深度学习产生种子数据选择问题

时间:2019-06-14 12:24:06

标签: r

图书馆(keras)     库(字符串)     路径<-get_file(       “ nietzsche.txt”,       origin =“ https://s3.amazonaws.com/text-datasets/nietzsche.txt”     ) 这是问题     文字<-tolower(readChar(path,file.info(path)$ size))     cat(“ Corpus length:”,nchar(text),“ \ n”)

  # Select a text seed at random
  start_index <- sample(1:(nchar(text) - maxlen - 1), 1)  
  seed_text <- str_sub(text, start_index, start_index + maxlen - 1)

  cat("--- Generating with seed:", seed_text, "\n\n")

  for (temperature in c(0.2, 0.5, 1.0, 1.2)) {

    cat("------ temperature:", temperature, "\n")
    cat(seed_text, "\n")

    generated_text <- seed_text

    # We generate 400 characters
    for (i in 1:400) {

      sampled <- array(0, dim = c(1, maxlen, length(chars)))
      generated_chars <- strsplit(generated_text, "")[[1]]
      for (t in 1:length(generated_chars)) {
        char <- generated_chars[[t]]
        sampled[1, t, char_indices[[char]]] <- 1
      }

      preds <- model %>% predict(sampled, verbose = 0)
      next_index <- sample_next_char(preds[1,], temperature)
      next_char <- chars[[next_index]]

      generated_text <- paste0(generated_text, next_char)
      generated_text <- substring(generated_text, 2)

      cat(next_char)
    }
    cat("\n\n")
  }
}

文本生成深度学习代码。我想使用我指定的文本,而不是在这里选择随机文本种子。如何修改?另外,当我第一次导入文件时,真的需要在get_file()中编写文本并指定文本吗?

0 个答案:

没有答案