| Project |
RefactoringType |
RefactoringLink |
CommitLink |
TrueRefactoring? |
Description |
File |
| lene/nn-wtf |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : MNISTGraph, verbose : Any, learning_rate : Any, layer_sizes : Any, train_dir : Any, input_size : Any, output_size : Any] to [self : MNISTGraph, input_size : Any, layer_sizes : Any, output_size : Any, learning_rate : Any, verbose : Any, train_dir : Any] in method package __init__(self MNISTGraph, input_size Any, layer_sizes Any, output_size Any, learning_rate Any, verbose Any, train_dir Any) : void from class org.nn_wtf.mnist_graph.MNISTGraph |
nn_wtf/mnist_graph.py |
| tsurumeso/waifu2x-chainer |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [src : Any, model : Any, cfg : Any] to [cfg : Any, src : Any, model : Any] in method package denoise_image(cfg Any, src Any, model Any) : void from class org.waifu2x.PyDummyClass1 |
waifu2x.py |
| tsurumeso/waifu2x-chainer |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [src : Any, scale_model : Any, cfg : Any, alpha_model : Any] to [cfg : Any, src : Any, scale_model : Any, alpha_model : Any] in method package upscale_image(cfg Any, src Any, scale_model Any, alpha_model Any) : void from class org.waifu2x.PyDummyClass1 |
waifu2x.py |
| tsurumeso/waifu2x-chainer |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [model : Any, src : Any, block_size : Any, batch_size : Any] to [src : Any, model : Any, block_size : Any, batch_size : Any] in method package blockwise(src Any, model Any, block_size Any, batch_size Any) : void from class org.lib.reconstruct.PyDummyClass1 |
lib/reconstruct.py |
| tsurumeso/waifu2x-chainer |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [model : Any, src : Any, tta_level : Any, block_size : Any, batch_size : Any] to [src : Any, model : Any, tta_level : Any, block_size : Any, batch_size : Any] in method package scale_tta(src Any, model Any, tta_level Any, block_size Any, batch_size Any) : void from class org.lib.reconstruct.PyDummyClass1 |
lib/reconstruct.py |
| tsurumeso/waifu2x-chainer |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [model : Any, src : Any, tta_level : Any, block_size : Any, batch_size : Any] to [src : Any, model : Any, tta_level : Any, block_size : Any, batch_size : Any] in method package noise_tta(src Any, model Any, tta_level Any, block_size Any, batch_size Any) : void from class org.lib.reconstruct.PyDummyClass1 |
lib/reconstruct.py |
| tsurumeso/waifu2x-chainer |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [model : Any, src : Any, block_size : Any, batch_size : Any] to [src : Any, model : Any, block_size : Any, batch_size : Any] in method package scale(src Any, model Any, block_size Any, batch_size Any) : void from class org.lib.reconstruct.PyDummyClass1 |
lib/reconstruct.py |
| tsurumeso/waifu2x-chainer |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [model : Any, src : Any, block_size : Any, batch_size : Any] to [src : Any, model : Any, block_size : Any, batch_size : Any] in method package noise(src Any, model Any, block_size Any, batch_size Any) : void from class org.lib.reconstruct.PyDummyClass1 |
lib/reconstruct.py |
| tsurumeso/waifu2x-chainer |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [model : Any, src : Any, cfg : Any] to [src : Any, model : Any, cfg : Any] in method package denoise_image(src Any, model Any, cfg Any) : void from class org.waifu2x.PyDummyClass1 |
waifu2x.py |
| tsurumeso/waifu2x-chainer |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [model : Any, src : Any, cfg : Any] to [src : Any, model : Any, cfg : Any] in method package upscale_image(src Any, model Any, cfg Any) : void from class org.waifu2x.PyDummyClass1 |
waifu2x.py |
| pierluigiferrari/ssd_keras |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : BoxFilter, image_height : Any, image_width : Any, labels : Any] to [self : BoxFilter, labels : Any, image_height : Any, image_width : Any] in method package __call__(self BoxFilter, labels Any, image_height Any, image_width Any) : void from class org.data_generator.object_detection_2d_image_boxes_validation_utils.BoxFilter |
data_generator/object_detection_2d_image_boxes_validation_utils.py |
| pierluigiferrari/ssd_keras |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : ImageValidator, image_height : Any, image_width : Any, labels : Any] to [self : ImageValidator, labels : Any, image_height : Any, image_width : Any] in method package __call__(self ImageValidator, labels Any, image_height Any, image_width Any) : void from class org.data_generator.object_detection_2d_image_boxes_validation_utils.ImageValidator |
data_generator/object_detection_2d_image_boxes_validation_utils.py |
| autonomio/talos |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : AutoScan, task : Any, max_param_values : Any, experiment_name : Any] to [self : AutoScan, task : Any, experiment_name : Any, max_param_values : Any] in method package __init__(self AutoScan, task Any, experiment_name Any, max_param_values Any) : void from class org.talos.autom8.autoscan.AutoScan |
talos/autom8/autoscan.py |
| tflearn/tflearn |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [x : Any, channel_shared : Any, weights_init : Any, restore : Any, trainable : Any, reuse : Any, scope : Any, name : Any] to [x : Any, channel_shared : Any, weights_init : Any, trainable : Any, restore : Any, reuse : Any, scope : Any, name : Any] in method package prelu(x Any, channel_shared Any, weights_init Any, trainable Any, restore Any, reuse Any, scope Any, name Any) : void from class org.tflearn.activations.PyDummyClass1 |
tflearn/activations.py |
| uber/ludwig |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : SequenceEmbedEncoder, vocab : Any, representation : Any, embedding_size : Any, embeddings_trainable : Any, pretrained_embeddings : Any, embeddings_on_cpu : Any, initializer : Any, reduce_output : Any, regularizer : Any, dropout_rate : Any] to [self : SequenceEmbedEncoder, vocab : Any, representation : Any, embedding_size : Any, embeddings_trainable : Any, pretrained_embeddings : Any, embeddings_on_cpu : Any, initializer : Any, regularizer : Any, dropout_rate : Any, reduce_output : Any] in method package __init__(self SequenceEmbedEncoder, vocab Any, representation Any, embedding_size Any, embeddings_trainable Any, pretrained_embeddings Any, embeddings_on_cpu Any, initializer Any, regularizer Any, dropout_rate Any, reduce_output Any) : void from class org.ludwig.models.modules.sequence_encoders.SequenceEmbedEncoder |
ludwig/models/modules/sequence_encoders.py |
