Sourcery refactored xin branch #1
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| args = super().parse_args() | ||
| return args | ||
| return super().parse_args() |
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Function ArgParser.parse_args refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
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| raise Exception('No existing model_path: ' + args.model_path) | ||
| raise Exception(f'No existing model_path: {args.model_path}') |
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Function get_logger refactored with the following changes:
- Use f-string instead of string concatenation (
use-fstring-for-concatenation) - Replace call to format with f-string (
use-fstring-for-formatting)
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| metrics = {} | ||
| logs = [] | ||
| for i in range(args.num_proc): | ||
| for _ in range(args.num_proc): | ||
| log = queue.get() | ||
| logs = logs + log | ||
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| for metric in logs[0].keys(): | ||
| metrics[metric] = sum([log[metric] for log in logs]) / len(logs) | ||
| metrics = { | ||
| metric: sum(log[metric] for log in logs) / len(logs) | ||
| for metric in logs[0].keys() | ||
| } | ||
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| for k, v in metrics.items(): | ||
| print('Test average {} at [{}/{}]: {}'.format(k, args.step, args.max_step, v)) | ||
| print(f'Test average {k} at [{args.step}/{args.max_step}]: {v}') |
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Function main refactored with the following changes:
- Move assignment closer to its usage within a block (
move-assign-in-block) - Replace unused for index with underscore (
for-index-underscore) - Convert for loop into dictionary comprehension (
dict-comprehension) - Replace unneeded comprehension with generator (
comprehension-to-generator) - Replace call to format with f-string (
use-fstring-for-formatting)
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| original_name = name[0:-6] | ||
| state_sum = target[original_name+'_state-data-'] | ||
| original_name = name[:-6] | ||
| state_sum = target[f'{original_name}_state-data-'] |
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Function KGEServer._push_handler refactored with the following changes:
- Replace a[0:x] with a[:x] and a[x:len(a)] with a[x:] (
remove-redundant-slice-index) - Use f-string instead of string concatenation (
use-fstring-for-concatenation)
| """Get data from data_path/dataset/part_machine_id | ||
| """Get data from data_path/dataset/part_machine_id |
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Function get_server_data refactored with the following changes:
- Use f-string instead of string concatenation [×2] (
use-fstring-for-concatenation)
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| print('batch size ({}) is incompatible to the negative sample size ({}). Change the batch size to {}'.format( | ||
| old_batch_size, neg_sample_size, batch_size)) | ||
| print( | ||
| f'batch size ({old_batch_size}) is incompatible to the negative sample size ({neg_sample_size}). Change the batch size to {batch_size}' | ||
| ) | ||
|
|
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Function get_compatible_batch_size refactored with the following changes:
- Replace call to format with f-string (
use-fstring-for-formatting)
| assert f_remote.status_code == 200, 'fail to open {}'.format(url) | ||
| assert f_remote.status_code == 200, f'fail to open {url}' |
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Function _download_and_extract refactored with the following changes:
- Replace call to format with f-string (
use-fstring-for-formatting)
| for i, l in enumerate(f): | ||
| pass | ||
| pass |
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Function _file_line refactored with the following changes:
- Remove nested block which has no effect (
remove-empty-nested-block)
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| print('Reading {} triples....'.format(mode)) | ||
| print(f'Reading {mode} triples....') |
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Function KGDataset.read_triple refactored with the following changes:
- Replace call to format with f-string [×2] (
use-fstring-for-formatting)
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| print('Reading {} triples....'.format(mode)) | ||
| print(f'Reading {mode} triples....') |
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Function PartitionKGDataset.read_triple refactored with the following changes:
- Replace call to format with f-string [×2] (
use-fstring-for-formatting)
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| url = 'https://data.dgl.ai/dataset/{}.zip'.format(name) | ||
| url = f'https://data.dgl.ai/dataset/{name}.zip' | ||
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| if not os.path.exists(os.path.join(path, name)): | ||
| print('File not found. Downloading from', url) | ||
| _download_and_extract(url, path, name + '.zip') | ||
| _download_and_extract(url, path, f'{name}.zip') |
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Function KGDatasetFB15k.__init__ refactored with the following changes:
