditions |
| mx.callback.log.speedometer |
Calculate the training speed |
| mx.callback.log.train.metric |
Log training metric each period |
| mx.callback.save.checkpoint |
Save checkpoint to files each period iteration. |
| mx.cpu |
Create a mxnet CPU context. |
| mx.ctx.default |
Set/Get default context for array creation. |
| mx.exec.backward |
Peform an backward on the executors This function will MUTATE the state of exec |
| mx.exec.forward |
Peform an forward on the executors This function will MUTATE the state of exec |
| mx.exec.update.arg.arrays |
Update the executors with new arrays This function will MUTATE the state of exec |
| mx.exec.update.aux.arrays |
Update the executors with new arrays This function will MUTATE the state of exec |
| mx.exec.update.grad.arrays |
Update the executors with new arrays This function will MUTATE the state of exec |
| mx.gpu |
Create a mxnet GPU context. |
| mx.gru |
Training GRU Unrolled Model |
| mx.gru.forward |
Using forward function to predict in gru inference model |
| mx.gru.inference |
Create a GRU Inference Model |
| mx.init.create |
Create initialization of argument like arg.array |
| mx.init.internal.default |
Internal default value initialization scheme. |
| mx.init.normal |
Create a initializer that initialize the weight with normal(0, sd) |
| mx.init.uniform |
Create a initializer that initialize the weight with uniform [-scale, scale] |
| mx.init.Xavier |
Xavier initializer |
| mx.io.arrayiter |
Create MXDataIter compatible iterator from R's array |
| mx.io.CSVIter |
Returns the CSV file iterator. |
| mx.io.extract |
Extract a certain field from DataIter. |
| mx.io.ImageDetRecordIter |
Create iterator for image detection dataset packed in recordio. |
| mx.io.ImageRecordIter |
Iterates on image RecordIO files |
| mx.io.ImageRecordIter_v1 |
Iterating on image RecordIO files |
| mx.io.ImageRecordUInt8Iter |
Iterating on image RecordIO files |
| mx.io.ImageRecordUInt8Iter_v1 |
Iterating on image RecordIO files |
| mx.io.MNISTIter |
Iterating on the MNIST dataset. |
| mx.kv.create |
Create a mxnet KVStore. |
| mx.lr_scheduler.FactorScheduler |
Learning rate scheduler. Reduction based on a factor value. |
| mx.lr_scheduler.MultiFactorScheduler |
Multifactor learning rate scheduler. Reduction based on a factor value at different steps. |
| mx.lstm |
Training LSTM Unrolled Model |
| mx.lstm.forward |
Using forward function to predict in lstm inference model |
| mx.lstm.inference |
Create a LSTM Inference Model |
| mx.metric.accuracy |
Accuracy metric for classification |
| mx.metric.custom |
Helper function to create a customized metric |
| mx.metric.mae |
MAE (Mean Absolute Error) metric for regression |
| mx.metric.mse |
MSE (Mean Squared Error) metric for regression |
| mx.metric.Perplexity |
Perplexity metric for language model |
| mx.metric.rmse |
RMSE (Root Mean Squared Error) metric for regression |
| mx.metric.rmsle |
RMSLE (Root Mean Squared Logarithmic Error) metric for regression |
| mx.metric.top_k_accuracy |
Top-k accuracy metric for classification |
| mx.mlp |
Convenience interface for multiple layer perceptron |
| mx.model.FeedForward.create |
Create a MXNet Feedforward neural net model with the specified training. |
| mx.model.init.params |
Parameter initialization |
| mx.model.load |
Load model checkpoint from file. |
| mx.model.save |
Save model checkpoint into file. |
| mx.nd.abs |
Returns element-wise absolute value of the input. |
| mx.nd.Activation |
Applies an activation function element-wise to the input. |
| mx.nd.adam.update |
Update function for Adam optimizer. Adam is seen as a generalization of AdaGrad. |
| mx.nd.add.n |
Adds all input arguments element-wise. |
| mx.nd.arccos |
Returns element-wise inverse cosine of the input array. |
| mx.nd.arccosh |
Returns the element-wise inverse hyperbolic cosine of the input array, computed element-wise. |
| mx.nd.arcsin |
Returns element-wise inverse sine of the input array. |
| mx.nd.arcsinh |
Returns the element-wise inverse hyperbolic sine of the input array, computed element-wise. |
| mx.nd.arctan |
Returns element-wise inverse tangent of the input array. |
| mx.nd.arctanh |
Returns the element-wise inverse hyperbolic tangent of the input array, computed element-wise. |
| mx.nd.argmax |
Returns indices of the maximum values along an axis. |
| mx.nd.argmax.channel |
Returns argmax indices of each channel from the input array. |
| mx.nd.argmin |
Returns indices of the minimum values along an axis. |
| mx.nd.argsort |
Returns the indices that would sort an input array along the given axis. |
| mx.nd.array |
Create a new 'mx.ndarray' that copies the content from src on ctx. |
| mx.nd.batch.dot |
Batchwise dot product. |
| mx.nd.batch.take |
Takes elements from a data batch. |
| mx.nd.BatchNorm |
Batch normalization. |
| mx.nd.BatchNorm.v1 |
Batch normalization. |
| mx.nd.BilinearSampler |
Applies bilinear sampling to input feature map. |
| mx.nd.BlockGrad |
Stops gradient computation. |
| mx.nd.broadcast.add |
Returns element-wise sum of the input arrays with broadcasting. |
| mx.nd.broadcast.axes |
Broadcasts the input array over particular axes. |
| mx.nd.broadcast.axis |
Broadcasts the input array over particular axes. |
| mx.nd.broadcast.div |
Returns element-wise division of the input arrays with broadcasting. |
| mx.nd.broadcast.equal |
Returns the result of element-wise **equal to** (==) comparison operation with broadcasting. |
| mx.nd.broadcast.greater |
Returns the result of element-wise **greater than** (>) comparison operation with broadcasting. |
| mx.nd.broadcast.greater.equal |
Returns the result of element-wise **greater than or equal to** (>=) comparison operation with broadcasting. |
| mx.nd.broadcast.hypot |
Returns the hypotenuse of a right angled triangle, given its "legs" with broadcasting. |
| mx.nd.broadcast.lesser |
Returns the result of element-wise **lesser than** (<) comparison operation with broadcasting. |
| mx.nd.broadcast.lesser.equal |
Returns the result of element-wise **lesser than or equal to** (<=) comparison operation with broadcasting. |
| mx.nd.broadcast.maximum |
Returns element-wise maximum of the input arrays with broadcasting. |
| mx.nd.broadcast.minimum |
Returns element-wise minimum of the input arrays with broadcasting. |
| mx.nd.broadcast.minus |
Returns element-wise difference of the input arrays with broadcasting. |
| mx.nd.broadcast.mod |
Returns element-wise modulo of the input arrays with broadcasting. |
| mx.nd.broadcast.mul |
Returns element-wise product of the input arrays with broadcasting. |
| mx.nd.broadcast.not.equal |
Returns the result of element-wise **not equal to** (!=) comparison operation with broadcasting. |
| mx.nd.broadcast.plus |
Returns element-wise sum of the input arrays with broadcasting. |
| mx.nd.broadcast.power |
Returns result of first array elements raised to powers from second array, element-wise with broadcasting. |
| mx.nd.broadcast.sub |
Returns element-wise difference of the input arrays with broadcasting. |
| mx.nd.broadcast.to |
Broadcasts the input array to a new shape. |
| mx.nd.cast |
Casts all elements of the input to a new type. |
| mx.nd.ceil |
Returns element-wise ceiling of the input. |
| mx.nd.choose.element.0index |
Choose one element from each line(row for python, column for R/Julia) in lhs according to index indicated by rhs. This function assume rhs uses 0-based index. |
| mx.nd.clip |
Clips (limits) the values in an array. |
| mx.nd.concat |
Joins input arrays along a given axis. |
| mx.nd.Convolution |
Compute *N*-D convolution on *(N+2)*-D input. |
| mx.nd.Convolution.v1 |
This operator is DEPRECATED. Apply convolution to input then add a bias. |
| mx.nd.copyto |
Generate an mx.ndarray object on ctx, with data copied from src |
| mx.nd.Correlation |
Applies correlation to inputs. |
| mx.nd.cos |
Computes the element-wise cosine of the input array. |
| mx.nd.cosh |
Returns the hyperbolic cosine of the input array, computed element-wise. |
| mx.nd.crop |
Slices a contiguous region of the array. |
| mx.nd.Custom |
Apply a custom operator implemented in a frontend language (like Python). |
| mx.nd.Deconvolution |
Computes 2D transposed convolution (aka fractionally strided convolution) of the input tensor. This operation can be seen as the gradient of Convolution operation with respect to its input. Convolution usually reduces the size of the input. Transposed convolution works the other way, going from a smaller input to a larger output while preserving the connectivity pattern. |
| mx.nd.degrees |
Converts each element of the input array from radians to degrees. |
| mx.nd.dot |
Dot product of two arrays. |
| mx.nd.Dropout |
Applies dropout operation to input array. |
| mx.nd.ElementWiseSum |
Adds all input arguments element-wise. |
| mx.nd.elemwise.add |
Adds arguments element-wise. |
| mx.nd.Embedding |
Maps integer indices to vector representations (embeddings). |
| mx.nd.exp |
Returns element-wise exponential value of the input. |
| mx.nd.expand.dims |
Inserts a new axis of size 1 into the array shape |
| mx.nd.expm1 |
Returns "exp(x) - 1" computed element-wise on the input. |
| mx.nd.fill.element.0index |
Fill one element of each line(row for python, column for R/Julia) in lhs according to index indicated by rhs and values indicated by mhs. This function assume rhs uses 0-based index. |
| mx.nd.fix |
Returns element-wise rounded value to the nearest integer towards zero of the input. |
| mx.nd.flatten |
Flattens the input array into a 2-D array by collapsing the higher dimensions. |
| mx.nd.flip |
Reverses the order of elements along given axis while preserving array shape. |
| mx.nd.floor |
Returns element-wise floor of the input. |
| mx.nd.FullyConnected |
Applies a linear transformation: :math:'Y = XW^T + b'. |
| mx.nd.gamma |
Returns the gamma function (extension of the factorial function to the reals) , computed element-wise on the input array. |
| mx.nd.gammaln |
Returns element-wise log of the absolute value of the gamma function of the input. |
| mx.nd.GridGenerator |
Generates 2D sampling grid for bilinear sampling. |
| mx.nd.identity |
Returns a copy of the input. |
| mx.nd.IdentityAttachKLSparseReg |
Apply a sparse regularization to the output a sigmoid activation function. |
| mx.nd.InstanceNorm |
Applies instance normalization to the n-dimensional input array. |
| mx.nd.L2Normalization |
Normalize the input array using the L2 norm. |
| mx.nd.LeakyReLU |
Applies Leaky rectified linear unit activation element-wise to the input. |
| mx.nd.linalg.gemm |
Performs general matrix multiplication and accumulation. Input are three tensors *A*, *B*, *C* each of dimension *n >= 2* and each having the same shape on the leading *n-2* dimensions. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ , *B*\ :sub:'i'\ , *C*\ :sub:'i' be the matrices given by the last *2* dimensions. The operator performs the BLAS3 function *gemm* |
| mx.nd.linalg.gemm2 |
Performs general matrix multiplication. Input are two tensors *A*, *B* each of dimension *n >= 2* and each having the same shape on the leading *n-2* dimensions. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ , *B*\ :sub:'i'\ be the matrices given by the last *2* dimensions. The operator performs the BLAS3 function *gemm* (restricted to two arguments) |
| mx.nd.linalg.potrf |
Performs Cholesky factorization of a symmetric positive-definite matrix. Input is a tensor *A* of dimension *n >= 2*. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ be the matrix given by the last *2* dimensions. The operator performs the Cholesky factorization (LAPACK function *potrf*) on each *A*\ :sub:'i'\ , i.e. it computes a lower triangular matrix *U*\ :sub:'i' such that |
| mx.nd.linalg.potri |
Performs matrix inversion from a Cholesky factorization. Input is a tensor *A* of dimension *n >= 2*. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ be the matrix given by the last *2* dimensions. The operator assumes that each *A*\ :sub:'i' is the Cholesky factorization of some symmetric positive-definite matrix *B*\ :sub:'i' given as a lower triangular matrix (so *A* is the output of a prior call to operator *linalg_potrf*). The operator computes the inverse of each *B*\ :sub:'i' from this decomposition, i.e |
| mx.nd.linalg.sumlogdiag |
Computes the sum of the logarithms of all diagonal elements in a matrix. Input is a tensor *A* of dimension *n >= 2*. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ be the matrix given by the last *2* dimensions. The operator performs a reduction of each such matrix to a scalar by summing up the logarithms of all diagonal elements. All matrices must be square and all diagonal elements must be positive. |
| mx.nd.linalg.trmm |
Performs multiplication with a triangular matrix. Input are two tensors *A*, *B* each of dimension *n >= 2* and each having the same shape on the leading *n-2* dimensions. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ , *B*\ :sub:'i'\ be the matrices given by the last *2* dimensions. The operator performs the BLAS3 function *trmm* |
| mx.nd.linalg.trsm |
Solves matrix equations involving a triangular matrix. Input are two tensors *A*, *B* each of dimension *n >= 2* and each having the same shape on the leading *n-2* dimensions. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ , *B*\ :sub:'i'\ be the matrices given by the last *2* dimensions. The operator performs the BLAS3 function *trsm*, i.e. it solves the equation |
| mx.nd.LinearRegressionOutput |
Computes and optimizes for squared loss during backward propagation. Just outputs "data" during forward propagation. |
| mx.nd.load |
Load an mx.nd.array object on disk |
| mx.nd.log |
Returns element-wise Natural logarithmic value of the input. |
| mx.nd.log.softmax |
Computes the log softmax of the input. This is equivalent to computing softmax followed by log. |
| mx.nd.log10 |
Returns element-wise Base-10 logarithmic value of the input. |
| mx.nd.log1p |
Returns element-wise "log(1 + x)" value of the input. |
| mx.nd.log2 |
Returns element-wise Base-2 logarithmic value of the input. |
| mx.nd.LogisticRegressionOutput |
Applies a logistic function to the input. |
| mx.nd.LRN |
Applies local response normalization to the input. |
| mx.nd.MAERegressionOutput |
Computes mean absolute error of the input. |
| mx.nd.make.loss |
Stops gradient computation. .. note:: "make_loss" is deprecated, use "MakeLoss". |
| mx.nd.MakeLoss |
Make your own loss function in network construction. |
| mx.nd.max |
Computes the max of array elements over given axes. |
| mx.nd.max.axis |
Computes the max of array elements over given axes. |
| mx.nd.mean |
Computes the mean of array elements over given axes. |
| mx.nd.min |
Computes the min of array elements over given axes. |
| mx.nd.min.axis |
Computes the min of array elements over given axes. |
| mx.nd.mp.sgd.mom.update |
Updater function for multi-precision sgd optimizer |
| mx.nd.mp.sgd.update |
Updater function for multi-precision sgd optimizer |
| mx.nd.nanprod |
Computes the product of array elements over given axes treating Not a Numbers ("NaN") as one. |
| mx.nd.nansum |
Computes the sum of array elements over given axes treating Not a Numbers ("NaN") as zero. |
| mx.nd.negative |
Numerical negative of the argument, element-wise. |
| mx.nd.norm |
Flattens the input array and then computes the l2 norm. |
| mx.nd.normal |
Draw random samples from a normal (Gaussian) distribution. |
| mx.nd.one.hot |
Returns a one-hot array. |
| mx.nd.ones |
Generate an mx.ndarray object with ones |
| mx.nd.ones.like |
Return an array of ones with the same shape and type as the input array. |
| mx.nd.pad |
Pads an input array with a constant or edge values of the array. |
| mx.nd.pick |
Picks elements from an input array according to the input indices along the given axis. |
| mx.nd.Pooling |
Performs pooling on the input. |
| mx.nd.Pooling.v1 |
This operator is DEPRECATED. Perform pooling on the input. |
| mx.nd.prod |
Computes the product of array elements over given axes. |
| mx.nd.radians |
Converts each element of the input array from degrees to radians. |
| mx.nd.random.exponential |
Draw random samples from an exponential distribution. |
| mx.nd.random.gamma |
Draw random samples from a gamma distribution. |
| mx.nd.random.generalized.negative.binomial |
Draw random samples from a generalized negative binomial distribution. |
| mx.nd.random.negative.binomial |
Draw random samples from a negative binomial distribution. |
| mx.nd.random.normal |
Draw random samples from a normal (Gaussian) distribution. |
| mx.nd.random.poisson |
Draw random samples from a Poisson distribution. |
| mx.nd.random.uniform |
Draw random samples from a uniform distribution. |
| mx.nd.reciprocal |
Returns the reciprocal of the argument, element-wise. |
| mx.nd.relu |
Computes rectified linear. |
| mx.nd.repeat |
Repeats elements of an array. |
| mx.nd.reshape |
Reshapes the input array. |
| mx.nd.reverse |
Reverses the order of elements along given axis while preserving array shape. |
| mx.nd.rint |
Returns element-wise rounded value to the nearest integer of the input. |
| mx.nd.rmsprop.update |
Update function for 'RMSProp' optimizer. |
| mx.nd.rmspropalex.update |
Update function for RMSPropAlex optimizer. |
| mx.nd.RNN |
Applies a recurrent layer to input. |
| mx.nd.ROIPooling |
Performs region of interest(ROI) pooling on the input array. |
| mx.nd.round |
Returns element-wise rounded value to the nearest integer of the input. |
| mx.nd.rsqrt |
Returns element-wise inverse square-root value of the input. |
| mx.nd.sample.exponential |
Concurrent sampling from multiple exponential distributions with parameters lambda (rate). |
| mx.nd.sample.gamma |
Concurrent sampling from multiple gamma distributions with parameters *alpha* (shape) and *beta* (scale). |
| mx.nd.sample.generalized.negative.binomial |
Concurrent sampling from multiple generalized negative binomial distributions with parameters *mu* (mean) and *alpha* (dispersion). |
| mx.nd.sample.multinomial |
Concurrent sampling from multiple multinomial distributions. |
| mx.nd.sample.negative.binomial |
Concurrent sampling from multiple negative binomial distributions with parameters *k* (failure limit) and *p* (failure probability). |
| mx.nd.sample.normal |
Concurrent sampling from multiple normal distributions with parameters *mu* (mean) and *sigma* (standard deviation). |
| mx.nd.sample.poisson |
Concurrent sampling from multiple Poisson distributions with parameters lambda (rate). |
| mx.nd.sample.uniform |
Concurrent sampling from multiple uniform distributions on the intervals given by *[low,high)*. |
| mx.nd.save |
Save an mx.nd.array object |
| mx.nd.SequenceLast |
Takes the last element of a sequence. |
| mx.nd.SequenceMask |
Sets all elements outside the sequence to a constant value. |
| mx.nd.SequenceReverse |
Reverses the elements of each sequence. |
| mx.nd.sgd.mom.update |
Momentum update function for Stochastic Gradient Descent (SDG) optimizer. |
| mx.nd.sgd.update |
Update function for Stochastic Gradient Descent (SDG) optimizer. |
| mx.nd.sigmoid |
Computes sigmoid of x element-wise. |
| mx.nd.sign |
Returns element-wise sign of the input. |
| mx.nd.sin |
Computes the element-wise sine of the input array. |
| mx.nd.sinh |
Returns the hyperbolic sine of the input array, computed element-wise. |
| mx.nd.slice.axis |
Slices along a given axis. |
| mx.nd.SliceChannel |
Splits an array along a particular axis into multiple sub-arrays. |
| mx.nd.smooth.l1 |
Calculate Smooth L1 Loss(lhs, scalar) by summing |
| mx.nd.softmax |
Applies the softmax function. |
| mx.nd.softmax.cross.entropy |
Calculate cross entropy of softmax output and one-hot label. |
| mx.nd.SoftmaxActivation |
Applies softmax activation to input. This is intended for internal layers. |
| mx.nd.SoftmaxOutput |
Computes the gradient of cross entropy loss with respect to softmax output. |
| mx.nd.sort |
Returns a sorted copy of an input array along the given axis. |
| mx.nd.SpatialTransformer |
Applies a spatial transformer to input feature map. |
| mx.nd.split |
Splits an array along a particular axis into multiple sub-arrays. |
| mx.nd.sqrt |
Returns element-wise square-root value of the input. |
| mx.nd.square |
Returns element-wise squared value of the input. |
| mx.nd.stack |
Join a sequence of arrays along a new axis. |
| mx.nd.stop.gradient |
Stops gradient computation. |
| mx.nd.sum |
Computes the sum of array elements over given axes. |
| mx.nd.sum.axis |
Computes the sum of array elements over given axes. |
| mx.nd.SVMOutput |
Computes support vector machine based transformation of the input. |
| mx.nd.swapaxes |
Interchanges two axes of an array. |
| mx.nd.SwapAxis |
Interchanges two axes of an array. |
| mx.nd.take |
Takes elements from an input array along the given axis. |
| mx.nd.tan |
Computes the element-wise tangent of the input array. |
| mx.nd.tanh |
Returns the hyperbolic tangent of the input array, computed element-wise. |
| mx.nd.tile |
Repeats the whole array multiple times. |
| mx.nd.topk |
Returns the top *k* elements in an input array along the given axis. |
| mx.nd.transpose |
Permutes the dimensions of an array. |
| mx.nd.trunc |
Return the element-wise truncated value of the input. |
| mx.nd.uniform |
Draw random samples from a uniform distribution. |
| mx.nd.UpSampling |
Performs nearest neighbor/bilinear up sampling to inputs. |
| mx.nd.where |
Given three ndarrays, condition, x, and y, return an ndarray with the elements from x or y, depending on the elements from condition are true or false. x and y must have the same shape. If condition has the same shape as x, each element in the output array is from x if the corresponding element in the condition is true, and from y if false. If condition does not have the same shape as x, it must be a 1D array whose size is the same as x's first dimension size. Each row of the output array is from x's row if the corresponding element from condition is true, and from y's row if false. |
| mx.nd.zeros |
Generate an mx.nd.array object with zeros |
| mx.nd.zeros.like |
Return an array of zeros with the same shape and type as the input array. |
| mx.opt.adadelta |
Create an AdaDelta optimizer with respective parameters. |
| mx.opt.adagrad |
Create an AdaGrad optimizer with respective parameters. AdaGrad optimizer of Duchi et al., 2011, |
| mx.opt.adam |
Create an Adam optimizer with respective parameters. Adam optimizer as described in [King2014]. |
| mx.opt.create |
Create an optimizer by name and parameters |
| mx.opt.get.updater |
Get an updater closure that can take list of weight and gradient and return updated list of weight. |
| mx.opt.rmsprop |