| uber/ludwig |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : LudwigModel, data_df : Any, data_train_df : Any, data_validation_df : Any, data_test_df : Any, data_csv : Any, data_train_csv : Any, data_validation_csv : Any, data_test_csv : Any, data_hdf5 : Any, data_train_hdf5 : Any, data_validation_hdf5 : Any, data_test_hdf5 : Any, data_dict : Any, data_train_dict : Any, data_test_dict : Any, data_validation_dict : Any, train_set_metadata_json : Any, experiment_name : Any, model_name : Any, model_load_path : Any, model_resume_path : Any, skip_save_model : Any, skip_save_progress : Any, skip_save_log : Any, skip_save_processed_input : Any, output_directory : Any, gpus : Any, gpu_fraction : Any, use_horovod : Any, random_seed : Any, logging_level : Any, debug : Any] to [self : LudwigModel, data_df : Any, data_train_df : Any, data_validation_df : Any, data_test_df : Any, data_csv : Any, data_train_csv : Any, data_validation_csv : Any, data_test_csv : Any, data_hdf5 : Any, data_train_hdf5 : Any, data_validation_hdf5 : Any, data_test_hdf5 : Any, data_dict : Any, data_train_dict : Any, data_validation_dict : Any, data_test_dict : Any, train_set_metadata_json : Any, experiment_name : Any, model_name : Any, model_load_path : Any, model_resume_path : Any, skip_save_model : Any, skip_save_progress : Any, skip_save_log : Any, skip_save_processed_input : Any, output_directory : Any, gpus : Any, gpu_fraction : Any, use_horovod : Any, random_seed : Any, logging_level : Any, debug : Any] in method package train(self LudwigModel, data_df Any, data_train_df Any, data_validation_df Any, data_test_df Any, data_csv Any, data_train_csv Any, data_validation_csv Any, data_test_csv Any, data_hdf5 Any, data_train_hdf5 Any, data_validation_hdf5 Any, data_test_hdf5 Any, data_dict Any, data_train_dict Any, data_validation_dict Any, data_test_dict Any, train_set_metadata_json Any, experiment_name Any, model_name Any, model_load_path Any, model_resume_path Any, skip_save_model Any, skip_save_progress Any, skip_save_log Any, skip_save_processed_input Any, output_directory Any, gpus Any, gpu_fraction Any, use_horovod Any, random_seed Any, logging_level Any, debug Any) : void from class org.ludwig.api.LudwigModel |
ludwig/api.py |
| uber/ludwig |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : EmbedEncoder, vocab : Any, representation : Any, embedding_size : Any, embeddings_trainable : Any, pretrained_embeddings : Any, embeddings_on_cpu : Any, initializer : Any, dropout : Any, regularize : Any, reduce_output : Any] to [self : EmbedEncoder, vocab : Any, representation : Any, embedding_size : Any, embeddings_trainable : Any, pretrained_embeddings : Any, embeddings_on_cpu : Any, dropout : Any, initializer : Any, regularize : Any, reduce_output : Any] in method package __init__(self EmbedEncoder, vocab Any, representation Any, embedding_size Any, embeddings_trainable Any, pretrained_embeddings Any, embeddings_on_cpu Any, dropout Any, initializer Any, regularize Any, reduce_output Any) : void from class org.ludwig.models.modules.sequence_encoders.EmbedEncoder |
ludwig/models/modules/sequence_encoders.py |
| uber/ludwig |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : ParallelCNN, should_embed : Any, vocab : Any, representation : Any, embedding_size : Any, embeddings_trainable : Any, pretrained_embeddings : Any, embeddings_on_cpu : Any, conv_layers : Any, num_conv_layers : Any, filter_size : Any, num_filters : Any, pool_size : Any, fc_layers : Any, num_fc_layers : Any, fc_size : Any, norm : Any, dropout : Any, activation : Any, initializer : Any, regularize : Any, reduce_output : Any] to [self : ParallelCNN, should_embed : Any, vocab : Any, representation : Any, embedding_size : Any, embeddings_trainable : Any, pretrained_embeddings : Any, embeddings_on_cpu : Any, conv_layers : Any, num_conv_layers : Any, filter_size : Any, num_filters : Any, pool_size : Any, fc_layers : Any, num_fc_layers : Any, fc_size : Any, norm : Any, activation : Any, dropout : Any, initializer : Any, regularize : Any, reduce_output : Any] in method package __init__(self ParallelCNN, should_embed Any, vocab Any, representation Any, embedding_size Any, embeddings_trainable Any, pretrained_embeddings Any, embeddings_on_cpu Any, conv_layers Any, num_conv_layers Any, filter_size Any, num_filters Any, pool_size Any, fc_layers Any, num_fc_layers Any, fc_size Any, norm Any, activation Any, dropout Any, initializer Any, regularize Any, reduce_output Any) : void from class org.ludwig.models.modules.sequence_encoders.ParallelCNN |
ludwig/models/modules/sequence_encoders.py |
| uber/ludwig |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : StackedParallelCNN, should_embed : Any, vocab : Any, representation : Any, embedding_size : Any, embeddings_trainable : Any, pretrained_embeddings : Any, embeddings_on_cpu : Any, stacked_layers : Any, num_stacked_layers : Any, filter_size : Any, num_filters : Any, stride : Any, pool_size : Any, pool_stride : Any, fc_layers : Any, num_fc_layers : Any, fc_size : Any, activation : Any, norm : Any, dropout : Any, initializer : Any, regularize : Any, reduce_output : Any] to [self : StackedParallelCNN, should_embed : Any, vocab : Any, representation : Any, embedding_size : Any, embeddings_trainable : Any, pretrained_embeddings : Any, embeddings_on_cpu : Any, stacked_layers : Any, num_stacked_layers : Any, filter_size : Any, num_filters : Any, stride : Any, pool_size : Any, pool_stride : Any, fc_layers : Any, num_fc_layers : Any, fc_size : Any, norm : Any, activation : Any, dropout : Any, initializer : Any, regularize : Any, reduce_output : Any] in method package __init__(self StackedParallelCNN, should_embed Any, vocab Any, representation Any, embedding_size Any, embeddings_trainable Any, pretrained_embeddings Any, embeddings_on_cpu Any, stacked_layers Any, num_stacked_layers Any, filter_size Any, num_filters Any, stride Any, pool_size Any, pool_stride Any, fc_layers Any, num_fc_layers Any, fc_size Any, norm Any, activation Any, dropout Any, initializer Any, regularize Any, reduce_output Any) : void from class org.ludwig.models.modules.sequence_encoders.StackedParallelCNN |
ludwig/models/modules/sequence_encoders.py |
| catalyst-team/catalyst |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : SequentialNet, hiddens : Any, layer_fn : Any, bias : Any, norm_fn : Any, activation_fn : Any, dropout : Any, layer_order : Any, residual : Any] to [self : SequentialNet, hiddens : Any, layer_fn : Any, norm_fn : Any, activation_fn : Any, bias : Any, dropout : Any, layer_order : Any, residual : Any] in method package __init__(self SequentialNet, hiddens Any, layer_fn Any, norm_fn Any, activation_fn Any, bias Any, dropout Any, layer_order Any, residual Any) : void from class org.catalyst.contrib.models.sequential.SequentialNet |
catalyst/contrib/models/sequential.py |
| hanxiao/bert-as-service |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [sess : Any, input_graph_def : Any, output_node_names : Any, logger : Any, variable_names_whitelist : Any, variable_names_blacklist : Any, use_fp16 : Any] to [sess : Any, input_graph_def : Any, output_node_names : Any, variable_names_whitelist : Any, variable_names_blacklist : Any, use_fp16 : Any, logger : Any] in method package convert_variables_to_constants(sess Any, input_graph_def Any, output_node_names Any, variable_names_whitelist Any, variable_names_blacklist Any, use_fp16 Any, logger Any) : void from class org.server.bert_serving.server.graph.PyDummyClass1 |
server/bert_serving/server/graph.py |
