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In the model training step, specifically when we are standing in the "fit" step, we use the command and it crashes the kernel.
train and test are txt files readed from hdfs.
train = train.decode() test = test.decode() ffm_model = xl.create_ffm() ffm_model.setTrain(train) ffm_model.fit(param,str)
where str is the hdfs path to our production folder.
I am sorry if the issue is badly explained and/or contextualized , is the first time I report something as an issue to the library's owner.
What have we tried? import subprocess cat = subprocess.Popen(["hadoop", "fs", "-cat", str], stdout=subprocess.PIPE) ffm_model.fit(param,cat)
The file specified in str, already exists but is empty.
The text was updated successfully, but these errors were encountered:
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In the model training step, specifically when we are standing in the "fit" step, we use the command and it crashes the kernel.
train and test are txt files readed from hdfs.
train = train.decode()
test = test.decode()
ffm_model = xl.create_ffm()
ffm_model.setTrain(train)
ffm_model.fit(param,str)
where str is the hdfs path to our production folder.
I am sorry if the issue is badly explained and/or contextualized , is the first time I report something as an issue to the library's owner.
What have we tried?
import subprocess
cat = subprocess.Popen(["hadoop", "fs", "-cat", str], stdout=subprocess.PIPE)
ffm_model.fit(param,cat)
The file specified in str, already exists but is empty.
The text was updated successfully, but these errors were encountered: