tfdatasets (version 1.9)

dataset_filter: Filter a dataset by a predicate

Description

Filter a dataset by a predicate

Usage

dataset_filter(dataset, predicate)

Arguments

dataset

A dataset

predicate

A function mapping a nested structure of tensors (having shapes and types defined by output_shapes() and output_types() to a scalar tf$bool tensor.

Value

A dataset composed of records that matched the predicate.

Details

Note that the functions used inside the predicate must be tensor operations (e.g. tf$not_equal, tf$less, etc.). R generic methods for relational operators (e.g. <, >, <=, etc.) and logical operators (e.g. !, &, |, etc.) are provided so you can use shorthand syntax for most common comparisions (this is illustrated by the example below).

See Also

Other dataset methods: dataset_batch, dataset_cache, dataset_concatenate, dataset_decode_delim, dataset_interleave, dataset_map_and_batch, dataset_map, dataset_padded_batch, dataset_prefetch_to_device, dataset_prefetch, dataset_repeat, dataset_shuffle_and_repeat, dataset_shuffle, dataset_skip, dataset_take

Examples

# NOT RUN {
dataset <- text_line_dataset("mtcars.csv", record_spec = mtcars_spec) %>%
  dataset_filter(function(record) {
    record$mpg >= 20
})

dataset <- text_line_dataset("mtcars.csv", record_spec = mtcars_spec) %>%
  dataset_filter(function(record) {
    record$mpg >= 20 & record$cyl >= 6L
  })

# }
# NOT RUN {
# }

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