| NVIDIA/OpenSeq2Seq |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [layer_type : Any, name : Any, inputs : Any, filters : Any, kernel_size : Any, activation_fn : Any, strides : Any, padding : Any, dilation : Any, regularizer : Any, training : Any, data_format : Any] to [layer_type : Any, name : Any, inputs : Any, filters : Any, kernel_size : Any, activation_fn : Any, strides : Any, padding : Any, regularizer : Any, training : Any, data_format : Any, dilation : Any] in method package conv_actv(layer_type Any, name Any, inputs Any, filters Any, kernel_size Any, activation_fn Any, strides Any, padding Any, regularizer Any, training Any, data_format Any, dilation Any) : void from class org.open_seq2seq.parts.cnns.conv_blocks.PyDummyClass1 |
open_seq2seq/parts/cnns/conv_blocks.py |
| NVIDIA/OpenSeq2Seq |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [layer_type : Any, name : Any, inputs : Any, filters : Any, kernel_size : Any, activation_fn : Any, strides : Any, padding : Any, dilation : Any, regularizer : Any, training : Any, data_format : Any, bn_momentum : Any, bn_epsilon : Any] to [layer_type : Any, name : Any, inputs : Any, filters : Any, kernel_size : Any, activation_fn : Any, strides : Any, padding : Any, regularizer : Any, training : Any, data_format : Any, bn_momentum : Any, bn_epsilon : Any, dilation : Any] in method package conv_bn_actv(layer_type Any, name Any, inputs Any, filters Any, kernel_size Any, activation_fn Any, strides Any, padding Any, regularizer Any, training Any, data_format Any, bn_momentum Any, bn_epsilon Any, dilation Any) : void from class org.open_seq2seq.parts.cnns.conv_blocks.PyDummyClass1 |
open_seq2seq/parts/cnns/conv_blocks.py |
| NVIDIA/OpenSeq2Seq |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [layer_type : Any, name : Any, inputs : Any, filters : Any, kernel_size : Any, activation_fn : Any, strides : Any, padding : Any, dilation : Any, regularizer : Any, training : Any, data_format : Any] to [layer_type : Any, name : Any, inputs : Any, filters : Any, kernel_size : Any, activation_fn : Any, strides : Any, padding : Any, regularizer : Any, training : Any, data_format : Any, dilation : Any] in method package conv_ln_actv(layer_type Any, name Any, inputs Any, filters Any, kernel_size Any, activation_fn Any, strides Any, padding Any, regularizer Any, training Any, data_format Any, dilation Any) : void from class org.open_seq2seq.parts.cnns.conv_blocks.PyDummyClass1 |
open_seq2seq/parts/cnns/conv_blocks.py |
| NVIDIA/OpenSeq2Seq |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [layer_type : Any, name : Any, inputs : Any, filters : Any, kernel_size : Any, activation_fn : Any, strides : Any, padding : Any, dilation : Any, regularizer : Any, training : Any, data_format : Any] to [layer_type : Any, name : Any, inputs : Any, filters : Any, kernel_size : Any, activation_fn : Any, strides : Any, padding : Any, regularizer : Any, training : Any, data_format : Any, dilation : Any] in method package conv_in_actv(layer_type Any, name Any, inputs Any, filters Any, kernel_size Any, activation_fn Any, strides Any, padding Any, regularizer Any, training Any, data_format Any, dilation Any) : void from class org.open_seq2seq.parts.cnns.conv_blocks.PyDummyClass1 |
open_seq2seq/parts/cnns/conv_blocks.py |
| NVIDIA/OpenSeq2Seq |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : AttentionLayerNormalized, in_dim : Any, embed_size : Any, layer_id : Any, add_res : Any, mode : Any, normalization_type : Any, scaling_factor : Any, regularizer : Any, init_var : Any] to [self : AttentionLayerNormalized, in_dim : Any, embed_size : Any, layer_id : Any, add_res : Any, mode : Any, scaling_factor : Any, normalization_type : Any, regularizer : Any, init_var : Any] in method package __init__(self AttentionLayerNormalized, in_dim Any, embed_size Any, layer_id Any, add_res Any, mode Any, scaling_factor Any, normalization_type Any, regularizer Any, init_var Any) : void from class org.open_seq2seq.parts.convs2s.attention_wn_layer.AttentionLayerNormalized |
open_seq2seq/parts/convs2s/attention_wn_layer.py |
| asyml/texar |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [soft_sequence : Any, embedding : Any] to [embedding : Any, soft_sequence : Any] in method package soft_sequence_embedding(embedding Any, soft_sequence Any) : void from class org.texar.core.utils.PyDummyClass1 |
texar/core/utils.py |
| GPflow/GPflow |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : SamplingHelper, model_parameters : Any, target_log_prob_fn : Any] to [self : SamplingHelper, target_log_prob_fn : Any, model_parameters : Any] in method package __init__(self SamplingHelper, target_log_prob_fn Any, model_parameters Any) : void from class org.gpflow.optimizers.mcmc.SamplingHelper |
gpflow/optimizers/mcmc.py |
| GPflow/GPflow |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [closure : Any, optimizer : Any, var_list : Any, jit : Any, maxiter : Any] to [closure : Any, optimizer : Any, var_list : Any, maxiter : Any, jit : Any] in method package training_loop(closure Any, optimizer Any, var_list Any, maxiter Any, jit Any) : void from class org.gpflow.util.PyDummyClass1 |
gpflow/util.py |
| GPflow/GPflow |
Reorder Parameter |
RefactoringLink | CommitLink | No |
Reorder Parameter [p : Any, kernel : Any, feature : Any, mean : Any, _ : Any, nghp : Any] to [p : Any, mean : Any, _ : Any, kernel : Any, feature : Any, nghp : Any] in method package _E(p Any, mean Any, _ Any, kernel Any, feature Any, nghp Any) : void from class org.gpflow.expectations.misc.PyDummyClass1 |
gpflow/expectations/misc.py |
| GPflow/GPflow |
Reorder Parameter |
RefactoringLink | CommitLink | No |
Reorder Parameter [p : Any, kern : Any, feat : Any, mean : Any, _ : Any, nghp : Any] to [p : Any, mean : Any, _ : Any, kern : Any, feat : Any, nghp : Any] in method package _E(p Any, mean Any, _ Any, kern Any, feat Any, nghp Any) : void from class org.gpflow.expectations.misc.PyDummyClass1 |
gpflow/expectations/misc.py |
| OpenNMT/OpenNMT-py |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : PenaltyBuilder, length_pen : Any, cov_pen : Any] to [self : PenaltyBuilder, cov_pen : Any, length_pen : Any] in method package __init__(self PenaltyBuilder, cov_pen Any, length_pen Any) : void from class org.onmt.translate.Penalties.PenaltyBuilder |
onmt/translate/Penalties.py |
| aleju/imgaug |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : PerspectiveTransform, scale : Any, cval : Any, mode : Any, keep_size : Any, polygon_recoverer : Any, fit_output : Any, name : Any, deterministic : Any, random_state : Any] to [self : PerspectiveTransform, scale : Any, cval : Any, mode : Any, keep_size : Any, fit_output : Any, polygon_recoverer : Any, name : Any, deterministic : Any, random_state : Any] in method package __init__(self PerspectiveTransform, scale Any, cval Any, mode Any, keep_size Any, fit_output Any, polygon_recoverer Any, name Any, deterministic Any, random_state Any) : void from class org.imgaug.augmenters.geometric.PerspectiveTransform |
imgaug/augmenters/geometric.py |
