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tf.compat.v1.data.experimental.CsvDataset

A Dataset comprising lines from one or more CSV files.

Inherits From: Dataset, Dataset

filenames A tf.string tensor containing one or more filenames.
record_defaults A list of default values for the CSV fields. Each item in the list is either a valid CSV DType (float32, float64, int32, int64, string), or a Tensor object with one of the above types. One per column of CSV data, with either a scalar Tensor default value for the column if it is optional, or DType or empty Tensor if required. If both this and select_columns are specified, these must have the same lengths, and column_defaults is assumed to be sorted in order of increasing column index. If both this and 'exclude_cols' are specified, the sum of lengths of record_defaults and exclude_cols should equal the total number of columns in the CSV file.
compression_type (Optional.) A tf.string scalar evaluating to one of "" (no compression), "ZLIB", or "GZIP". Defaults to no compression.
buffer_size (Optional.) A tf.int64 scalar denoting the number of bytes to buffer while reading files. Defaults to 4MB.
header (Optional.) A tf.bool scalar indicating whether the CSV file(s) have header line(s) that should be skipped when parsing. Defaults to False.
field_delim (Optional.) A tf.string scalar containing the delimiter character that separates fields in a record. Defaults to ",".
use_quote_delim (Optional.) A tf.bool scalar. If False, treats double quotation marks as regular characters inside of string fields (ignoring RFC 4180, Section 2, Bullet 5). Defaults to True.
na_value (Optional.) A tf.string scalar indicating a value that will be treated as NA/NaN.
select_cols (Optional.) A sorted list of column indices to select from the input data. If specified, only this subset of columns will be parsed. Defaults to parsing all columns. At most one of select_cols and exclude_cols can be specified.

element_spec The type specification of an element of this dataset.

dataset = tf.data.Dataset.from_tensor_slices([1, 2, 3])
dataset.element_spec
TensorSpec(shape=(), dtype=tf.int32, name=None)

For more information, read this guide.

output_clas