Create an RMSProp optimizer with respective parameters. Reference: Tieleman T, Hinton G. Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude[J]. COURSERA: Neural Networks for Machine Learning, 2012, 4(2). The code follows: http://arxiv.org/pdf/1308.0850v5.pdf Eq(38) - Eq(45) by Alex Graves, 2013. |
| mx.opt.sgd |
Create an SGD optimizer with respective parameters. Perform SGD with momentum update |
| mx.profiler.config |
Set up the configuration of profiler. |
| mx.profiler.state |
Set up the profiler state to record operator. |
| mx.rnn |
Training RNN Unrolled Model |
| mx.rnn.forward |
Using forward function to predict in rnn inference model |
| mx.rnn.inference |
Create a RNN Inference Model |
| mx.rnorm |
Generate nomal distribution with mean and sd. |
| mx.runif |
Generate uniform distribution in [low, high) with specified shape. |
| mx.serialize |
Serialize MXNet model into RData-compatiable format. |
| mx.set.seed |
Set the seed used by mxnet device-specific random number generators. |
| mx.simple.bind |
Simple bind the symbol to executor, with information from input shapes. |
| mx.symbol.abs |
abs:Returns element-wise absolute value of the input. |
| mx.symbol.Activation |
Activation:Applies an activation function element-wise to the input. |
| mx.symbol.adam_update |
adam_update:Update function for Adam optimizer. Adam is seen as a generalization of AdaGrad. |
| mx.symbol.add_n |
add_n:Adds all input arguments element-wise. |
| mx.symbol.arccos |
arccos:Returns element-wise inverse cosine of the input array. |
| mx.symbol.arccosh |
arccosh:Returns the element-wise inverse hyperbolic cosine of the input array, computed element-wise. |
| mx.symbol.arcsin |
arcsin:Returns element-wise inverse sine of the input array. |
| mx.symbol.arcsinh |
arcsinh:Returns the element-wise inverse hyperbolic sine of the input array, computed element-wise. |
| mx.symbol.arctan |
arctan:Returns element-wise inverse tangent of the input array. |
| mx.symbol.arctanh |
arctanh:Returns the element-wise inverse hyperbolic tangent of the input array, computed element-wise. |
| mx.symbol.argmax |
argmax:Returns indices of the maximum values along an axis. |
| mx.symbol.argmax_channel |
argmax_channel:Returns argmax indices of each channel from the input array. |
| mx.symbol.argmin |
argmin:Returns indices of the minimum values along an axis. |
| mx.symbol.argsort |
argsort:Returns the indices that would sort an input array along the given axis. |
| mx.symbol.BatchNorm |
BatchNorm:Batch normalization. |
| mx.symbol.BatchNorm_v1 |
BatchNorm_v1:Batch normalization. |
| mx.symbol.batch_dot |
batch_dot:Batchwise dot product. |
| mx.symbol.batch_take |
batch_take:Takes elements from a data batch. |
| mx.symbol.BilinearSampler |
BilinearSampler:Applies bilinear sampling to input feature map. |
| mx.symbol.BlockGrad |
BlockGrad:Stops gradient computation. |
| mx.symbol.broadcast_add |
broadcast_add:Returns element-wise sum of the input arrays with broadcasting. |
| mx.symbol.broadcast_axes |
broadcast_axes:Broadcasts the input array over particular axes. |
| mx.symbol.broadcast_axis |
broadcast_axis:Broadcasts the input array over particular axes. |
| mx.symbol.broadcast_div |
broadcast_div:Returns element-wise division of the input arrays with broadcasting. |
| mx.symbol.broadcast_equal |
broadcast_equal:Returns the result of element-wise **equal to** (==) comparison operation with broadcasting. |
| mx.symbol.broadcast_greater |
broadcast_greater:Returns the result of element-wise **greater than** (>) comparison operation with broadcasting. |
| mx.symbol.broadcast_greater_equal |
broadcast_greater_equal:Returns the result of element-wise **greater than or equal to** (>=) comparison operation with broadcasting. |
| mx.symbol.broadcast_hypot |
broadcast_hypot: Returns the hypotenuse of a right angled triangle, given its "legs" with broadcasting. |
| mx.symbol.broadcast_lesser |
broadcast_lesser:Returns the result of element-wise **lesser than** (<) comparison operation with broadcasting. |
| mx.symbol.broadcast_lesser_equal |
broadcast_lesser_equal:Returns the result of element-wise **lesser than or equal to** (<=) comparison operation with broadcasting. |
| mx.symbol.broadcast_maximum |
broadcast_maximum:Returns element-wise maximum of the input arrays with broadcasting. |
| mx.symbol.broadcast_minimum |
broadcast_minimum:Returns element-wise minimum of the input arrays with broadcasting. |
| mx.symbol.broadcast_minus |
broadcast_minus:Returns element-wise difference of the input arrays with broadcasting. |
| mx.symbol.broadcast_mod |
broadcast_mod:Returns element-wise modulo of the input arrays with broadcasting. |
| mx.symbol.broadcast_mul |
broadcast_mul:Returns element-wise product of the input arrays with broadcasting. |
| mx.symbol.broadcast_not_equal |
broadcast_not_equal:Returns the result of element-wise **not equal to** (!=) comparison operation with broadcasting. |
| mx.symbol.broadcast_plus |
broadcast_plus:Returns element-wise sum of the input arrays with broadcasting. |
| mx.symbol.broadcast_power |
broadcast_power:Returns result of first array elements raised to powers from second array, element-wise with broadcasting. |
| mx.symbol.broadcast_sub |
broadcast_sub:Returns element-wise difference of the input arrays with broadcasting. |
| mx.symbol.broadcast_to |
broadcast_to:Broadcasts the input array to a new shape. |
| mx.symbol.cast |
cast:Casts all elements of the input to a new type. |
| mx.symbol.ceil |
ceil:Returns element-wise ceiling of the input. |
| mx.symbol.choose_element_0index |
choose_element_0index:Choose one element from each line(row for python, column for R/Julia) in lhs according to index indicated by rhs. This function assume rhs uses 0-based index. |
| mx.symbol.clip |
clip:Clips (limits) the values in an array. |
| mx.symbol.Concat |
Perform an feature concat on channel dim (dim 1) over all the inputs. |
| mx.symbol.Convolution |
Convolution:Compute *N*-D convolution on *(N+2)*-D input. |
| mx.symbol.Convolution_v1 |
Convolution_v1:This operator is DEPRECATED. Apply convolution to input then add a bias. |
| mx.symbol.Correlation |
Correlation:Applies correlation to inputs. |
| mx.symbol.cos |
cos:Computes the element-wise cosine of the input array. |
| mx.symbol.cosh |
cosh:Returns the hyperbolic cosine of the input array, computed element-wise. |
| mx.symbol.crop |
crop:Slices a contiguous region of the array. |
| mx.symbol.Custom |
Custom:Apply a custom operator implemented in a frontend language (like Python). |
| mx.symbol.Deconvolution |
Deconvolution:Computes 2D transposed convolution (aka fractionally strided convolution) of the input tensor. This operation can be seen as the gradient of Convolution operation with respect to its input. Convolution usually reduces the size of the input. Transposed convolution works the other way, going from a smaller input to a larger output while preserving the connectivity pattern. |
| mx.symbol.degrees |
degrees:Converts each element of the input array from radians to degrees. |
| mx.symbol.dot |
dot:Dot product of two arrays. |
| mx.symbol.Dropout |
Dropout:Applies dropout operation to input array. |
| mx.symbol.ElementWiseSum |
ElementWiseSum:Adds all input arguments element-wise. |
| mx.symbol.elemwise_add |
elemwise_add:Adds arguments element-wise. |
| mx.symbol.Embedding |
Embedding:Maps integer indices to vector representations (embeddings). |
| mx.symbol.exp |
exp:Returns element-wise exponential value of the input. |
| mx.symbol.expand_dims |
expand_dims:Inserts a new axis of size 1 into the array shape |
| mx.symbol.expm1 |
expm1:Returns "exp(x) - 1" computed element-wise on the input. |
| mx.symbol.fill_element_0index |
fill_element_0index:Fill one element of each line(row for python, column for R/Julia) in lhs according to index indicated by rhs and values indicated by mhs. This function assume rhs uses 0-based index. |
| mx.symbol.fix |
fix:Returns element-wise rounded value to the nearest integer towards zero of the input. |
| mx.symbol.flatten |
flatten:Flattens the input array into a 2-D array by collapsing the higher dimensions. |
| mx.symbol.flip |
flip:Reverses the order of elements along given axis while preserving array shape. |
| mx.symbol.floor |
floor:Returns element-wise floor of the input. |
| mx.symbol.FullyConnected |
FullyConnected:Applies a linear transformation: :math:'Y = XW^T + b'. |
| mx.symbol.gamma |
gamma:Returns the gamma function (extension of the factorial function to the reals) , computed element-wise on the input array. |
| mx.symbol.gammaln |
gammaln:Returns element-wise log of the absolute value of the gamma function of the input. |
| mx.symbol.GridGenerator |
GridGenerator:Generates 2D sampling grid for bilinear sampling. |
| mx.symbol.Group |
Create a symbol that groups symbols together. |
| mx.symbol.identity |
identity:Returns a copy of the input. |
| mx.symbol.IdentityAttachKLSparseReg |
IdentityAttachKLSparseReg:Apply a sparse regularization to the output a sigmoid activation function. |
| mx.symbol.infer.shape |
Inference the shape of arguments, outputs, and auxiliary states. |
| mx.symbol.InstanceNorm |
InstanceNorm:Applies instance normalization to the n-dimensional input array. |
| mx.symbol.L2Normalization |
L2Normalization:Normalize the input array using the L2 norm. |
| mx.symbol.LeakyReLU |
LeakyReLU:Applies Leaky rectified linear unit activation element-wise to the input. |
| mx.symbol.linalg_gemm |
linalg_gemm:Performs general matrix multiplication and accumulation. Input are three tensors *A*, *B*, *C* each of dimension *n >= 2* and each having the same shape on the leading *n-2* dimensions. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ , *B*\ :sub:'i'\ , *C*\ :sub:'i' be the matrices given by the last *2* dimensions. The operator performs the BLAS3 function *gemm* |
| mx.symbol.linalg_gemm2 |
linalg_gemm2:Performs general matrix multiplication. Input are two tensors *A*, *B* each of dimension *n >= 2* and each having the same shape on the leading *n-2* dimensions. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ , *B*\ :sub:'i'\ be the matrices given by the last *2* dimensions. The operator performs the BLAS3 function *gemm* (restricted to two arguments) |
| mx.symbol.linalg_potrf |
linalg_potrf:Performs Cholesky factorization of a symmetric positive-definite matrix. Input is a tensor *A* of dimension *n >= 2*. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ be the matrix given by the last *2* dimensions. The operator performs the Cholesky factorization (LAPACK function *potrf*) on each *A*\ :sub:'i'\ , i.e. it computes a lower triangular matrix *U*\ :sub:'i' such that |
| mx.symbol.linalg_potri |
linalg_potri:Performs matrix inversion from a Cholesky factorization. Input is a tensor *A* of dimension *n >= 2*. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ be the matrix given by the last *2* dimensions. The operator assumes that each *A*\ :sub:'i' is the Cholesky factorization of some symmetric positive-definite matrix *B*\ :sub:'i' given as a lower triangular matrix (so *A* is the output of a prior call to operator *linalg_potrf*). The operator computes the inverse of each *B*\ :sub:'i' from this decomposition, i.e |
| mx.symbol.linalg_sumlogdiag |
linalg_sumlogdiag:Computes the sum of the logarithms of all diagonal elements in a matrix. Input is a tensor *A* of dimension *n >= 2*. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ be the matrix given by the last *2* dimensions. The operator performs a reduction of each such matrix to a scalar by summing up the logarithms of all diagonal elements. All matrices must be square and all diagonal elements must be positive. |
| mx.symbol.linalg_trmm |
linalg_trmm:Performs multiplication with a triangular matrix. Input are two tensors *A*, *B* each of dimension *n >= 2* and each having the same shape on the leading *n-2* dimensions. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ , *B*\ :sub:'i'\ be the matrices given by the last *2* dimensions. The operator performs the BLAS3 function *trmm* |
| mx.symbol.linalg_trsm |
linalg_trsm:Solves matrix equations involving a triangular matrix. Input are two tensors *A*, *B* each of dimension *n >= 2* and each having the same shape on the leading *n-2* dimensions. For every *n-2* dimensional index *i* let *A*\ :sub:'i'\ , *B*\ :sub:'i'\ be the matrices given by the last *2* dimensions. The operator performs the BLAS3 function *trsm*, i.e. it solves the equation |
| mx.symbol.LinearRegressionOutput |
LinearRegressionOutput:Computes and optimizes for squared loss during backward propagation. Just outputs "data" during forward propagation. |
| mx.symbol.load |
Load an mx.symbol object |
| mx.symbol.load.json |
Load an mx.symbol object from a json string |
| mx.symbol.log |
log:Returns element-wise Natural logarithmic value of the input. |
| mx.symbol.log10 |
log10:Returns element-wise Base-10 logarithmic value of the input. |
| mx.symbol.log1p |
log1p:Returns element-wise "log(1 + x)" value of the input. |
| mx.symbol.log2 |
log2:Returns element-wise Base-2 logarithmic value of the input. |
| mx.symbol.LogisticRegressionOutput |
LogisticRegressionOutput:Applies a logistic function to the input. |
| mx.symbol.log_softmax |
log_softmax:Computes the log softmax of the input. This is equivalent to computing softmax followed by log. |
| mx.symbol.LRN |
LRN:Applies local response normalization to the input. |
| mx.symbol.MAERegressionOutput |
MAERegressionOutput:Computes mean absolute error of the input. |
| mx.symbol.MakeLoss |
MakeLoss:Make your own loss function in network construction. |
| mx.symbol.make_loss |
make_loss:Stops gradient computation. .. note:: "make_loss" is deprecated, use "MakeLoss". |
| mx.symbol.max |
max:Computes the max of array elements over given axes. |
| mx.symbol.max_axis |
max_axis:Computes the max of array elements over given axes. |
| mx.symbol.mean |
mean:Computes the mean of array elements over given axes. |
| mx.symbol.mp_sgd_mom_update |
mp_sgd_mom_update:Updater function for multi-precision sgd optimizer |
| mx.symbol.mp_sgd_update |
mp_sgd_update:Updater function for multi-precision sgd optimizer |
| mx.symbol.nanprod |
nanprod:Computes the product of array elements over given axes treating Not a Numbers ("NaN") as one. |
| mx.symbol.nansum |
nansum:Computes the sum of array elements over given axes treating Not a Numbers ("NaN") as zero. |
| mx.symbol.negative |
negative:Numerical negative of the argument, element-wise. |
| mx.symbol.norm |
norm:Flattens the input array and then computes the l2 norm. |
| mx.symbol.normal |
normal:Draw random samples from a normal (Gaussian) distribution. |
| mx.symbol.ones_like |
ones_like:Return an array of ones with the same shape and type as the input array. |
| mx.symbol.one_hot |
one_hot:Returns a one-hot array. |
| mx.symbol.pad |
pad:Pads an input array with a constant or edge values of the array. |
| mx.symbol.pick |
pick:Picks elements from an input array according to the input indices along the given axis. |
| mx.symbol.Pooling |
Pooling:Performs pooling on the input. |
| mx.symbol.Pooling_v1 |
Pooling_v1:This operator is DEPRECATED. Perform pooling on the input. |
| mx.symbol.prod |
prod:Computes the product of array elements over given axes. |
| mx.symbol.radians |
radians:Converts each element of the input array from degrees to radians. |
| mx.symbol.random_exponential |
random_exponential:Draw random samples from an exponential distribution. |
| mx.symbol.random_gamma |
random_gamma:Draw random samples from a gamma distribution. |
| mx.symbol.random_generalized_negative_binomial |
random_generalized_negative_binomial:Draw random samples from a generalized negative binomial distribution. |
| mx.symbol.random_negative_binomial |
random_negative_binomial:Draw random samples from a negative binomial distribution. |
| mx.symbol.random_normal |
random_normal:Draw random samples from a normal (Gaussian) distribution. |
| mx.symbol.random_poisson |
random_poisson:Draw random samples from a Poisson distribution. |
| mx.symbol.random_uniform |
random_uniform:Draw random samples from a uniform distribution. |
| mx.symbol.reciprocal |
reciprocal:Returns the reciprocal of the argument, element-wise. |
| mx.symbol.relu |
relu:Computes rectified linear. |
| mx.symbol.repeat |
repeat:Repeats elements of an array. |
| mx.symbol.reshape |
reshape:Reshapes the input array. |
| mx.symbol.reverse |
reverse:Reverses the order of elements along given axis while preserving array shape. |
| mx.symbol.rint |
rint:Returns element-wise rounded value to the nearest integer of the input. |
| mx.symbol.rmspropalex_update |
rmspropalex_update:Update function for RMSPropAlex optimizer. |
| mx.symbol.rmsprop_update |
rmsprop_update:Update function for 'RMSProp' optimizer. |
| mx.symbol.RNN |
RNN:Applies a recurrent layer to input. |
| mx.symbol.ROIPooling |
ROIPooling:Performs region of interest(ROI) pooling on the input array. |
| mx.symbol.round |
round:Returns element-wise rounded value to the nearest integer of the input. |
| mx.symbol.rsqrt |
rsqrt:Returns element-wise inverse square-root value of the input. |
| mx.symbol.sample_exponential |
sample_exponential:Concurrent sampling from multiple exponential distributions with parameters lambda (rate). |
| mx.symbol.sample_gamma |
sample_gamma:Concurrent sampling from multiple gamma distributions with parameters *alpha* (shape) and *beta* (scale). |
| mx.symbol.sample_generalized_negative_binomial |
sample_generalized_negative_binomial:Concurrent sampling from multiple generalized negative binomial distributions with parameters *mu* (mean) and *alpha* (dispersion). |
| mx.symbol.sample_multinomial |
sample_multinomial:Concurrent sampling from multiple multinomial distributions. |
| mx.symbol.sample_negative_binomial |
sample_negative_binomial:Concurrent sampling from multiple negative binomial distributions with parameters *k* (failure limit) and *p* (failure probability). |
| mx.symbol.sample_normal |
sample_normal:Concurrent sampling from multiple normal distributions with parameters *mu* (mean) and *sigma* (standard deviation). |
| mx.symbol.sample_poisson |
sample_poisson:Concurrent sampling from multiple Poisson distributions with parameters lambda (rate). |
| mx.symbol.sample_uniform |
sample_uniform:Concurrent sampling from multiple uniform distributions on the intervals given by *[low,high)*. |
| mx.symbol.save |
Save an mx.symbol object |
| mx.symbol.SequenceLast |
SequenceLast:Takes the last element of a sequence. |
| mx.symbol.SequenceMask |
SequenceMask:Sets all elements outside the sequence to a constant value. |
| mx.symbol.SequenceReverse |
SequenceReverse:Reverses the elements of each sequence. |
| mx.symbol.sgd_mom_update |
sgd_mom_update:Momentum update function for Stochastic Gradient Descent (SDG) optimizer. |
| mx.symbol.sgd_update |
sgd_update:Update function for Stochastic Gradient Descent (SDG) optimizer. |
| mx.symbol.sigmoid |
sigmoid:Computes sigmoid of x element-wise. |
| mx.symbol.sign |
sign:Returns element-wise sign of the input. |
| mx.symbol.sin |
sin:Computes the element-wise sine of the input array. |
| mx.symbol.sinh |
sinh:Returns the hyperbolic sine of the input array, computed element-wise. |
| mx.symbol.slice |
slice:Slices a contiguous region of the array. |
| mx.symbol.SliceChannel |
SliceChannel:Splits an array along a particular axis into multiple sub-arrays. |
| mx.symbol.slice_axis |
slice_axis:Slices along a given axis. |
| mx.symbol.smooth_l1 |
smooth_l1:Calculate Smooth L1 Loss(lhs, scalar) by summing |
| mx.symbol.softmax |
softmax:Applies the softmax function. |
| mx.symbol.SoftmaxActivation |
SoftmaxActivation:Applies softmax activation to input. This is intended for internal layers. |
| mx.symbol.SoftmaxOutput |
SoftmaxOutput:Computes the gradient of cross entropy loss with respect to softmax output. |
| mx.symbol.softmax_cross_entropy |
softmax_cross_entropy:Calculate cross entropy of softmax output and one-hot label. |
| mx.symbol.sort |
sort:Returns a sorted copy of an input array along the given axis. |
| mx.symbol.SpatialTransformer |
SpatialTransformer:Applies a spatial transformer to input feature map. |
| mx.symbol.split |
split:Splits an array along a particular axis into multiple sub-arrays. |
| mx.symbol.sqrt |
sqrt:Returns element-wise square-root value of the input. |
| mx.symbol.square |
square:Returns element-wise squared value of the input. |
| mx.symbol.stack |
stack:Join a sequence of arrays along a new axis. |
| mx.symbol.stop_gradient |
stop_gradient:Stops gradient computation. |
| mx.symbol.sum |
sum:Computes the sum of array elements over given axes. |
| mx.symbol.sum_axis |
sum_axis:Computes the sum of array elements over given axes. |
| mx.symbol.SVMOutput |
SVMOutput:Computes support vector machine based transformation of the input. |
| mx.symbol.swapaxes |
swapaxes:Interchanges two axes of an array. |
| mx.symbol.SwapAxis |
SwapAxis:Interchanges two axes of an array. |
| mx.symbol.take |
take:Takes elements from an input array along the given axis. |
| mx.symbol.tan |
tan:Computes the element-wise tangent of the input array. |
| mx.symbol.tanh |
tanh:Returns the hyperbolic tangent of the input array, computed element-wise. |
| mx.symbol.tile |
tile:Repeats the whole array multiple times. |
| mx.symbol.topk |
topk:Returns the top *k* elements in an input array along the given axis. |
| mx.symbol.transpose |
transpose:Permutes the dimensions of an array. |
| mx.symbol.trunc |
trunc:Return the element-wise truncated value of the input. |
| mx.symbol.uniform |
uniform:Draw random samples from a uniform distribution. |
| mx.symbol.UpSampling |
UpSampling:Performs nearest neighbor/bilinear up sampling to inputs. |
| mx.symbol.Variable |
Create a symbolic variable with specified name. |
| mx.symbol.where |
where:Given three ndarrays, condition, x, and y, return an ndarray with the elements from x or y, depending on the elements from condition are true or false. x and y must have the same shape. If condition has the same shape as x, each element in the output array is from x if the corresponding element in the condition is true, and from y if false. If condition does not have the same shape as x, it must be a 1D array whose size is the same as x's first dimension size. Each row of the output array is from x's row if the corresponding element from condition is true, and from y's row if false. |
| mx.symbol.zeros_like |
zeros_like:Return an array of zeros with the same shape and type as the input array. |
| mx.unserialize |
Unserialize MXNet model from Robject. |
| mxnet |
MXNet: Flexible and Efficient GPU computing and Deep Learning. |
| mxnet.export |
Internal function to generate mxnet_generated.R Users do not need to call this function. |


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I haven't done any drugs in quite some time. On my way to work, I bought a gram of Spice Gold from my local tattoo/head shop, which only ended up being 20 dollars. I wanted to try it, but I didn't want to be too ripped before work. So, during my lunch I pencil packed one tiny pinch into my Black and Mild. I thought it was just enough to get me a small buzz (I read reports it's like weed). I smoked 5 really big hits before I tasted the B&M.
20 Min. passed and it finally started to kick in, but once it started... it didn't stop. 10 minutes later, I was completely stoned (Extremely difficult for me to work with customers). I experienced mild delirium, time space distortion, major body tingles (mostly in the hands and face), the giggles, I spaced out alot. I honestly couldn't tell you it wasn't pot (aside from the fact it obviously wasn't). I also experienced some minimal paranoia, confusion, and extremely bad cotton mouth (gum and water come in handy).
My inital high lasted about 5 hours. My come down was slow and almost minimal. I woke up the next day and after about 3 hours of light headedness, my high came back (although much milder), and did so about 3-4 times that day. When it would comeback, it would last 20min-1hour.
It is an awesome legal high (and fairly inexpensive). I want to try Spice Diamond after I have finished my Spice Gold (Spice Diamond is 2x potency of Spice Gold). As a suggestion Do not drive! Do not use at work! (until you are confortable with it) get gum and plenty of water! Use responsibly!  Have fun! And remember, less like a rocket ship, and more like a balloon!
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