| tensorlayer/tensorlayer |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : Conv1d, n_filter : Any, filter_size : Any, stride : Any, dilation_rate : Any, act : Any, padding : Any, data_format : Any, W_init : Any, b_init : Any, in_channels : Any, name : Any] to [self : Conv1d, n_filter : Any, filter_size : Any, stride : Any, act : Any, padding : Any, data_format : Any, dilation_rate : Any, W_init : Any, b_init : Any, in_channels : Any, name : Any] in method package __init__(self Conv1d, n_filter Any, filter_size Any, stride Any, act Any, padding Any, data_format Any, dilation_rate Any, W_init Any, b_init Any, in_channels Any, name Any) : void from class org.tensorlayer.layers.convolution.simplified_conv.Conv1d |
tensorlayer/layers/convolution/simplified_conv.py |
| ray-project/ray |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : AxSearch, ax_client : Any, max_concurrent : Any, mode : Any, use_early_stopped_trials : Any] to [self : AxSearch, ax_client : Any, mode : Any, use_early_stopped_trials : Any, max_concurrent : Any] in method package __init__(self AxSearch, ax_client Any, mode Any, use_early_stopped_trials Any, max_concurrent Any) : void from class org.python.ray.tune.suggest.ax.AxSearch |
python/ray/tune/suggest/ax.py |
| deepchem/deepchem |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : HyperparamOpt, params_dict : Any, train_dataset : Any, valid_dataset : Any, output_transformers : Any, metric : Any, use_max : Any, logdir : Any] to [self : HyperparamOpt, params_dict : Any, train_dataset : Any, valid_dataset : Any, metric : Any, output_transformers : Any, use_max : Any, logdir : Any] in method package hyperparam_search(self HyperparamOpt, params_dict Any, train_dataset Any, valid_dataset Any, metric Any, output_transformers Any, use_max Any, logdir Any) : void from class org.deepchem.hyper.base_classes.HyperparamOpt |
deepchem/hyper/base_classes.py |
| deepchem/deepchem |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : GaussianProcessHyperparamOpt, params_dict : Any, train_dataset : Any, valid_dataset : Any, output_transformers : Any, metric : Any, use_max : Any, logdir : Any, max_iter : Any, search_range : Any, logfile : Any] to [self : GaussianProcessHyperparamOpt, params_dict : Any, train_dataset : Any, valid_dataset : Any, metric : Any, output_transformers : Any, use_max : Any, logdir : Any, max_iter : Any, search_range : Any, logfile : Any] in method package hyperparam_search(self GaussianProcessHyperparamOpt, params_dict Any, train_dataset Any, valid_dataset Any, metric Any, output_transformers Any, use_max Any, logdir Any, max_iter Any, search_range Any, logfile Any) : void from class org.deepchem.hyper.gaussian_process.GaussianProcessHyperparamOpt |
deepchem/hyper/gaussian_process.py |
| deepchem/deepchem |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : GridHyperparamOpt, params_dict : Any, train_dataset : Any, valid_dataset : Any, output_transformers : Any, metric : Any, use_max : Any, logdir : Any] to [self : GridHyperparamOpt, params_dict : Any, train_dataset : Any, valid_dataset : Any, metric : Any, output_transformers : Any, use_max : Any, logdir : Any] in method package hyperparam_search(self GridHyperparamOpt, params_dict Any, train_dataset Any, valid_dataset Any, metric Any, output_transformers Any, use_max Any, logdir Any) : void from class org.deepchem.hyper.grid_search.GridHyperparamOpt |
deepchem/hyper/grid_search.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : ExpandedConv2D, out_channels : Any, in_channels : Any, expansion_size : Any, expand_pad : Any, depthwise_stride : Any, depthwise_ksize : Any, depthwise_pad : Any, project_pad : Any, initialW : Any, bn_kwargs : Any] to [self : ExpandedConv2D, in_channels : Any, out_channels : Any, expansion_size : Any, expand_pad : Any, depthwise_stride : Any, depthwise_ksize : Any, depthwise_pad : Any, project_pad : Any, initialW : Any, bn_kwargs : Any] in method package __init__(self ExpandedConv2D, in_channels Any, out_channels Any, expansion_size Any, expand_pad Any, depthwise_stride Any, depthwise_ksize Any, depthwise_pad Any, project_pad Any, initialW Any, bn_kwargs Any) : void from class org.chainercv.links.model.mobilenet.expanded_conv_2d.ExpandedConv2D |
chainercv/links/model/mobilenet/expanded_conv_2d.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : Transform, mean : Any, scale_range : Any, crop_size : Any] to [self : Transform, mean : Any, crop_size : Any, scale_range : Any] in method package __init__(self Transform, mean Any, crop_size Any, scale_range Any) : void from class org.examples.pspnet.train_multi.Transform |
examples/pspnet/train_multi.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [pred_bboxes : Any, pred_labels : Any, pred_scores : Any, gt_bboxes : Any, gt_labels : Any, gt_crowdeds : Any, gt_areas : Any] to [pred_bboxes : Any, pred_labels : Any, pred_scores : Any, gt_bboxes : Any, gt_labels : Any, gt_areas : Any, gt_crowdeds : Any] in method package eval_detection_coco(pred_bboxes Any, pred_labels Any, pred_scores Any, gt_bboxes Any, gt_labels Any, gt_areas Any, gt_crowdeds Any) : void from class org.chainercv.evaluations.eval_detection_coco.PyDummyClass1 |
chainercv/evaluations/eval_detection_coco.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : VGG16, pretrained_model : Any, n_class : Any, mean : Any, layer_names : Any, initialW : Any, initial_bias : Any] to [self : VGG16, layer_names : Any, pretrained_model : Any, n_class : Any, mean : Any, initialW : Any, initial_bias : Any] in method package __init__(self VGG16, layer_names Any, pretrained_model Any, n_class Any, mean Any, initialW Any, initial_bias Any) : void from class org.chainercv.links.model.vgg.vgg16.VGG16 |
chainercv/links/model/vgg/vgg16.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [anchor_base : Any, feat_stride : Any, width : Any, height : Any] to [anchor_base : Any, feat_stride : Any, height : Any, width : Any] in method package _enumerate_shifted_anchor(anchor_base Any, feat_stride Any, height Any, width Any) : void from class org.chainercv.links.model.faster_rcnn.region_proposal_network.PyDummyClass1 |
chainercv/links/model/faster_rcnn/region_proposal_network.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [bbox : Any, size : Any, x_flip : Any, y_flip : Any] to [bbox : Any, size : Any, y_flip : Any, x_flip : Any] in method package flip_bbox(bbox Any, size Any, y_flip Any, x_flip Any) : void from class org.chainercv.transforms.bbox.flip_bbox.PyDummyClass1 |
chainercv/transforms/bbox/flip_bbox.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [bbox : Any, x_offset : Any, y_offset : Any] to [bbox : Any, y_offset : Any, x_offset : Any] in method package translate_bbox(bbox Any, y_offset Any, x_offset Any) : void from class org.chainercv.transforms.bbox.translate_bbox.PyDummyClass1 |
chainercv/transforms/bbox/translate_bbox.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [img : Any, x_flip : Any, y_flip : Any, copy : Any] to [img : Any, y_flip : Any, x_flip : Any, copy : Any] in method package flip(img Any, y_flip Any, x_flip Any, copy Any) : void from class org.chainercv.transforms.image.flip.PyDummyClass1 |
