Popularity
1.9
Growing
Activity
0.0
Stable
1
3
0
Monthly Downloads: 6
Programming language: Haskell
License: BSD 3-clause "New" or "Revised" License
fei-dataiter alternatives and similar packages
Based on the "fei" category.
Alternatively, view fei-dataiter alternatives based on common mentions on social networks and blogs.
WorkOS - The modern identity platform for B2B SaaS
The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
Promo
workos.com
Do you think we are missing an alternative of fei-dataiter or a related project?
Popular Comparisons
README
mxnet-dataiter
Here is an example of making a Conduit from MNIST dataset.
mnistIter (add @"image" "data/train-images-idx3-ubyte" $
add @"label" "data/train-labels-idx1-ubyte" $
add @"batch_size" 128
nil) :: ConduitData IO (NDArray Float, NDArray Float)
The first argument is provides named parameters for the MXNet Data Iterators. Detailed specification can be found in MXNet API 's python document.
Below is a snapshot of current support in this package.
type CSVIter_Args =
'[ "data_csv" := String, "data_shape" := [Int], "label_csv" := String, "label_shape" := [Int]
, "batch_size" := Int, "round_batch" := Bool, "prefetch_buffer" := Integer, "dtype" := String]
type MNISTIter_Args =
'[ "image" := String, "label" := String, "batch_size" := Int, "shuffle" := Bool, "flat" := Bool
, "seed" := Int, "silent" := Bool, "num_parts" := Int, "part_index" := Int
, "prefetch_buffer" := Integer, "dtype" := String]
type ImageRecordIter_Args =
'[ "path_imglist" := String, "path_imgrec" := String, "path_imgidx" := String, "aug_seq" := String
, "label_width" := Int, "data_shape" := [Int], "preprocess_threads" := Int, "verbose" := Bool
, "num_parts" := Int, "part_index" := Int, "shuffle_chunk_size" := Integer
, "shuffle_chunk_seed" := Int, "shuffle" := Bool, "seed" := Int, "batch_size" := Int
, "round_batch" := Bool, "prefetch_buffer" := Integer, "dtype" := String, "resize" := Int
, "rand_crop" := Bool, "max_rotate_angle" := Int, "max_aspect_ratio" := Float
, "max_shear_ratio" := Float, "max_crop_size" := Int, "min_crop_size" := Int
, "max_random_scale" := Float, "min_random_scale" := Float, "max_img_size" := Float
, "min_img_size" := Float, "random_h" := Int, "random_s" := Int, "random_l" := Int, "rotate" := Int
, "fill_value" := Int, "inter_method" := Int, "pad" := Int, "mirror" := Bool, "rand_mirror" := Bool
, "mean_img" := String, "mean_r" := Float, "mean_g" := Float, "mean_b" := Float, "mean_a" := Float
, "std_r" := Float, "std_g" := Float, "std_b" := Float, "std_a" := Float, "scale" := Float
, "max_random_contrast" := Float, "max_random_illumination" := Float]
type ImageDetRecordIter_Args =
'[ "path_imglist" := String, "path_imgrec" := String, "aug_seq" := String, "label_width" := Int
, "data_shape" := [Int], "preprocess_threads" := Int, "verbose" := Bool, "num_parts" := Int
, "part_index" := Int, "shuffle_chunk_size" := Integer, "shuffle_chunk_seed" := Int
, "label_pad_width" := Int, "label_pad_value" := Float, "shuffle" := Bool, "seed" := Int
, "batch_size" := Int, "round_batch" := Bool, "prefetch_buffer" := Integer, "dtype" := String
, "resize" := Int, "rand_crop_prob" := Float, "min_crop_scales" := [Float]
, "max_crop_scales" := [Float], "min_crop_aspect_ratios" := [Float]
, "max_crop_aspect_ratios" := [Float], "min_crop_overlaps" := [Float], "max_crop_overlaps" := [Float]
, "min_crop_sample_coverages" := [Float], "max_crop_sample_coverages" := [Float]
, "min_crop_object_coverages" := [Float], "max_crop_object_coverages" := [Float]
, "num_crop_sampler" := Int, "crop_emit_mode" := String, "emit_overlap_thresh" := Float
, "max_crop_trials" := [Int], "rand_pad_prob" := Float, "max_pad_scale" := Float
, "max_random_hue" := Int, "random_hue_prob" := Float, "max_random_saturation" := Int
, "random_saturation_prob" := Float, "max_random_illumination" := Int
, "random_illumination_prob" := Float, "max_random_contrast" := Float, "random_contrast_prob" := Float
, "rand_mirror_prob" := Float, "fill_value" := Int, "inter_method" := Int, "resize_mode" := String
, "mean_img" := String, "mean_r" := Float, "mean_g" := Float, "mean_b" := Float, "mean_a" := Float
, "std_r" := Float, "std_g" := Float, "std_b" := Float, "std_a" := Float, "scale" := Float]
type ImageRecordUInt8Iter_Args =
'[ "path_imglist" := String, "path_imgrec" := String, "path_imgidx" := String, "aug_seq" := String
, "label_width" := Int, "data_shape" := [Int], "preprocess_threads" := Int, "verbose" := Bool
, "num_parts" := Int, "part_index" := Int, "shuffle_chunk_size" := Integer
, "shuffle_chunk_seed" := Int, "shuffle" := Bool, "seed" := Int, "batch_size" := Int
, "round_batch" := Bool, "prefetch_buffer" := Integer, "dtype" := String, "resize" := Int
, "rand_crop" := Bool, "max_rotate_angle" := Int, "max_aspect_ratio" := Float
, "max_shear_ratio" := Float, "max_crop_size" := Int, "min_crop_size" := Int
, "max_random_scale" := Float, "min_random_scale" := Float, "max_img_size" := Float
, "min_img_size" := Float, "random_h" := Int, "random_s" := Int, "random_l" := Int, "rotate" := Int
, "fill_value" := Int, "inter_method" := Int, "pad" := Int]
type LibSVMIter_Args =
'[ "data_libsvm" := String, "data_shape" := [Int], "label_libsvm" := String, "label_shape" := [Int]
, "num_parts" := Int, "part_index" := Int, "batch_size" := Int, "round_batch" := Bool
, "prefetch_buffer" := Integer, "dtype" := String]