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--- layout: default body: whyme ---
I'm Andrew Hobby freelance designer and art director, who's been doing business as Get A Hobby-Design since 1998. I've recently changed my business name to simply- HobbyDesign.
I create a wide range of designs including advertising, logos, brochures, corporate identities, website concepts, dimensional pieces, and direct mailings. Prior to freelancing, I worked at various advertising agencies in and around the Boston area.
What I bring to the table is a traditional sense of brainstorming concepts specifically for a client's needs. Then taking those ideas to the computer, fine tune them, and then carrying through to the printing process - working alongside printers to get the most out of my designs to achieve the very best quality printed piece. Working with my clients every step of the way, unlike other creative companies where you'd get lost in the shuffle.
With me you get more than an experienced designer with personalized service, you get someone who delivers from initial concept through fulfillment. I have access to a network of industry professionals: photographers, web designers, printers, and copywriters, with the flexibility and talent to meet all of my client's needs. And always on time and within a budget.
So relax and get a hobby... Andrew Hobby


| Number of Classes | Line Coverage | Mutation Coverage |
|---|---|---|
| 55 | 91% | 88% |
| Name | Number of Classes | Line Coverage | Mutation Coverage |
|---|---|---|---|
| org.apache.commons.codec | 2 | 83% |
58% |
| org.apache.commons.codec.binary | 13 | 88% |
82% |
| org.apache.commons.codec.cli | 1 | 0% |
0% |
| org.apache.commons.codec.digest | 12 | 89% |
89% |
| org.apache.commons.codec.language | 13 | 97% |
94% |
| org.apache.commons.codec.language.bm | 7 | 90% |
76% |
| org.apache.commons.codec.net | 7 | 95% |
89% |


