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Merge pull request #457 from terrytangyuan/test
[R TST] Set up R Travis Environment
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Original file line number | Diff line number | Diff line change |
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require(mxnet) | ||
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context("models") | ||
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# test_that("basic symbol operation", { | ||
# # Network configuration | ||
# batch.size <- 100 | ||
# data <- mx.symbol.Variable("data") | ||
# fc1 <- mx.symbol.FullyConnected(data, name="fc1", num_hidden=128) | ||
# act1 <- mx.symbol.Activation(fc1, name="relu1", act_type="relu") | ||
# fc2 <- mx.symbol.FullyConnected(act1, name = "fc2", num_hidden = 64) | ||
# act2 <- mx.symbol.Activation(fc2, name="relu2", act_type="relu") | ||
# fc3 <- mx.symbol.FullyConnected(act2, name="fc3", num_hidden=10) | ||
# softmax <- mx.symbol.Softmax(fc3, name = "sm") | ||
# | ||
# dtrain = mx.io.MNISTIter( | ||
# image="data/train-images-idx3-ubyte", | ||
# label="data/train-labels-idx1-ubyte", | ||
# data.shape=c(784), | ||
# batch.size=batch.size, | ||
# shuffle=TRUE, | ||
# flat=TRUE, | ||
# silent=0, | ||
# seed=10) | ||
# | ||
# dtest = mx.io.MNISTIter( | ||
# image="data/t10k-images-idx3-ubyte", | ||
# label="data/t10k-labels-idx1-ubyte", | ||
# data.shape=c(784), | ||
# batch.size=batch.size, | ||
# shuffle=FALSE, | ||
# flat=TRUE, | ||
# silent=0) | ||
# | ||
# mx.set.seed(0) | ||
# devices = lapply(1:2, function(i) { | ||
# mx.cpu(i) | ||
# }) | ||
# | ||
# # create the model | ||
# model <- mx.model.FeedForward.create(softmax, X=dtrain, eval.data=dtest, | ||
# ctx=devices, num.round=1, | ||
# learning.rate=0.1, momentum=0.9, | ||
# initializer=mx.init.uniform(0.07), | ||
# epoch.end.callback=mx.callback.save.checkpoint("chkpt"), | ||
# batch.end.callback=mx.callback.log.train.metric(100)) | ||
# | ||
# # do prediction | ||
# pred <- predict(model, dtest) | ||
# label <- mx.io.extract(dtest, "label") | ||
# dataX <- mx.io.extract(dtest, "data") | ||
# # Predict with R's array | ||
# pred2 <- predict(model, X=dataX) | ||
# | ||
# accuracy <- function(label, pred) { | ||
# ypred = max.col(t(as.array(pred))) | ||
# return(sum((as.array(label) + 1) == ypred) / length(label)) | ||
# } | ||
# | ||
# print(paste0("Finish prediction... accuracy=", accuracy(label, pred))) | ||
# print(paste0("Finish prediction... accuracy2=", accuracy(label, pred2))) | ||
# }) |
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#!/bin/bash | ||
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if [ ${TASK} == "r_test" ]; then | ||
cat mxnet/mxnet.Rcheck/*.log | ||
fi |