data-handling

问题 I have a large dataset that I would like to use for training in Tensorflow. The data is stored in compressed numpy format (using numpy.savez_compressed ). There are variable numbers of images per file due to the way they are produced. Currently I use a Keras Sequence based generator object to train, but I'd like to move entirely to Tensorflow without Keras. I'm looking at the Dataset API on the TF website, but it is not obvious how I might use this to read numpy data. My first idea was this

问题 I have a large dataset that I would like to use for training in Tensorflow. The data is stored in compressed numpy format (using numpy.savez_compressed ). There are variable numbers of images per file due to the way they are produced. Currently I use a Keras Sequence based generator object to train, but I'd like to move entirely to Tensorflow without Keras. I'm looking at the Dataset API on the TF website, but it is not obvious how I might use this to read numpy data. My first idea was this

问题 I'm using Python, and I have a dataset of 6 columns, R, Rc, J, T, Ca and Cb. I need to "aggregate" on the columns "R" then "J", so that for each R, each row is a unique "J". Rc is a characteristic of R. Ca and Cb are characteristics of T. It will make more sense looking at the table below. I need to go from: #______________________ ________________________________________________________________ #| R Rc J T Ca Cb| |# R Rc J Ca(T=1) Ca(T=2) Ca(T=3) Cb(T=1) Cb(T=2) Cb(T=3)| #| a p 1 1 x d| |# a

问题 I'm using Python, and I have a dataset of 6 columns, R, Rc, J, T, Ca and Cb. I need to "aggregate" on the columns "R" then "J", so that for each R, each row is a unique "J". Rc is a characteristic of R. Ca and Cb are characteristics of T. It will make more sense looking at the table below. I need to go from: #______________________ ________________________________________________________________ #| R Rc J T Ca Cb| |# R Rc J Ca(T=1) Ca(T=2) Ca(T=3) Cb(T=1) Cb(T=2) Cb(T=3)| #| a p 1 1 x d| |# a

问题 I am recreating the entire standard C library and I'm working on an implementation for strle n that I would like to be the basis of all my other str functions. My current implementation is as follows: int ft_strlen(char const *str) { int length; length = 0; while(str[length] != '\0' || str[length + 1] == '\0') length++; return length; } My question is that when I pass a str like: char str[6] = "hi!"; As expected, the memory reads: ['h']['i']['!']['\0']['\0']['\0']['\0'] If you look at my

问题 I am recreating the entire standard C library and I'm working on an implementation for strle n that I would like to be the basis of all my other str functions. My current implementation is as follows: int ft_strlen(char const *str) { int length; length = 0; while(str[length] != '\0' || str[length + 1] == '\0') length++; return length; } My question is that when I pass a str like: char str[6] = "hi!"; As expected, the memory reads: ['h']['i']['!']['\0']['\0']['\0']['\0'] If you look at my