Once the file has been loaded into the application's address space, one of two initialization procedures will be invoked in the new code. Typically the initialization procedure will add new commands to a Tcl interpreter. The name of the initialization procedure is determined by packageName and whether or not the target interpreter is a safe one. For normal interpreters the name of the initialization procedure will have the form pkg_Init, where pkg is the same as packageName except that the first letter is converted to upper case and all other letters are converted to lower case. For example, if packageName is foo or FOo, the initialization procedure's name will be Foo_Init.
If the target interpreter is a safe interpreter, then the name of the initialization procedure will be pkg_SafeInit instead of pkg_Init. The pkg_SafeInit function should be written carefully, so that it initializes the safe interpreter only with partial functionality provided by the package that is safe for use by untrusted code. For more information on Safe-Tcl, see the safe manual entry.
The initialization procedure must match the following prototype:
typedef int Tcl_PackageInitProc(Tcl_Interp *interp);The interp argument identifies the interpreter in which the package is to be loaded. The initialization procedure must return TCL_OK or TCL_ERROR to indicate whether or not it completed successfully; in the event of an error it should set the interpreter's result to point to an error message. The result of the load command will be the result returned by the initialization procedure.
The actual loading of a file will only be done once for each fileName in an application. If a given fileName is loaded into multiple interpreters, then the first load will load the code and call the initialization procedure; subsequent loads will call the initialization procedure without loading the code again. It is not possible to unload or reload a package.
The load command also supports packages that are statically linked with the application, if those packages have been registered by calling the Tcl_StaticPackage procedure. If fileName is an empty string, then packageName must be specified.
If packageName is omitted or specified as an empty string, Tcl tries to guess the name of the package. This may be done differently on different platforms. The default guess, which is used on most UNIX platforms, is to take the last element of fileName, strip off the first three characters if they are lib, and use any following alphabetic and underline characters as the module name. For example, the command load libxyz4.2.so uses the module name xyz and the command load bin/last.so {} uses the module name last.
If fileName is an empty string, then packageName must be specified. The load command first searches for a statically loaded package (one that has been registered by calling the Tcl_StaticPackage procedure) by that name; if one is found, it is used. Otherwise, the load command searches for a dynamically loaded package by that name, and uses it if it is found. If several different files have been loaded with different versions of the package, Tcl picks the file that was loaded first.
load [file join [pwd] mylib.DLL]
#include <tcl.h> #include <stdio.h> static int fooCmd(ClientData clientData, Tcl_Interp *interp, int objc, Tcl_Obj *const objv[]) { printf("called with %d arguments\n", objc); return TCL_OK; } int Foo_Init(Tcl_Interp *interp) { if (Tcl_InitStubs(interp, "8.1", 0) == NULL) { return TCL_ERROR; } printf("creating foo command"); Tcl_CreateObjCommand(interp, "foo", fooCmd, NULL, NULL); return TCL_OK; }
When built into a shared/dynamic library with a suitable name (e.g. foo.dll on Windows, libfoo.so on Solaris and Linux) it can then be loaded into Tcl with the following:
# Load the extension switch $tcl_platform(platform) { windows { load [file join [pwd] foo.dll] } unix { load [file join [pwd] libfoo[info sharedlibextension]] } } # Now execute the command defined by the extension foo
Copyright © 1995-1996 Sun Microsystems, Inc. Copyright © 1995-1997 Roger E. Critchlow Jr.


In earlier cultures, the Shaman was usually present at the death of an individual to help their soul to move on to Heaven, the Valhallah, the Light, or whatever the other side was perceived to be. It was a time of healing for the family and community, and it is a process now referred to as psychopomp.
Unfortunately, in our modern culture, people die and there is no such Spirit work done. The family is often spread out over the country, and they may not even gather for the funeral. Yet, the work is there. Souls that are either confused, obstinate or have unfinished business do not move on to the Spirit world.
The following two examples demonstrate the significance of this kind of work. A man from my mentor group in Seattle was called to go to Malaysia where a huge clothing store had collapsed, killing hundreds of people. However, he returned from his trip looking very puzzled. He had not been able to find very many souls. Our group contributed this to the fact that Malaysia had a culture which took care of this kind of work, but the news later reported the loss of only six lives. The rest of the bodies were store dummies!
The second example involves my grandmother who died last month at 95, a very angry and bitter woman. She was estranged from her family, so I had only met her a few times. I had no grief or sense of loss at her passing. Yet, I felt compelled to do something at the time of her funeral, which was being held in another part of the country.
I journeyed and asked my totems to take me to her spirit, knowing that she was probably still around. When I found her, she was so angry that I couldnt get close to her. Not knowing what else to do, I began to sing to her. She stopped her raging and looked at me, seeing me for the first time. My mind said that we were family, that we shared the same genes, but that it went deeper than that. She was a good woman who had had a bad life, and I cared for her. I saw her soul. That soul part, though attenuated in her, looked back at me and responded.
At this point in the journey my face was wet with tears. I held out my hands to her and she came to me. As she came, a large, heavy cloak dropped away from her. She was young again and smiling. Still singing, I turned her towards the Light. Just before she went into it, she turned and threw back several things. They fluttered and were gone. She smiled again and said, I dont really need those, and they are not mine anyway. Then she was gone. They had been soul parts that she had stolen. They were now free to return to those to whom they belonged. As the Light expanded, so did the joy in my heart. I returned from my journey, knowing that healing comes in its own timeas it did for my grandmother, and for me.
Richard Gossett is a psychotherapist and practising shaman in Conway, Washington. A member of the Svaha Spirit Lodge, a shamanic community in the Pacific Northwest, he travels around the US and Canada helping people develop ritualistic communities using shamanic techniques. He is currently mentoring a group in Vancouver and can be reached at<PHONE_NUMBER>, or by writing to PO Box 827, Conway, Washington 98238.


