Saving and restoring shiny app having multiple tabs

I can able to save the state of the app but when I restore it, it's giving message as Restored session but I didn't get the app as in saved state.
Following is the example code I have used to save and restore. file will stored in .rds format

library(shinydashboard)
library(shinyWidgets)
library(plotly)
library(DT)
library(corrr)
library(dplyr)
library(Robyn)
library(qgraph)
library(shinyjs)
library(utils)
library(tools)
library(stringi)

ui <- function(request){fluidPage(
  useShinyjs(),
  titlePanel("APP"),
  useShinydashboard(),
  fileInput(
    "file",
    "Choose CSV File",
    accept = c("text/csv",
               "text/comma-separated-values,text/plain",
               ".csv")
  ),
  checkboxInput("header",
                "Header",
                value = TRUE),
  radioButtons(
    "disp",
    "Display",
    choices = c(Head = "head",
                All = "all"),
    selected = "head"
  ),
  fileInput("restore_bookmark", 
            "Restore Session", 
            multiple = FALSE 
            #accept = ".rds"),
  ),
  #  SIDEBAR --------------------------------------------------------
  navlistPanel(
    widths = c(2,10),
    #  Input data ---------------------------------------------------
    tabPanel('Input data',
             fluidRow(
               box(width = 12,
                   dataTableOutput('table'),
                   title = 'Raw data'),
               box(width = 6,
                   dataTableOutput('miss'),
                   title = 'Missing percentage table'),
               box(width = 6,
                   dataTableOutput('dtype'),
                   title = 'Datatype')
             )
    ),
    #  Basic EDA ----------------------------------------------------
    tabPanel('Basic EDA',
             fluidRow(
               column(width = 7,
                      box(
                        width = NULL,
                        plotlyOutput('correlation',
                                     height = 450),
                        title = 'Correlation plot',
                        style = 'overflow-y:scroll; max-height: 600px'
                      ),
                      box(
                        width = NULL,
                        selectInput(
                          inputId = 'x_axis',
                          label = 'X-axis',
                          'Names',
                          multiple = FALSE
                        ),
                        selectInput(
                          inputId = 'y_axis',
                          label = 'Y-axis',
                          'Names',
                          multiple = FALSE
                        )
                      )
               ),
               column(width = 5,
                      box(
                        width = NULL,
                        plotOutput('network',
                                   height = 250),
                        title = 'Correlation network',
                        sliderInput('netslider',
                                    'Min corr',
                                    min = 0,
                                    max = 1,
                                    value = 0.3)
                      ),
                      box(
                        width = NULL,
                        plotlyOutput('scatter',
                                     height = 300),
                        title = 'Scatter plot'
                      )
               )
             ),
             actionButton("save_inputs", 
                          'Save Session', 
                          icon = icon("download"))
    )
  )
)}

server <- function(input, output, session) {
  #  Session saving --------------------------------------------------
  latestBookmarkURL <- reactiveVal()
  
  onBookmarked(
    fun = function(url) { #url
      latestBookmarkURL(parseQueryString(url))
    }
  )
  
  onRestored(function(state) {
    showNotification(paste("Restored session:",
                           basename(state$dir)),
                     duration = 10,
                     type = "message")
  })
  observeEvent(input$save_inputs, {
    showModal(modalDialog(
      title = "Session Name",
      textInput("session_name", 
                "Please enter a session name (optional):"),
      footer = tagList(
        modalButton("Cancel"),
        downloadButton("download_inputs", "OK")
      )
    ))
  }, ignoreInit = TRUE)
  # SAVE SESSION ---------------------------------------------------------------
  output$download_inputs <- downloadHandler(
    filename = function() {
      removeModal()
      session$doBookmark()
      
      if (input$session_name != "") {
        
        tmp_session_name <- sub("\\.rds$", "", input$session_name)
        tmp_session_name <- stri_replace_all(tmp_session_name, "", regex = "[^[:alnum:]]")
        tmp_session_name <- paste0(tmp_session_name, ".rds")
        print(tmp_session_name)
      } else {
        paste(req(latestBookmarkURL()), "rds", sep = ".")
        
      }
    },
    print(latestBookmarkURL()),
    
    content = function(file) {
      file.copy(from = file.path(
        ".",
        "shiny_bookmarks",
        req(latestBookmarkURL()),
        "input.rds"
        #paste0(ses_name(),'.rds')
      ),
      to = file)
      
    }
  )
  # LOAD SESSION ---------------------------------------------------------------
  observeEvent(input$restore_bookmark, {
      sessionName <- file_path_sans_ext(input$restore_bookmark$name)
      targetPath <- file.path(".", "shiny_bookmarks", sessionName, "input.rds")
      restoreURL <- paste0(session$clientData$url_protocol, "//", 
                           session$clientData$url_hostname, ":", 
                           session$clientData$url_port, 
                           session$clientData$url_pathname, 
                           "?_state_id_=", 
                           sessionName)
      