chainercv/transforms/image/flip.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [img : Any, x_random : Any, y_random : Any, return_param : Any, copy : Any] to [img : Any, y_random : Any, x_random : Any, return_param : Any, copy : Any] in method package random_flip(img Any, y_random Any, x_random Any, return_param Any, copy Any) : void from class org.chainercv.transforms.image.random_flip.PyDummyClass1 |
chainercv/transforms/image/random_flip.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [keypoint : Any, size : Any, x_flip : Any, y_flip : Any] to [keypoint : Any, size : Any, y_flip : Any, x_flip : Any] in method package flip_keypoint(keypoint Any, size Any, y_flip Any, x_flip Any) : void from class org.chainercv.transforms.keypoint.flip_keypoint.PyDummyClass1 |
chainercv/transforms/keypoint/flip_keypoint.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [keypoint : Any, x_offset : Any, y_offset : Any] to [keypoint : Any, y_offset : Any, x_offset : Any] in method package translate_keypoint(keypoint Any, y_offset Any, x_offset Any) : void from class org.chainercv.transforms.keypoint.translate_keypoint.PyDummyClass1 |
chainercv/transforms/keypoint/translate_keypoint.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [anchor : Any, W : Any, H : Any] to [anchor : Any, H : Any, W : Any] in method package _get_inside_index(anchor Any, H Any, W Any) : void from class org.chainercv.links.model.faster_rcnn.utils.anchor_target_creator.PyDummyClass1 |
chainercv/links/model/faster_rcnn/utils/anchor_target_creator.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [label : Any, alpha : Any, label_names : Any, ax : Any] to [label : Any, label_names : Any, alpha : Any, ax : Any] in method package vis_label(label Any, label_names Any, alpha Any, ax Any) : void from class org.chainercv.visualizations.vis_label.PyDummyClass1 |
chainercv/visualizations/vis_label.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [base_raw_bbox : Any, bbox : Any] to [bbox : Any, base_raw_bbox : Any] in method package delta_decode(bbox Any, base_raw_bbox Any) : void from class org.chainercv.links.model.faster_rcnn.utils.delta_decode.PyDummyClass1 |
chainercv/links/model/faster_rcnn/utils/delta_decode.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [gt_label : Any, pred_label : Any, n_class : Any] to [pred_label : Any, gt_label : Any, n_class : Any] in method package _fast_hist(pred_label Any, gt_label Any, n_class Any) : void from class org.chainercv.evaluations.eval_semantic_segmentation.PyDummyClass1 |
chainercv/evaluations/eval_semantic_segmentation.py |
| chainer/chainercv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [label_true : Any, label_pred : Any, n_class : Any] to [label_pred : Any, label_true : Any, n_class : Any] in method package eval_semantic_segmentation(label_pred Any, label_true Any, n_class Any) : void from class org.chainercv.evaluations.eval_semantic_segmentation.PyDummyClass1 |
chainercv/evaluations/eval_semantic_segmentation.py |
| keras-team/keras |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [path : Any, seed : Any, test_split : Any] to [path : Any, test_split : Any, seed : Any] in method package load_data(path Any, test_split Any, seed Any) : void from class org.keras.datasets.boston_housing.PyDummyClass1 |
keras/datasets/boston_housing.py |
| keras-team/keras |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : DirectoryIterator, directory : Any, image_data_generator : Any, target_size : Any, color_mode : Any, data_format : Any, classes : Any, class_mode : Any, batch_size : Any, shuffle : Any, seed : Any, save_to_dir : Any, save_prefix : Any, save_format : Any, follow_links : Any] to [self : DirectoryIterator, directory : Any, image_data_generator : Any, target_size : Any, color_mode : Any, classes : Any, class_mode : Any, batch_size : Any, shuffle : Any, seed : Any, data_format : Any, save_to_dir : Any, save_prefix : Any, save_format : Any, follow_links : Any] in method package __init__(self DirectoryIterator, directory Any, image_data_generator Any, target_size Any, color_mode Any, classes Any, class_mode Any, batch_size Any, shuffle Any, seed Any, data_format Any, save_to_dir Any, save_prefix Any, save_format Any, follow_links Any) : void from class org.keras.preprocessing.image.DirectoryIterator |
keras/preprocessing/image.py |
| keras-team/keras |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : GRU, input_dim : Any, output_dim : Any, init : Any, inner_init : Any, activation : Any, inner_activation : Any, truncate_gradient : Any, weights : Any, return_sequences : Any] to [self : GRU, input_dim : Any, output_dim : Any, init : Any, inner_init : Any, activation : Any, inner_activation : Any, weights : Any, truncate_gradient : Any, return_sequences : Any] in method package __init__(self GRU, input_dim Any, output_dim Any, init Any, inner_init Any, activation Any, inner_activation Any, weights Any, truncate_gradient Any, return_sequences Any) : void from class org.keras.layers.recurrent.GRU |
keras/layers/recurrent.py |
| keras-team/keras |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : LSTM, input_dim : Any, output_dim : Any, init : Any, inner_init : Any, activation : Any, inner_activation : Any, truncate_gradient : Any, weights : Any, return_sequences : Any] to [self : LSTM, input_dim : Any, output_dim : Any, init : Any, inner_init : Any, activation : Any, inner_activation : Any, weights : Any, truncate_gradient : Any, return_sequences : Any] in method package __init__(self LSTM, input_dim Any, output_dim Any, init Any, inner_init Any, activation Any, inner_activation Any, weights Any, truncate_gradient Any, return_sequences Any) : void from class org.keras.layers.recurrent.LSTM |
keras/layers/recurrent.py |
| danforthcenter/plantcv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [stem_objects : Any, rgb_img : Any] to [rgb_img : Any, stem_objects : Any] in method package analyze_stem(rgb_img Any, stem_objects Any) : void from class org.plantcv.plantcv.morphology.analyze_stem.PyDummyClass1 |
plantcv/plantcv/morphology/analyze_stem.py |
| danforthcenter/plantcv |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [index_array : Any, mask : Any, histplot : Any, bins : Any, max_bin : Any, min_bin : Any] to [index_array : Any, mask : Any, histplot : Any, bins : Any, min_bin : Any, max_bin : Any] in method package analyze_index(index_array Any, mask Any, histplot Any, bins Any, min_bin Any, max_bin Any) : void from class org.plantcv.plantcv.hyperspectral.analyze_index.PyDummyClass1 |
plantcv/plantcv/hyperspectral/analyze_index.py |
| UFAL-DSG/tgen |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [correct : Any, gold : Any, predicted : Any] to [correct : Any, predicted : Any, gold : Any] in method package f1_from_counts(correct Any, predicted Any, gold Any) : void from class org.tgen.eval.PyDummyClass1 |
tgen/eval.py |