Okay, a few personal notes first. I'm a male in my mid thirties with some (long ago) experience with psychoactives. As a kid I took a gram of 'shrooms following a Scorpions concert and on another occasion dropped half a hit of acid with my friend. On both occasions I experienced what would probably be considered a mild threshold sort of trip, but at fifteen I felt like the walls of Jericho were coming down. Anyhoo, that's the limit of my experience with psychadelics going into the situation I'm about to relay, what I can recall of it anyway.
So, as I said, I'm in my mid thirties and recently divorced, which basically felt like an amputation sans anasthesia. I found that my thoughts were more and more preoccupied with the days of my misspent youth (can you say 'midlife crisis' boys and girls?), and this leads me to investigate the possibility of growing some shrooms (chitake's perhaps).  Strikes me as too good to be true, but I press on with my research.  So I'm intrigued right? I mean, who wouldn't be?   I suppose there's like a two percent chance of actually getting something out of it. Yesterday it arrived.
This is what happened.
I took my package into the house, opened it, inspected the contents. Sure enough, salvia 10x, said so right there on the package. I then did something I wasn't at all prepared for, and wished afterward I hadn't done. Which is to say I loaded the bowl of a small pipe and proceeded to fire up. But let's not get ahead of ourselves. My initial feeling as I sat there with a fully loaded bowl of salvia was one of apprehension. Not that something *bad* was about to happen in the sense of an overwhelming psychadelic trip (of course not, why would I think anything like that?), but apprehension that what would undoubtedly occur is nothing at all. That I would get no buzz whatsoever from the substance other than that peculiar buzz one gets from the sense of being had.
I smoke it just like the trip reports have all said. I hold the fire on the S throughout and hit that fucker hard.  Tastes kinda harsh. Before I'm through inhaling (INhaling mind you, not EXhaling) I start to notice a buzz in my whole body. Thoughts seem kind of disjointed. Okay, I've taken my hit, now holding the smoke, counting one onethousand two onethousand in my head in an attempt to hold the smoke for at least thirty seconds. Feeling strange now. Really having to concentrate on the counting. Blow out my hit. Now I have to load up another bowl QUICK. I know this because five million trip reports have told me I must take a second hit immediately after the first. So I try and dump out a bit more S onto the cd case, and at this point the weirdness broadens.
My vision narrows to no more than my hands and that little bag of power.  With great concentration I focus what's remaining of my coherent thought processes on shaking out that bit of S but it's turned into a chore of almost unimaginable magnitude. Apparently I'm still intent on getting that second hit. My hands, oh Jesus my hands are suddenly these alien looking.....things. Totally detached from my body these 'things' are.  They shake and I have no control over them. They're the only things that seem to exist and they're really fuckin' freaking me out. I put the bag of S down on the desk and from there, all I can really recall are impressions. Once the bag is down I lean back in my computer chair and then it hits in full force.
The aspect I remember chiefly is the gravity distortion thing. Despite having read about this numerous times and seeing that it was quite apparently the thread of commonality that binds various people's salvia experiences together, I am nonetheless astounded at the actual power of this occurence. Reading about being 'pulled in every direction' from a trip report just doesn't convey sufficient meaning to actually prepare one for this experience. I was being rolled up, I was falling, no not falling, being *hurtled*, toward what exactly? I haven't a clue, but it was the strangest sensation I've ever felt. Not at all pleasant.
At this point in the trip I don't know if my eyes are open or closed. I think they were closed. Maybe it doesn't make a difference if they were open or not. All rational thought was obliterated.  Strangely enough I wasn't frightened at this point. I think being scared would have required some thought, some realization, some contemplation on what was happening and I really wasn't capable of any of that. I was pure sensory, no thought at all. It wasn't something I was doing as much as it was something that was happening to me.
At some point I open my eyes, either that or the *real* reality drifted back into its proper place, and see my bed. I have to go lay down, this is way too intense, I'm gonna come flying out of this chair if I don't hit the bed. So, marshalling all of my mental and physical capability, I fight the effects of this alien gravity and take the two plodding steps to the bed and collapse into it. Right on my face. I have to roll over. Now I'm sinking into the bed. Now it's lights out again. Utter obliteration. Falling. Being rolled up. This isn't possible. This simply can't be happening. I can hear something like a rushing sound. My shirt is strangling me.  Herculean effort to get the shirt off. Success. Back in the *real* world for a moment. Oh God don't let me go under again. Please. I can see things as they normally are right now, please don't submerge me in this madness any longer.
Ever experience sleep paralysis? That moment of being almost awake enough to start moving around but not quite? This is basically what I experienced for the next minute or so. Just laying there staring and trying to move. Finally I'm capable of movement. I go out to the living room. Drink some water. Tv. Normalcy.  I didn't care for it nor do I wish to feel it again.  Anyway, this is what happened to me on my first and probably only trip on salvia. Don't go into this unless you're prepared to go all the way. Follow the rules. Get a sitter.  The hype is real.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


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Cook delicious gourmet pizza in 15 minutes with this awesome outdoor pizza oven
by Maren EstradaI have to admit, I was skeptical before I first tried the Ooni Koda Outdoor Pizza Oven. I make pizza in my normal oven from time to time and it’s already delicious, so can a special dedicated pizza oven really be that much better? Well, the answer to my question is yes, it can. You’ll simply never get the same kind of crust and flavor out of a regular over as you will out of one of Ooni’s oven’s, and they cost way less than you might think!
Ooni Koda Outdoor Pizza Oven, Pizza Maker, Portable Oven, Gas Oven, Award Winning Pizza Oven
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Infiniti QX55 teased again
Infiniti will soon have a new 'Bionic Cheetah' on the prowl as it teases a new coupe crossover: the QX55.
by William Stopford- shares
Infiniti invented the coupe crossover with the muscular FX/QX70, which it nicknamed the “Bionic Cheetah”. It’s been discontinued from overseas markets and will soon be withdrawn from Australia, but Infiniti has a new coupe crossover coming to fill the void, the QX55.
The BMW X3-sized QX50 upon which the QX55 is based is a handsome, contemporary SUV but it lacks the visual dynamism of the outgoing QX70.
The QX55, therefore, takes the QX50’s bones and adds more exuberant styling. It'll reach North American showrooms from mid-2020.
The roofline is steeply raked aft of the C-pillar and there’s the subtlest hint of a notchback in the car’s silhouette. Overall, the QX55 is rather more reminiscent of a high-riding hatchback than a lifted sedan or wagon. In that respect, it’s more akin to an Audi Q8 than a Mercedes-Benz GLC Coupe.
You’ll notice, too, that the C-pillar treatment much more closely resembles the old QX70 than any newer Infiniti passenger cars or SUVs, almost all of which feature Infiniti’s unique “crescent-cut” C-pillar treatment.
The QX55 will be one of the last Infinitis designed by outgoing Infiniti design chief Karim Habib, who left the company earlier this year.
Overall, the QX55 does a pretty convincing impression of the QX70. Though that SUV’s current iteration was launched in some markets just over a decade ago, its styling has aged well and is arguably more harmonious than some subsequent coupe crossovers.
Above: Infinti QX70.
Where the QX55 differs markedly from the old QX70 is in its drivetrain. As it’s based on the QX50, it uses a front- and all-wheel-drive platform, not a rear- and all-wheel-drive one.
There’s no raspy V6 or grunty V8 either, as the QX55 will almost certainly retain the QX50’s 2.0-litre variable-compression turbocharged four mated to a continuously variable transmission.
In the QX50, the trick 2.0-litre produces 200kW and 390Nm.
The new naming convention echoes BMW’s delineation of sedans/wagons and their coupe siblings, though it’s unclear whether Infiniti will follow this convention with future passenger cars – by this new logic, the Q60 coupe should be a Q55.
Australia
No QX55 for us. No QX50 either. Infiniti has (almost) left the building, the company announcing earlier this year that it’ll stop selling cars in Australia by late 2020.
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Infiniti QX55 teased again


Upon completing this lesson you should be able to:
- Describe the shapes and arrangments that bacteria can have
- List and characterize the external structures of bacteria
- Describe the significance of biofilms
- Describe the composition of the bacterial cell wall
- Explain the differences between gram positive and gram negative cells
- Explain the steps of the gram stain and how it works
- List and characterize the internal structures of bacteria
- Describe the function of endospores and explain their importance
- List the characteristics of the archea and eukaryotes
- Describe the relative size of microbes and how magnification works
- Explain resolving power and factors that influence it
- Explain how staining works
- Describe the types of specialized staining
- Differentiate between the various types of microscopy


Preparation time
less than 30 mins
Cooking time
over 2 hours
Serves
Serves 6-8
This Boxing Day classic is perked up with a zesty marmalade glaze and homemade parsley sauce.
Place the gammon into a large, heavy-based, lidded saucepan with the lemon, orange, apple, cinnamon stick, onion, chillies and 2 of the star anise. Pour in enough water to cover the gammon.
Cover the pan with the lid, place onto the heat, bring the water to the boil, then turn the heat down until simmering. Simmer for 2 hours, or until the meat is tender, then set aside to cool in the cooking liquid.
Preheat the oven to 230C/210C Fan/Gas 7.
In a small pan, heat the marmalade, honey, mustard, the remaining 3 star anise and the cloves in a small pan until the preserves have melted, then stir and set aside.
Lift the cooled ham from the cooking liquid and transfer to a roasting tin. Carve the layer of fat on top of the ham in a criss-cross pattern, then spread the marmalade glaze over the top. Return to the oven for a further 20 minutes, basting with the glaze every 5-8 minutes, until the surface of the gammon is golden-brown and just starting to blacken at the edge.
Meanwhile, boil the potatoes in a saucepan of salted water for 10-15 minutes, or until just tender, then drain and return to the pan. Stir in the butter to coat, then season, to taste, with salt and freshly ground black pepper. Keep warm.
For the parsley sauce, pour the milk into a saucepan and add the clove-studded onion halves. Heat until just simmering, then turn off the heat and leave to infuse for a few minutes.
In a separate saucepan, heat the butter until melted, then whisk in the flour until well combined and cook for 30 seconds. Whisk in the infused milk a little at a time, waiting until the sauce thickens before adding each new batch of milk - you should end up with a smooth sauce the consistency of double cream. Stir in the double cream and then cook for further 1-2 minutes. Season with lemon juice, to taste, and salt and freshly ground black pepper, then remove the pan from the heat and stir in the chopped parsley.
To serve, pile the buttered potatoes onto a serving platter and place the gammon on top. Pour the parsley sauce into a jug to serve alongside. Carve at the table.