      # redirect user to restoreURL
      runjs(sprintf("window.location = '%s';", restoreURL))
      })
    dataset <- reactive({
      read.csv("./Dataset/data.csv")
    })
    observe(
      output$table <- DT::renderDataTable({
        if (input$disp == 'head') {
          head(dataset())
        }
        else{
          dataset()
        }
      })
    )
    # Missing percentage table ---------------------------------------
    output$miss <- renderDataTable({
      miss_dataframe = data.frame(names(dataset()),
                                  (colMeans(is.na(dataset())))*100)
      setNames(miss_dataframe,c("Variable","Missing percentage"))
    })
    
    # Datatype table -------------------------------------------------
    output$dtype <- renderDataTable({
      dtype_dataframe = data.frame(names(dataset()),
                                   sapply(dataset(),class))
      setNames(dtype_dataframe,c('Variables','Data type'))
    })
    # Correlation plot -----------------------------------------------------------
    sub_dataset <- reactive({
      subset(dataset(),
             select = sapply(dataset(),
                             class) != 'character',
             drop = TRUE)
    })
    output$correlation <- renderPlotly({
      cor_sub <- cor(sub_dataset())
      plot_ly(x = names(sub_dataset()),
              y = names(sub_dataset()),
              z = cor_sub,
              type = 'heatmap',
              colors = colorRamp(c("red", "green")),
              zmin = -1,
              zmax = 1,
              width = 600,
              height = 500) %>%
        layout(title = paste('Correlation plot'))
    })
    # Correlation network --------------------------------------------
    output$network <- renderPlot({
      qgraph(cor(sub_dataset()),
             shape = 'ellipse',
             overlay = TRUE,
             layout = 'spring',
             minimum = input$netslider,
             vsize = 8,
             labels = TRUE,
             nodeNames = colnames(sub_dataset()),
             details = T,
             legend = T,
             legend.cex = 0.4, 
             GLratio = 1.3,
             label.prop = 1.5
      )
    })
    # scatter plot ---------------------------------------------------------------
    observe({
      updateSelectInput(inputId = "x_axis",choices = names(dataset()))
      updateSelectInput(inputId = "y_axis",choices = names(dataset()))
    })
    
    x_axis <- reactive({
      dataset()[,input$x_axis]
    })
    y_axis <- reactive({
      dataset()[,input$y_axis]
    })
    
    output$scatter <- renderPlotly({
      plot_ly(dataset(), x = x_axis(),
              y = y_axis(),
              type = 'scatter',
              mode = 'markers') %>% 
        layout(title = paste("Scatter plot"))
    })

}
enableBookmarking(store = 'server')
shinyApp(ui = ui, server = server)

Here is the output of dput(head(read.csv("./Dataset/data.csv")))

"2020-01-04", "2020-01-05", "2020-01-06"), CRM_web_visits = c(72531L, 
74512L, 102819L, 79954L, 36726L, 35314L), DIRECT.NOSOURCE._web_visits = c(170419L, 
201539L, 182053L, 174788L, 169971L, 191405L), DISPLAY_ad_spend = c(5974.94, 
6791.05, 6475.65, 6977.87, 7184.88, 7282.68), DISPLAY_impression = c(5195802L, 
6419806L, 6851564L, 7465473L, 8542588L, 8856138L), EARNEDSOCIAL_web_visits = c(8468L, 
13646L, 17214L, 15885L, 16675L, 12983L), ORGANICSEARCH_web_visits = c(161203L, 
228753L, 228830L, 223210L, 219383L, 228044L), OTHERS_web_visits = c(709L, 
1561L, 1698L, 1541L, 1448L, 1685L), PAIDSEARCH_ad_spend = c(83432.41, 
103529.01, 102688.27, 109478.01, 109835.46, 102679.45), PAIDSEARCH_impression = c(9614558L, 
10974797L, 11177990L, 12129001L, 11936305L, 11635109L), PAIDSOCIAL_ad_spend = c(11538.3, 
8512.8, 8805.4, 11433.27, 11323.38, 11344.67), PAIDSOCIAL_impression = c(12212695L, 
8692666L, 8456129L, 9878943L, 10315930L, 11530289L), PARTNERSHIPMARKETING_ad_spend = c(63636.11, 
6130.62, 8362.65, 6208.49, 6114.99, 5079.42), PARTNERSHIPMARKETING_click = c(72785L, 
119086L, 113134L, 92235L, 92232L, 81516L), REFERRINGSITES_web_visits = c(7955L, 
12286L, 13948L, 12509L, 10906L, 11595L), Overall_Revenue = c(941026.4, 
1293915.56, 1485440.42, 1395251.29, 1358603.2, 1342233.84)), row.names = c(NA, 
6L), class = "data.frame")

Any suggestions will be appreciated.

Thanks in advance