| UFAL-DSG/tgen |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [correct : Any, gold : Any, predicted : Any] to [correct : Any, predicted : Any, gold : Any] in method package p_r_f1_from_counts(correct Any, predicted Any, gold Any) : void from class org.tgen.eval.PyDummyClass1 |
tgen/eval.py |
| PIQuIL/QuCumber |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : NeuralStateBase, v : Any, vp : Any] to [self : NeuralStateBase, vp : Any, v : Any] in method package importance_sampling_numerator(self NeuralStateBase, vp Any, v Any) : void from class org.qucumber.nn_states.neural_state.NeuralStateBase |
qucumber/nn_states/neural_state.py |
| PIQuIL/QuCumber |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : NeuralStateBase, v : Any, vp : Any] to [self : NeuralStateBase, vp : Any, v : Any] in method package importance_sampling_weight(self NeuralStateBase, vp Any, v Any) : void from class org.qucumber.nn_states.neural_state.NeuralStateBase |
qucumber/nn_states/neural_state.py |
| PIQuIL/QuCumber |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : WaveFunctionBase, v : Any, vp : Any] to [self : WaveFunctionBase, vp : Any, v : Any] in method package importance_sampling_numerator(self WaveFunctionBase, vp Any, v Any) : void from class org.qucumber.nn_states.wavefunction.WaveFunctionBase |
qucumber/nn_states/wavefunction.py |
| PIQuIL/QuCumber |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : DensityGradsUtils, target : Any, bases : Any, space : Any] to [self : DensityGradsUtils, target : Any, space : Any, bases : Any] in method package compute_numerical_KL(self DensityGradsUtils, target Any, space Any, bases Any) : void from class org.tests.grads_utils.DensityGradsUtils |
tests/grads_utils.py |
| PIQuIL/QuCumber |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : ComplexWaveFunction, basis : Any, sample : Any] to [self : ComplexWaveFunction, sample : Any, basis : Any] in method package gradient(self ComplexWaveFunction, sample Any, basis Any) : void from class org.qucumber.nn_states.complex_wavefunction.ComplexWaveFunction |
qucumber/nn_states/complex_wavefunction.py |
| rail-berkeley/softlearning |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : SQL, env : Any, pool : Any, Qs : Any, policy : Any, plotter : Any, policy_lr : Any, Q_lr : Any, value_n_particles : Any, td_target_update_interval : Any, kernel_fn : Any, kernel_n_particles : Any, kernel_update_ratio : Any, discount : Any, tau : Any, reward_scale : Any, use_saved_Q : Any, use_saved_policy : Any, save_full_state : Any, train_Q : Any, train_policy : Any] to [self : SQL, env : Any, policy : Any, Qs : Any, pool : Any, plotter : Any, policy_lr : Any, Q_lr : Any, value_n_particles : Any, td_target_update_interval : Any, kernel_fn : Any, kernel_n_particles : Any, kernel_update_ratio : Any, discount : Any, tau : Any, reward_scale : Any, use_saved_Q : Any, use_saved_policy : Any, save_full_state : Any, train_Q : Any, train_policy : Any] in method package __init__(self SQL, env Any, policy Any, Qs Any, pool Any, plotter Any, policy_lr Any, Q_lr Any, value_n_particles Any, td_target_update_interval Any, kernel_fn Any, kernel_n_particles Any, kernel_update_ratio Any, discount Any, tau Any, reward_scale Any, use_saved_Q Any, use_saved_policy Any, save_full_state Any, train_Q Any, train_policy Any) : void from class org.softlearning.algorithms.sql.SQL |
softlearning/algorithms/sql.py |
| mathurinm/celer |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : LassoCV, eps : Any, n_alphas : Any, alphas : Any, fit_intercept : Any, max_iter : Any, tol : Any, cv : Any, verbose : Any, gap_freq : Any, max_epochs : Any, p0 : Any, prune : Any, normalize : Any, precompute : Any] to [self : LassoCV, eps : Any, n_alphas : Any, alphas : Any, fit_intercept : Any, normalize : Any, max_iter : Any, tol : Any, cv : Any, verbose : Any, gap_freq : Any, max_epochs : Any, p0 : Any, prune : Any, precompute : Any] in method package __init__(self LassoCV, eps Any, n_alphas Any, alphas Any, fit_intercept Any, normalize Any, max_iter Any, tol Any, cv Any, verbose Any, gap_freq Any, max_epochs Any, p0 Any, prune Any, precompute Any) : void from class org.celer.dropin_sklearn.LassoCV |
celer/dropin_sklearn.py |
| alexandrebarachant/muse-lsl |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [address : Any, backend : Any, Interface : Any, name : Any, duration : Any, filename : Any] to [duration : Any, address : Any, filename : Any, backend : Any, Interface : Any, name : Any] in method package record_direct(duration Any, address Any, filename Any, backend Any, Interface Any, name Any) : void from class org.muselsl.record.PyDummyClass1 |
muselsl/record.py |
| adalca/neuron |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : GaussianBlur, level : Any, sigma : Any] to [self : GaussianBlur, sigma : Any, level : Any] in method package __init__(self GaussianBlur, sigma Any, level Any) : void from class org.neurite.tf.layers.GaussianBlur |
neurite/tf/layers.py |
| rushter/MLAlgorithms |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [predicted : Any, actual : Any] to [actual : Any, predicted : Any] in method package binary_crossentropy(actual Any, predicted Any) : void from class org.mla.metrics.metrics.PyDummyClass1 |
mla/metrics/metrics.py |
| librosa/librosa |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : TimeFormatter, unit : Any, lag : Any] to [self : TimeFormatter, lag : Any, unit : Any] in method package __init__(self TimeFormatter, lag Any, unit Any) : void from class org.librosa.display.TimeFormatter |
librosa/display.py |
| librosa/librosa |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [S : Any, y : Any, sr : Any, n_mfcc : Any] to [y : Any, sr : Any, S : Any, n_mfcc : Any] in method package mfcc(y Any, sr Any, S Any, n_mfcc Any) : void from class org.librosa.feature.PyDummyClass1 |
librosa/feature.py |
| librosa/librosa |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [S : Any, y : Any, sr : Any, fmin : Any, fmax : Any, threshold : Any] to [y : Any, sr : Any, S : Any, fmin : Any, fmax : Any, threshold : Any] in method package piptrack(y Any, sr Any, S Any, fmin Any, fmax Any, threshold Any) : void from class org.librosa.feature.PyDummyClass1 |
librosa/feature.py |
| librosa/librosa |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [onsets : Any, y : Any, sr : Any, hop_length : Any, start_bpm : Any] to [y : Any, sr : Any, onsets : Any, hop_length : Any, start_bpm : Any] in method package beat_track(y Any, sr Any, onsets Any, hop_length Any, start_bpm Any) : void from class org.librosa.beat.PyDummyClass1 |
librosa/beat.py |
| librosa/librosa |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [S : Any, y : Any, sr : Any] to [y : Any, sr : Any, S : Any] in method package onset_strength(y Any, sr Any, S Any) : void from class org.librosa.beat.PyDummyClass1 |
librosa/beat.py |
| merbanan/rtl_433_tests |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [input_fn : Any, rtl_433_cmd : Any, samplerate : Any, protocol : Any] to [input_fn : Any, samplerate : Any, protocol : Any, rtl_433_cmd : Any] in method package run_rtl433(input_fn Any, samplerate Any, protocol Any, rtl_433_cmd Any) : void from class org.bin.run_test.PyDummyClass1 |