2020 AFC U19 Championship Qualifiers: Kuwait edge Pakistan 2-1; Palestine open with win
Kuwait had to come back from behind to defeat Pakistan in the opening match of their 2020 AFC U19 Championship Qualifiers at the Al Seeb Stadium in Seeb, Oman.
Matches in 10 out of the 11 groups have been completed and 14 out of the 16 qualification slots for next year’s continental championship in Uzbekistan have already been filled.
However, Group A featuring Oman, Palestine, Iraq, Kuwait and Pakistan was postponed after Iraq, who were originally to host the matches from the first week of November, saw anti-government protests forcing the competition to move out to Oman.
Pakistan had taken the lead against Kuwait through Muhammad Waheed in the 27th minute, but Kuwait were quick in their reply as Salman Al-Bous equalised in the very next minute before Abdulrahman Karam struck the winner in the 57th minute.
In the other game of the group, hosts Oman were beaten 1-0 by Palestine as Anas Baniowda scored the only goal of the game in the 19th minute.
10 group winners — Qatar, Tajikistan, IR Iran, Bahrain, Saudi Arabia, Malaysia, Australia, Korea Republic and Japan — and four best runners-up — Indonesia, Laos, Vietnam, Uzbekistan and Yemen — have already qualified for the 2020 AFC U19 Championship.
The two remaining slots in the tournament proper will go to the winner of Group A and the runners-up in Group A if they can better Cambodia’s tally of six points and goal difference of +3.
(Photo credit: Asian Football Confederation)


Sound Studios ‐ Where Technology & Art Come Together
Welcome to my site! This is the V2 site I am designing as a part of my CIS 155 Web Development class here at Olympic College. I will be updating this with more content and improving the design in the coming weeks, so stay tuned!
A few things I like to do:- Anything Technology!
- Photograpy & Videograpy
- Hiking and Outdoors
- Playing Piano and Violin
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TWILIGHT A film review by Mark R. Leeper
Capsule: Mystery in a minor key. A once- policeman, once-detective, Harry Ross is now unpaid an errand boy and friend for a wealthy man. One errand gets him involved in a murder. Soon the complications involves blackmail and the buried past. There is a lot of talk and not a lot of thrills in this mystery set in modern Los Angeles. Rating: 6 (0 to 10), +1 (-4 to +4)
Considering that TWILIGHT is only 94 minutes long and moves at such a slow pace, the plot is surprisingly complex, not to say downright confusing. The three main male characters are in their sixties and are taking that fact rather hard. Harry Ross (Paul Newman) has been a cop and a detective, but these days he is a houseguest for the well-off Jack and Catherine Ames (Gene Hackman and Susan Sarandon).  Two years earlier the errand was to pick up Jack's daughter who had run off with her boy friend to Puerto Vallarto.
Given a private package to deliver to a woman runs Harry into a man dying of a fatal dose of bullets.  Both the police and Harry are anxious to know why. Harry is able to discover that the dead man was anxious to uncover the story, never fully explained, of what happened to Catherine's first husband before she married Jack.
Director Robert Benton, director of NOBODY'S FOOL, co-wrote this film trying for the depth of character that film had and at the same time the sort of mystery that Newman had with HARPER. It must have looked good on paper. Clearly a lot of good actors had some respect for the production and were willing to take non-starring roles. We see people like Stockard Channing and James Garner in supporting roles. M.  It is hard to judge from a script if a mystery will be a good one or not. While the plot complications were convoluted, I picked out the killer early in the film, never wavered from my belief, and I was right. I suspect many viewers did the same. The film was probably made with the assumption that audiences would want to go along with Newman's easy- going rapport with his fellow actors, particularly James Garner with whom easy rapport does not seem like much of an accomplishment. However, with too much being so mellow the film robs itself of a sense of any real tension. Hackman tries to give some power to his role, but there is only so much he can do playing a man dying of cancer.
Of some additional interest is that the Ames mansion was really the home of Cedric Gibbons and Delores Del Rio. Gibbons was the art director on films like A NIGHT AT THE OPERA, THE BAD AND THE BEAUTIFUL, and LUST FOR LIFE. Del Rio was a fiery Latin beauty in films of the 1930s and 1940s. The Ames's other home was one actually built by Frank Lloyd Wright, though never completed.
The aptly named TWILIGHT seems full of characters in the twilight of their lives and reaching a point where they think and talk rather than act. The point is carefully driven home that Newman's character is still a lover, but the viewer has reason to be skeptical. The actors give the feel of people going gently into that good night. I rate TWILIGHT a 6 on the 0 to 10 scale and a +1 on the -4 to +4 scale.
Mark R. Leeper<EMAIL_ADDRESS>Copyright 1998 Mark R. Leeper
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Strikes the upper surface of the impenetrable foliage of my trees, and but a few stray gleams steal into the inner sanctuary, I throw myself down among the tall grass by the trickling stream and, as I lie close to the earth, a thousand unknown plants are noticed by me.
When I hear the buzz of the little world among the stalks, and grow familiar with the countless indescribable forms of the insects and flies, then I feel the presence of the Almighty, who formed us in his own image, and the breath of that universal love which bears and sustains.


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Role: Graphic design, UX design & strategy
Technology: Graphic design, UX design, Adobe Suite
Lesson Learned: How you communicate the project is more important than the project itself
Lucid is a set of 250 conversation cards that prompt thinking differently and creating optimal future scenarios for humanity.
It's not about what will happen, it's about what we should do.
The deck is divided into eight sections: thinking differently, future scenarios, what it means to be human, creating & innovating, alternate realities, human consciousness, shaping tomorrow, the big questions, and rethink. Rethink is designed to to challenge your thinking & initial answers, see alternative perspectives and your own biases.
The conversation cards are designed to provoke thinking differently about the world and its norms & creating the future that we want. I think we have to decide on an individual, community then cultural level what a good life is, what it means to be human, we want for ourselves and what type of future we want for the planet.
The more we bring this into our conversations the more it impacts our decisions collectively. It’s not just a few people but it’s all of us shaping the world. The world shaped us, and then we shape the world right back.
The future won’t be about doing the same thing over and over again. Anything that can be automated will be. We have a choice to be fearful of this or to embrace it and let it give the chance to discover a richer path of life fulfillment. I think that path should be of conversation and knowledge sharing.
Lucid is also a knowledge sharing platform that connects you to the thought leaders whose work is dedicated to answering these questions. I believe we should be compensating creators directly, especially those who produce knowledge pushing us all forward, by subscribing directly to thought leaders.


Delete existing equalizer settings.
DELETE /songLibrary/id/51f973830d861c2c5c626910 HTTP/1.1 Host: test.alpineconnectivity.com:8888 Authorization: Basic YWxleGFuZGVyLmoucnlhbkBnbWFpbC5jb206YmVhc3Q=
This service may only be used by registered users who are authorized to use it.
The HTTP Basic Authentication scheme is used to pass the encoded username:password of the user.
Only the owner of the songLibrary is allowed to DELETE it.
Don't call this service unless you really want to DELETE the songLibrary. There is no UNDO service.
DELETE /songLibrary/id/51f973830d861c2c5c626910 HTTP/1.1 Host: test.alpineconnectivity.com:8888 Authorization: Basic YWxleGFuZGVyLmoucnlhbkBnbWFpbC5jb206YmVhc3Q=
| id (required) |
The "id" field uniquely specifies the song library to delete |
The following response codes are possible from this service.
(Client code must handle each of them.):
The content of the body of the HTTP Response will always be JSON.
Therefore, the following header will always be sent:
Content-Type: application/json
The body of the response should always contain JSON.
The type of JSON returned varies by the response code.
4 types of JSON are possible.
If the service executed successfully
JSON like the following will be returned in the body of the response:
HTTP/1.1 200 Success
No JSON is necessary.
If there was a major error the request that prevents us from even processing it,
the standard JSON describing the error will be returned in the body of the response:
HTTP/1.1 400 Bad Request { "errorCode": 1, "errorMessage": "INVALID JSON", "data": "No JSON was POSTed!" }
If a valid username/password was not passed via the Basic Authentication mechanism, this error code will be returned.
HTTP/1.1 401 Not Authorized WWW-Authenticate: Basic realm="alpineconnectivity.com" { "errorCode": 401, "errorMessage": "Not Authorized", "data": "Authorization header was not found." }
If an error occured on the server that prevents us from satisfying the request,
the standard JSON describing the error will be returned in the body of the response:
HTTP/1.1 500 Server Error { "errorCode": 3, "errorMessage": "SERVER ERROR", "data": "Unable to read the body of the HTTP POST." }


The Tale of Tommy Fox
by Arthur Scott Bailey
Chapter 21: “The Biggest Surprise of All”
Additional Information
- Year Published: 1917
- Language: English
- Country of Origin: United States of America
- Source: Bailey, A. S. (1917). The Tale of Tommy Fox. New York: Grosset and Dunlap.
-
Readability:
- Flesch–Kincaid Level: 4.0
- Word Count: 671
- Genre: Fantasy
- Keywords: 20th century literature, american literature, children's stories, sleepy-time tales
- ✎ Cite This
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It was a pretty big surprise for Tommy Fox, when Mr. Grouse sprang out of the snow, right beneath his feet. But it was nothing at all, compared with the surprise Tommy had when he reached home.
Very late at night Tommy stole into his mother’s house. In fact, it was nearly morning. And Tommy crept in very quietly, for he hardly expected that his mother would be awake and he did not want to disturb her.
Tommy had just curled up on his bed and was all ready to go to sleep, when to his great astonishment he heard his mother talking. She was not talking to him, but to someone near her, for she spoke so low that Tommy could not hear what she was saying.
He thought right away that somebody had come to pay them a visit. And he called out—
“Who’s here, Mother? Is it a visitor?”
“Yes, Tommy,” Mrs. Fox answered. “Come here and see who it is.”
Tommy jumped out of bed and hopped across the room. At first he couldn’t see anybody but his mother.
“It’s just a joke!” Tommy exclaimed. “You’re only fooling!”
“Look sharp!” said Mrs. Fox. “It’s a surprise. What do you call this?” She moved aside a bit, and pointed to a little, soft, woolly thing which lay close beside her. Tommy had to look two or three times to see what it was. And even then he wasn’t sure.
“Is it—is it—a baby?” he asked.
“That’s just what it is,” his mother said.
Tommy certainly was surprised. And before he could find his voice again Mrs. Fox showed him another baby fox, and another and another and another.
Yes—there they were—five of them all together, small and soft and woolly. They weren’t nearly so brightly colored as Tommy and his mother—just a pale, brownish red. Tommy Fox could hardly believe it. As he stared at them he suddenly noticed something strange about the baby foxes. “Why—they’re all blind—every one of them!” he cried. “Hadn’t we better send them back and get some good ones?” he asked.
Mrs. Fox laughed.
“Of course they’re blind,” she said. “You were blind when you were their age. Their eyes will be open in a few days.... Well—what do you think of them, Tommy?” she asked; for Tommy Fox seemed to be lost in thought.
“I was wondering how they would ever be able to hunt—they’re so small.”
“Oh! I’ll have to hunt for them, for a long time,” his mother explained. “When they get big enough I shall teach them to hunt for themselves, just as I taught you.
“Now you see why I showed you how to catch mice and rabbits and woodchucks,” Mrs. Fox said. “You’ll have to look out for yourself now, Tommy. For I shall have all I can do to find enough for myself and five children to eat, without feeding a big fellow like you.”
That made Tommy Fox feel very proud. He felt bigger, and stronger, and wiser than ever before.
“I shall get along all right,” Tommy said. “I almost caught Mr. Grouse tonight. But he got away.” Tommy yawned, for he was very sleepy.
But of course it was only a dream.


