tf.io.decode

Convert CSV records to tensors. Each column maps to one tensor.

tf.io.decode_csv(
    records, record_defaults, field_delim=',', use_quote_delim=True,
    na_value='', select_cols=None, name=None
)

Used in the notebooks

Used in the tutorials
Load CSV data Robust machine learning on streaming data using Kafka and Tensorflow-IO

RFC 4180 format is expected for the CSV records. (https://tools.ietf.org/html/rfc4180) Note that we allow leading and trailing spaces with int or float field.

Args
`records`	A `Tensor` of type `string`. Each string is a record/row in the csv and all records should have the same format.
`record_defaults`	A list of `Tensor` objects with specific types. Acceptable types are `float32`, `float64`, `int32`, `int64`, `string`. One tensor per column of the input record, with either a scalar default value for that column or an empty vector if the column is required.
`field_delim`	An optional `string`. Defaults to `","`. char delimiter to separate fields in a record.
`use_quote_delim`	An optional `bool`. Defaults to `True`. If false, treats double quotation marks as regular characters inside of the string fields (ignoring RFC 4180, Section 2, Bullet 5).
`na_value`	Additional string to recognize as NA/NaN.
`select_cols`	Optional sorted list of column indices to select. If specified, only this subset of columns will be parsed and returned.
`name`	A name for the operation (optional).

Returns
A list of `Tensor` objects. Has the same type as `record_defaults`. Each tensor will have the same shape as records.

Raises
`ValueError`	If any of the arguments is malformed.

TensorFlow

tf.io / decode_bmp

Used in the notebooks

Args

Returns

Raises

TensorFlow

tf

tf.audio

tf.autograph

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tf.io / decode_bmp

Used in the notebooks

Args

Returns

Raises