node_modules/@tensorflow/tfjs-data/dist/tf-data.js
/**
         * Create a `CSVDataset`.
         *
         * @param input A `DataSource` providing a chunked, UTF8-encoded byte stream.
         * @param csvConfig (Optional) A CSVConfig object that contains configurations
         *     of reading and decoding from CSV file(s).
         *
         *     hasHeader: (Optional) A boolean value that indicates whether the first
         *     row of provided CSV file is a header line with column names, and should
         *     not be included in the data. Defaults to `true`.
         *
         *     columnNames: (Optional) A list of strings that corresponds to
         *     the CSV column names, in order. If provided, it ignores the column
         *     names inferred from the header row. If not provided, infers the column
         *     names from the first row of the records. If hasHeader is false and
         *     columnNames is not provided, this method throws an error.
         *
         *     columnConfigs: (Optional) A dictionary whose key is column names, value
         *     is an object stating if this column is required, column's data type,
         *     default value, and if this column is label. If provided, keys must
         *     correspond to names provided in columnNames or inferred from the file
         *     header lines. If isLabel is true any column, returns an array of two
         *     items: the first item is a dict of features key/value pairs, the second
         *     item is a dict of labels key/value pairs. If no feature is marked as
         *     label, returns a dict of features only.
         *
         *     configuredColumnsOnly (Optional) If true, only columns provided in
         *     columnConfigs will be parsed and provided during iteration.
         *
         *     delimiter (Optional) The string used to parse each line of the input
         *     file. Defaults to `,`.
         */


@param input A `DataSource` providing a chunked, UTF8-encoded byte stream.
@param csvConfig (Optional) A CSVConfig object that contains configurations
of reading and decoding from CSV file(s).

(Optional) A boolean value that indicates whether the first
row of provided CSV file is a header line with column names, and should
not be included in the data. Defaults to `true`.

(Optional) A list of strings that corresponds to
the CSV column names, in order. If provided, it ignores the column
names inferred from the header row. If not provided, infers the column
names from the first row of the records. If hasHeader is false and
columnNames is not provided, this method throws an error.

(Optional) A dictionary whose key is column names, value
is an object stating if this column is required, column's data type,
default value, and if this column is label. If provided, keys must
correspond to names provided in columnNames or inferred from the file
header lines. If isLabel is true any column, returns an array of two
items: the first item is a dict of features key/value pairs, the second
item is a dict of labels key/value pairs. If no feature is marked as
label, returns a dict of features only.

configuredColumnsOnly (Optional) If true, only columns provided in
columnConfigs will be parsed and provided during iteration.

delimiter (Optional) The string used to parse each line of the input
file. Defaults to `,`.
@param input A ` DataSource ` providing a chunked UTF8 - encoded byte stream . @param csvConfig ( Optional ) A CSVConfig object that contains configurations of reading and decoding from CSV file ( s ) . ( Optional ) A boolean value that indicates whether the first row of provided CSV file is a header line with column names and should not be included in the data . Defaults to ` true ` . ( Optional ) A list of strings that corresponds to the CSV column names in order . If provided it ignores the column names inferred from the header row . If not provided infers the column names from the first row of the records . If hasHeader is false and columnNames is not provided this method throws an error . ( Optional ) A dictionary whose key is column names value is an object stating if this column is required column ' s data type default value and if this column is label . If provided keys must correspond to names provided in columnNames or inferred from the file header lines . If isLabel is true any column returns an array of two items : the first item is a dict of features key / value pairs the second item is a dict of labels key / value pairs . If no feature is marked as label returns a dict of features only . configuredColumnsOnly ( Optional ) If true only columns provided in columnConfigs will be parsed and provided during iteration . delimiter ( Optional ) The string used to parse each line of the input file . Defaults to ` ` .
function CSVDataset(input, csvConfig) {
            var _this = _super.call(this) || this;
            _this.input = input;
            _this.hasHeader = true;
            _this.fullColumnNames = null;
            _this.columnNamesValidated = false;
            _this.columnConfigs = null;
            _this.configuredColumnsOnly = false;
            _this.delimiter = ',';
            _this.base = new TextLineDataset(input);
            if (!csvConfig) {
                csvConfig = {};
            }
            _this.hasHeader = csvConfig.hasHeader === false ? false : true;
            _this.fullColumnNames = csvConfig.columnNames;
            _this.columnConfigs = csvConfig.columnConfigs;
            _this.configuredColumnsOnly = csvConfig.configuredColumnsOnly;
            _this.delimiter = csvConfig.delimiter ? csvConfig.delimiter : ',';
            return _this;
        }
function CSVDataset ( input , csvConfig ) { var _this = _super . call ( this ) || this ; _this . input = input ; _this . hasHeader = true ; _this . fullColumnNames = null ; _this . columnNamesValidated = false ; _this . columnConfigs = null ; _this . configuredColumnsOnly = false ; _this . delimiter = ',' ; _this . base = new TextLineDataset ( input ) ; if ( ! csvConfig ) { csvConfig = { } ; } _this . hasHeader = csvConfig . hasHeader === false ? false : true ; _this . fullColumnNames = csvConfig . columnNames ; _this . columnConfigs = csvConfig . columnConfigs ; _this . configuredColumnsOnly = csvConfig . configuredColumnsOnly ; _this . delimiter = csvConfig . delimiter ? csvConfig . delimiter : ',' ; return _this ; }
Create a `CSVDataset`.
Create a ` CSVDataset ` .