bin/run_test.py |
| pymanopt/pymanopt |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : Sphere, n : Any, m : Any] to [self : Sphere, m : Any, n : Any] in method package __init__(self Sphere, m Any, n Any) : void from class org.pymanopt.manifolds.sphere.Sphere |
pymanopt/manifolds/sphere.py |
| mariogeiger/se3cnn |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : FiniteElementModel, position : Any, basis : Any, Model : Any, out_dim : Any] to [self : FiniteElementModel, out_dim : Any, position : Any, basis : Any, Model : Any] in method package __init__(self FiniteElementModel, out_dim Any, position Any, basis Any, Model Any) : void from class org.se3cnn.point_radial.FiniteElementModel |
se3cnn/point_radial.py |
| freelunchtheorem/Conditional_Density_Estimation |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : LinearGaussian, mu : Any, ndim_x : Any, mu_slope : Any, std : Any, std_slope : Any, random_seed : Any] to [self : LinearGaussian, ndim_x : Any, mu : Any, mu_slope : Any, std : Any, std_slope : Any, random_seed : Any] in method package __init__(self LinearGaussian, ndim_x Any, mu Any, mu_slope Any, std Any, std_slope Any, random_seed Any) : void from class org.cde.density_simulation.LinearGaussian.LinearGaussian |
cde/density_simulation/LinearGaussian.py |
| freelunchtheorem/Conditional_Density_Estimation |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : LinearStudentT, mu : Any, ndim_x : Any, mu_slope : Any, std : Any, std_slope : Any, dof_low : Any, dof_high : Any, random_seed : Any] to [self : LinearStudentT, ndim_x : Any, mu : Any, mu_slope : Any, std : Any, std_slope : Any, dof_low : Any, dof_high : Any, random_seed : Any] in method package __init__(self LinearStudentT, ndim_x Any, mu Any, mu_slope Any, std Any, std_slope Any, dof_low Any, dof_high Any, random_seed Any) : void from class org.cde.density_simulation.LinearStudentT.LinearStudentT |
cde/density_simulation/LinearStudentT.py |
| CamDavidsonPilon/lifelines |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : KaplanMeierFitter, lower_bound : Any, upper_bound : Any, event_observed : Any, timeline : Any, label : Any, alpha : Any, ci_labels : Any, show_progress : Any, entry : Any, weights : Any, tol : Any] to [self : KaplanMeierFitter, lower_bound : Any, upper_bound : Any, event_observed : Any, timeline : Any, label : Any, alpha : Any, ci_labels : Any, entry : Any, weights : Any, tol : Any, show_progress : Any] in method package fit_interval_censoring(self KaplanMeierFitter, lower_bound Any, upper_bound Any, event_observed Any, timeline Any, label Any, alpha Any, ci_labels Any, entry Any, weights Any, tol Any, show_progress Any) : void from class org.lifelines.fitters.kaplan_meier_fitter.KaplanMeierFitter |
lifelines/fitters/kaplan_meier_fitter.py |
| CamDavidsonPilon/lifelines |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [model : Any, t : Any, model2 : Any, ax : Any, text_position : Any] to [model : Any, model2 : Any, t : Any, ax : Any, text_position : Any] in method package rmst_plot(model Any, model2 Any, t Any, ax Any, text_position Any) : void from class org.lifelines.plotting.PyDummyClass1 |
lifelines/plotting.py |
| nilearn/nilearn |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [img : Any, surf_mesh : Any, radius : Any, kind : Any, interpolation : Any, n_samples : Any, mask_img : Any] to [img : Any, surf_mesh : Any, radius : Any, interpolation : Any, kind : Any, n_samples : Any, mask_img : Any] in method package vol_to_surf(img Any, surf_mesh Any, radius Any, interpolation Any, kind Any, n_samples Any, mask_img Any) : void from class org.nilearn.surface.surface.PyDummyClass1 |
nilearn/surface/surface.py |
| matthewwithanm/django-imagekit |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : Register, id : Any, spec : Any] to [self : Register, spec : Any, id : Any] in method package spec(self Register, spec Any, id Any) : void from class org.imagekit.registry.Register |
imagekit/registry.py |
| matthewwithanm/django-imagekit |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : ProcessedImageField, processors : Any, format : Any, options : Any, autoconvert : Any, spec : Any, spec_id : Any] to [self : ProcessedImageField, processors : Any, format : Any, options : Any, autoconvert : Any, spec_id : Any, spec : Any] in method package __init__(self ProcessedImageField, processors Any, format Any, options Any, autoconvert Any, spec_id Any, spec Any) : void from class org.imagekit.forms.fields.ProcessedImageField |
imagekit/forms/fields.py |
| matthewwithanm/django-imagekit |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : AddBorder, color : Any, thickness : Any] to [self : AddBorder, thickness : Any, color : Any] in method package __init__(self AddBorder, thickness Any, color Any) : void from class org.imagekit.processors.resize.AddBorder |
imagekit/processors/resize.py |
| pysb/pysb |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [model : Any, dif0 : Any, y0 : Any, initial_dist : Any] to [model : Any, initial_dist : Any, dif0 : Any, y0 : Any] in method package _translate_species(model Any, initial_dist Any, dif0 Any, y0 Any) : void from class org.pysb.tools.pysb_pyurdme.PyDummyClass1 |
pysb/tools/pysb_pyurdme.py |
| pysb/pysb |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : PyurdmeSimulator, tspan : Any, mesh : Any, param_values : Any, dif0 : Any, y0 : Any, initial_dist : Any, solver : Any] to [self : PyurdmeSimulator, tspan : Any, mesh : Any, initial_dist : Any, param_values : Any, dif0 : Any, y0 : Any, solver : Any] in method package run(self PyurdmeSimulator, tspan Any, mesh Any, initial_dist Any, param_values Any, dif0 Any, y0 Any, solver Any) : void from class org.pysb.tools.pysb_pyurdme.PyurdmeSimulator |
pysb/tools/pysb_pyurdme.py |
| pysb/pysb |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [model : Any, tspan : Any, mesh : Any, param_values : Any, dif0 : Any, y0 : Any, initial_dist : Any, verbose : Any] to [model : Any, tspan : Any, mesh : Any, initial_dist : Any, param_values : Any, dif0 : Any, y0 : Any, verbose : Any] in method package run_pyurdme(model Any, tspan Any, mesh Any, initial_dist Any, param_values Any, dif0 Any, y0 Any, verbose Any) : void from class org.pysb.tools.pysb_pyurdme.PyDummyClass2 |
pysb/tools/pysb_pyurdme.py |
| bonlime/keras-deeplab-v3-plus |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [x : Any, filters : Any, prefix : Any, kernel_size : Any, stride : Any, rate : Any] to [x : Any, filters : Any, prefix : Any, stride : Any, kernel_size : Any, rate : Any] in method package conv2d_same(x Any, filters Any, prefix Any, stride Any, kernel_size Any, rate Any) : void from class org.model.PyDummyClass1 |
model.py |
| dit/dit |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [pmf : Any, n_variables : Any, symbol_map : Any, m : Any, with_replacement : Any] to [pmf : Any, n_variables : Any, m : Any, symbol_map : Any, with_replacement : Any] in method package moment_constraints(pmf Any, n_variables Any, m Any, symbol_map Any, with_replacement Any) : void from class org.dit.algorithms.maxentropy.PyDummyClass2 |