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Design for Context, Consultant (October 2018 - April 2020)
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The Art Information Commons at the Philadelphia Museum of Art has been made possible by The Andrew W. Mellon Foundation.


Vietnamese truck victim was at Dutch migrant centre: Report
THE HAGUE: One of the 39 Vietnamese victims found dead in a refrigerated truck in Britain last month is a minor who disappeared from a Dutch asylum shelter previously, a newspaper report said Saturday (Nov 23).
The boy, whose name and age was not released, was among the bodies found near the south-east English port of Purfleet on Oct 23, the Algemeen Dagblad daily reported.
"The teenaged boy absconded from an extra-secure facility for vulnerable asylum seekers," the paper said, quoting a source at the COA, the Dutch government organisation handling refugees.
The COA declined to give the victim's name, but the newspaper said investigations showed the teen went missing from an asylum-seeker's centre in southern Limburg province.
READ: 'Easy money and a better life': Vietnamese undeterred by UK truck tragedy
Six Vietnamese teens also disappeared from the centre in August, sparking a massive police search involving helicopters, the paper said.
The COA however declined to link the disappearance of the six teens to the dead victim in Britain.
The bodies of eight women and 31 men were found in a trailer on an industrial estate east of London, with one of the youngest a 15-year-old boy named Nguyen Huy Hung.
READ: Vietnam 'strongly condemns' human trafficking after UK truck tragedy
The lorry had earlier arrived on a cargo ferry from the Belgian port of Zeebrugge.
Hundreds of migrants try to enter Britain annually through the world's busiest waterway using unsafe boats.
The role human traffickers play in such operations came under new scrutiny after the Vietnamese tragedy.
British detectives investigating the case on Friday made another arrest, detaining a 23-year-old man from Northern Ireland on suspicion of conspiracy to traffic people and conspiracy to assist unlawful immigration.
Northern Irish truck driver Mo Robinson, 25, has already appeared in court in connection with the case, while another man from Northern Irish, Eamonn Harrison, 22, is facing extradition proceedings in Ireland.


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Sam is designed to decrease the barrier to getting help and make talking about mental health easier. Sam can also direct you to speak with an actual person.
Whenever you need help, Sam is there. Talk to Sam on your phone or desktop 24/7.
Sam detects what on-campus/off-campus groups could help you the most and connects your directly.
Sam schedules your appointments for you! Sam connects directly to your own calendar which will send you a reminder of your appointment.


Note that the code on the left is eval'd and then dumped on the right. What this script does, is the second part, dumping real Javascript data.
You can try your own code, use only 1 line of code. It can handle from the simplest data, to complex collections.
The way each "thing" is dumped can be easily changed, and it support HTML mode output. Enjoy!


Information Architect
November 2015 to Present
University of Michigan Health System
July 2015 to October 2015
Vertafore, Inc.
January 2014 to July 2015
TechSmith Corporation
August 2008
Michigan State University
Coursework in ethnographic field methods, anthropology, cultural studies, web authoring, visual design.
March 2016
Scrum Alliance
Licensed Scrum Product Owner through March 2018, license #507634.
Founder Feb 2015 - Present
Women In Tech Chat
I started a chat group for women who work in tech to give and receive support. More information including our Code of Conduct and how to join can be found at witchat.github.io.
Volunteer Nov 2014 - Present
Information Architecture Summit
I have reviewed and provided feedback on IA Summit conference talk proposals for the past 2 years. For the 2017 conference, I will be joining the team as director of social media.
Member since 2014
Information Architecture Institute
The IAI is a non-profit organization dedicated to promoting awareness for information architecture. In 2015 and 2016, I worked with then IAI President Abby Covert to run a volunteer-driven review of the IAI's resource library.
Member since 2014
Girl Develop It: Ann Arbor
GDI has played a vital role in my professional life, helping me learn and gain confidence. I have taken classes, assisted with teaching, and volunteered at events.


ProjectLoopsLearning To Code - Graphic Design - I.T Enthusiast
Projects
About
I am currently 16 and living in Melbourne Australia. I enjoy almost anything tech-wise. I can program in HTML and have the basic knowledge in java script, I also just began to learn C++.
This website was created as a personal site to post projects and tasks I have worked on at school as well as other random things.
In I.T we are studying data visualisation and the problem solving methodology. We were required to collect primary data concerning a topic we are interested in where numerical values could be collected. For this topic I chose to collect my data on broadband. I gathered information about the ISP they chose to sign up with, the speed they get and the type of service they have. Because I had to collect primary data I decided to create an
online survey
using google forms. My survey consisted of very restricted answers after finding that the internet has a lot of trolls now days. Before changing the answers to only tick and numeric answers I had over 20 results within a few hours. These weren't the type of results I was looking for. I think that overall after I began to collect more results that my survey was a success, I ended up with 53 results and was able to use them in an info graphic
to visualise my findings as you can see above. This paricular project was being worked on over the span of just over a month. My progress was recorded onto this
gnatt chart. My data can be found
here
Project Title
Use this area of the page to describe your project. The icon above is part of a free icon set by Flat Icons. On their website, you can download their free set with 16 icons, or you can purchase the entire set with 146 icons for only $12!
Use this area of the page to describe your project. The icon above is part of a free icon set by Flat Icons. On their website, you can download their free set with 16 icons, or you can purchase the entire set with 146 icons for only $12!


DETERRENCE
Reviewed by Harvey Karten Paramount Classics Director: Rod Lurie Writer: Rod Lurie Cast: Kevin Pollak, Timothy Hutton, Sheryl Lee Ralph, Sean Astin, Clotilde Courau, Bajda Djola, Mark Thompson, Michael Mantell, Kathryn Morris, Clotilde Courau, Ryan Cutrona
"Deterrence" mines the same fields as "Dr. Strangelove" but Rod Lurie, who directs and has written his first feature film, is about as distant from Stanley Kubrick as New York is from Perth, Australia. The story takes place in a single room- -the only "opening up" occurring from file films--and fulfills all the requirements of a particularly inept off-off-Broadway play: barely workmanlike actors who look as though they couldn't make it as waiters, virtually non-existent direction, and a script that is so ludicrous that the "filmed play" looks more like William Inge's comedy "Bus Stop" than like Sidney Lumet's "Fail-Safe."  If Lurie had billed his movie as a lampoon, he'd be off the hook. But if you take a look at his agitprop statement in the production notes, you might be appalled at his one-dimensional, simplistic view of America's role in the world--all of which comes out in his depiction of a president who represents the banality of evil.
Lurie, an Israeli-born American citizen who went to West Point, now bills himself as pacifistic and somewhat to the left of center in his politics. He appears to say in his notes that Truman's decision to drop the A-bomb on Japan was inspired by racism, pure and simple, since Japan was about to surrender imminently with no land invasion by Americans necessary: that the U.S. used the bomb not just once, but twice on the Japanese civilians simply to show the Russians that we had the weapon. Similarly he believes that President Walter Emerson (Kevin Pollak), Lurie's fatuous creation, feels little compunction about ordering the nuking of Baghdad during a crisis since after-all-they're-only-Arabs. If the acting, direction and screenplay of "Deterrence" do not strike you as absurd, perhaps Lurie's simplistic evocation of truth will. All in all, the picture is a travesty in every regard.
The scene opens during a brutal snowstorm in Aztec, Colorado in the year 2008, the inhabitants of a diner being a cross-section of Americans. Enter the president of the United States (Pollak), his chief of staff Marshall Thompson (Timothy Hutton), his national security adviser, Gayle Redford (Sheryl Lee Ralph) and Special Agent Dexter (Ryan Cutrona). Trapped by the storm just as the polls close in Colorado's presidential primary, the president naturally awes the cafe's denizens, who include the owner, Harvey (Bajda Djola), a 30- ish married couple, Taylor Woods (Michael Mantell) and Lizzie (Kathryn Morris), a clueless waitress with a Quebecois accent, Katie (Clotilde Courau), and redneck Ralph (Sean Astin). When Iraqi dictator Udei Hussein takes advantage of the president's involvement in the primary and of a crisis in Asia to invade Kuwait once again, President Pollak--a short, uncharismatic man who had never been elected to the office but who had taken over from the deceased chief executive-- does not have the manpower to divert to the Middle East to turn back the invaders. In the most preposterous decision of this thoroughly ludicrous story, he ratchets up the ante on the spot. If Udei does not --get this--withdraw within two hours and surrender himself in the U.S. Embassy, the U.S. will drop a nuclear bomb on Baghdad.
Everyone in the audience during the special screening of this movie was either biting his lip or simply being polite. How else to explain the complete absence of uproarious laughter in the congregation?
But that's not all. Dismissing the advice of his national security adviser and his chief of staff, the president instead calls upon the American people, i.e. those middle-Americans slurping coffee and serving chili in the cafe, to give their opinions. With the fate of the world in the balance (since Iraq has threatened to drop its own recently purchased nuclear missiles on New York, Sydney, Washington, Tokyo, Tel Aviv and other Western allies), President Emerson puffs casually on his cigar, gives a buzz on the pay phone to his wife back in Washington (who tells him that she will not be his Eva Braun), and goes on national TV. He even discusses football with the pilot of the B-52 which is approaching Iraqi air space.
Timothy Hutton has been made up to look like "Fail-Safe"'s Henry Fonda, thereby losing the boyish charm he displayed so well in "The Substance of Fire." But the 41-year-old Kevin Pollak is perfectly cast: he got his start as a stand-up comic on the San Francisco club circuit.
Rated R. Running Time: 101 minutes. (C) 2000 Harvey Karten<EMAIL_ADDRESS>The review above was posted to the
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