dit/algorithms/maxentropy.py |
| scikit-optimize/scikit-optimize |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [func : Any, y_opt : Any, bounds : Any, acq_optimizer : Any, acq_func : Any, margin : Any, n_calls : Any, init_gen : Any, n_random_starts : Any] to [func : Any, y_opt : Any, bounds : Any, acq_optimizer : Any, acq_func : Any, margin : Any, n_calls : Any, n_random_starts : Any, init_gen : Any] in method package check_minimize(func Any, y_opt Any, bounds Any, acq_optimizer Any, acq_func Any, margin Any, n_calls Any, n_random_starts Any, init_gen Any) : void from class org.skopt.tests.test_gp_opt.PyDummyClass1 |
skopt/tests/test_gp_opt.py |
| scikit-optimize/scikit-optimize |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : BayesSearchCV, spaces : Any, names : Any] to [self : BayesSearchCV, names : Any, spaces : Any] in method package add_spaces(self BayesSearchCV, names Any, spaces Any) : void from class org.skopt.searchcv.BayesSearchCV |
skopt/searchcv.py |
| scikit-optimize/scikit-optimize |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [func : Any, dimensions : Any, base_estimator : Any, acq_func : Any, xi : Any, kappa : Any, acq_optimizer : Any, n_calls : Any, n_points : Any, n_random_starts : Any, n_restarts_optimizer : Any, x0 : Any, y0 : Any, random_state : Any, verbose : Any, callback : Any] to [func : Any, dimensions : Any, base_estimator : Any, n_calls : Any, n_random_starts : Any, acq_func : Any, acq_optimizer : Any, x0 : Any, y0 : Any, random_state : Any, verbose : Any, callback : Any, n_points : Any, n_restarts_optimizer : Any, xi : Any, kappa : Any] in method package gp_minimize(func Any, dimensions Any, base_estimator Any, n_calls Any, n_random_starts Any, acq_func Any, acq_optimizer Any, x0 Any, y0 Any, random_state Any, verbose Any, callback Any, n_points Any, n_restarts_optimizer Any, xi Any, kappa Any) : void from class org.skopt.optimizer.gp_opt.PyDummyClass1 |
skopt/optimizer/gp_opt.py |
| scikit-optimize/scikit-optimize |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [func : Any, dimensions : Any, base_estimator : Any, n_calls : Any, n_points : Any, n_random_starts : Any, x0 : Any, y0 : Any, random_state : Any, acq : Any, xi : Any, kappa : Any, verbose : Any, specs : Any, callback : Any] to [func : Any, dimensions : Any, base_estimator : Any, n_calls : Any, n_points : Any, n_random_starts : Any, specs : Any, x0 : Any, y0 : Any, random_state : Any, acq : Any, xi : Any, kappa : Any, verbose : Any, callback : Any] in method package _tree_minimize(func Any, dimensions Any, base_estimator Any, n_calls Any, n_points Any, n_random_starts Any, specs Any, x0 Any, y0 Any, random_state Any, acq Any, xi Any, kappa Any, verbose Any, callback Any) : void from class org.skopt.tree_opt.PyDummyClass1 |
skopt/tree_opt.py |
| scikit-optimize/scikit-optimize |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : GradientBoostingQuantileRegressor, quantiles : Any, base_estimator : Any, random_state : Any, n_jobs : Any] to [self : GradientBoostingQuantileRegressor, quantiles : Any, base_estimator : Any, n_jobs : Any, random_state : Any] in method package __init__(self GradientBoostingQuantileRegressor, quantiles Any, base_estimator Any, n_jobs Any, random_state Any) : void from class org.skopt.learning.gbrt.GradientBoostingQuantileRegressor |
skopt/learning/gbrt.py |
| datascienceinc/Skater |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [y_predicted : Any, y_true : Any] to [y_true : Any, y_predicted : Any] in method package check_data(y_true Any, y_predicted Any) : void from class org.skater.model.scorer.Scorer |
skater/model/scorer.py |
| datascienceinc/Skater |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [y_predicted : Any, y_true : Any] to [y_true : Any, y_predicted : Any] in method package check_data(y_true Any, y_predicted Any) : void from class org.skater.model.scorer.RegressionScorer |
skater/model/scorer.py |
| datascienceinc/Skater |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [y_predicted : Any, y_true : Any] to [y_true : Any, y_predicted : Any] in method package check_data(y_true Any, y_predicted Any) : void from class org.skater.model.scorer.ClassifierScorer |
skater/model/scorer.py |
| fgnt/pb_bss |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [target_psd_matrix : Any, beamformer : Any, noise_psd_matrix : Any] to [beamformer : Any, target_psd_matrix : Any, noise_psd_matrix : Any] in method package get_bf_vector(beamformer Any, target_psd_matrix Any, noise_psd_matrix Any) : void from class org.paderbox.speech_enhancement.beamformer.PyDummyClass1 |
paderbox/speech_enhancement/beamformer.py |
| explosion/thinc |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [W : Any, b : Any, cell_tm1 : Any, hidden_tm1 : Any, inputs : Any] to [W : Any, b : Any, hidden_tm1 : Any, cell_tm1 : Any, inputs : Any] in method package lstm(W Any, b Any, hidden_tm1 Any, cell_tm1 Any, inputs Any) : void from class org.thinc.backends.jax_ops.PyDummyClass1 |
thinc/backends/jax_ops.py |
| jadore801120/attention-is-all-you-need-pytorch |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [seq_q : Any, seq_k : Any] to [seq_k : Any, seq_q : Any] in method package get_attn_key_pad_mask(seq_k Any, seq_q Any) : void from class org.transformer.Models.PyDummyClass1 |
transformer/Models.py |
| geek-ai/MAgent |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [self : DeepQNetwork, env : Any, handle : Any, name : Any, batch_size : Any, reward_decay : Any, learning_rate : Any, train_freq : Any, target_update : Any, memory_size : Any, eval_obs : Any, use_dueling : Any, use_double : Any, infer_batch_size : Any, custom_view_space : Any, custom_feature_space : Any, num_gpu : Any] to [self : DeepQNetwork, env : Any, handle : Any, name : Any, batch_size : Any, learning_rate : Any, reward_decay : Any, train_freq : Any, target_update : Any, memory_size : Any, eval_obs : Any, use_dueling : Any, use_double : Any, infer_batch_size : Any, custom_view_space : Any, custom_feature_space : Any, num_gpu : Any] in method package __init__(self DeepQNetwork, env Any, handle Any, name Any, batch_size Any, learning_rate Any, reward_decay Any, train_freq Any, target_update Any, memory_size Any, eval_obs Any, use_dueling Any, use_double Any, infer_batch_size Any, custom_view_space Any, custom_feature_space Any, num_gpu Any) : void from class org.python.magent.builtin.mx_model.dqn.DeepQNetwork |
python/magent/builtin/mx_model/dqn.py |
| metagenome-atlas/atlas |
Reorder Parameter |
RefactoringLink | CommitLink | Yes |
Reorder Parameter [report_out : Any, read_counts : Any, zipfiles_raw : Any, zipfiles_QC : Any, min_quality : Any] to [report_out : Any, read_counts : Any, zipfiles_QC : Any, min_quality : Any, zipfiles_raw : Any] in method package main(report_out Any, read_counts Any, zipfiles_QC Any, min_quality Any, zipfiles_raw Any) : void from class org.atlas.report.qc_report.PyDummyClass1 |
atlas/report/qc_report.py |