- Replace call to format with f-string (
use-fstring-for-formatting) - Use f-string instead of string concatenation (
use-fstring-for-concatenation)
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| url = 'https://data.dgl.ai/dataset/{}.zip'.format(name) | ||
| url = f'https://data.dgl.ai/dataset/{name}.zip' | ||
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| if not os.path.exists(os.path.join(path, name)): | ||
| print('File not found. Downloading from', url) | ||
| _download_and_extract(url, path, name + '.zip') | ||
| _download_and_extract(url, path, f'{name}.zip') |
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Function KGDatasetFB15k237.__init__ refactored with the following changes:
- Replace call to format with f-string (
use-fstring-for-formatting) - Use f-string instead of string concatenation (
use-fstring-for-concatenation)
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| url = 'https://data.dgl.ai/dataset/{}.zip'.format(name) | ||
| url = f'https://data.dgl.ai/dataset/{name}.zip' | ||
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| if not os.path.exists(os.path.join(path, name)): | ||
| print('File not found. Downloading from', url) | ||
| _download_and_extract(url, path, name + '.zip') | ||
| _download_and_extract(url, path, f'{name}.zip') |
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Function KGDatasetWN18.__init__ refactored with the following changes:
- Replace call to format with f-string (
use-fstring-for-formatting) - Use f-string instead of string concatenation (
use-fstring-for-concatenation)
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| url = 'https://data.dgl.ai/dataset/{}.zip'.format(name) | ||
| url = f'https://data.dgl.ai/dataset/{name}.zip' | ||
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| if not os.path.exists(os.path.join(path, name)): | ||
| print('File not found. Downloading from', url) | ||
| _download_and_extract(url, path, name + '.zip') | ||
| _download_and_extract(url, path, f'{name}.zip') |
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Function KGDatasetWN18rr.__init__ refactored with the following changes:
- Replace call to format with f-string (
use-fstring-for-formatting) - Use f-string instead of string concatenation (
use-fstring-for-concatenation)
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| url = 'https://data.dgl.ai/dataset/{}.zip'.format(name) | ||
| url = f'https://data.dgl.ai/dataset/{name}.zip' | ||
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| if not os.path.exists(os.path.join(path, name)): | ||
| print('File not found. Downloading from', url) | ||
| _download_and_extract(url, path, '{}.zip'.format(name)) | ||
| _download_and_extract(url, path, f'{name}.zip') |
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Function KGDatasetFreebase.__init__ refactored with the following changes:
- Replace call to format with f-string [×2] (
use-fstring-for-formatting)
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| print('relation partition {} edges into {} parts'.format(len(heads), n)) | ||
| print(f'relation partition {len(heads)} edges into {n} parts') |
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Function BalancedRelationPartition refactored with the following changes:
- Replace call to format with f-string [×3] (
use-fstring-for-formatting) - Convert for loop into list comprehension (
list-comprehension)
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| print('random partition {} edges into {} parts'.format(len(heads), n)) | ||
| print(f'random partition {len(heads)} edges into {n} parts') |
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Function RandomPartition refactored with the following changes:
- Replace call to format with f-string [×2] (
use-fstring-for-formatting)
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| raise Exception('get invalid type: ' + eval_type) | ||
| raise Exception(f'get invalid type: {eval_type}') |
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Function EvalDataset.get_edges refactored with the following changes:
- Use f-string instead of string concatenation (
use-fstring-for-concatenation)
| if model_name == 'RESCAL': | ||
| rel_dim = relation_dim * entity_dim | ||
| else: | ||
| rel_dim = relation_dim | ||
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| rel_dim = relation_dim * entity_dim if model_name == 'RESCAL' else relation_dim |
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Function KEModel.__init__ refactored with the following changes:
- Replace if statement with if expression (
assign-if-exp) - Replace multiple comparisons of same variable with
inoperator (merge-comparisons)
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| self.entity_emb.save(path, dataset+'_'+self.model_name+'_entity') | ||
| self.entity_emb.save(path, f'{dataset}_{self.model_name}_entity') | ||
| if self.strict_rel_part or self.soft_rel_part: | ||
| self.global_relation_emb.save(path, dataset+'_'+self.model_name+'_relation') | ||
| self.global_relation_emb.save(path, f'{dataset}_{self.model_name}_relation') | ||
| else: | ||
| self.relation_emb.save(path, dataset+'_'+self.model_name+'_relation') | ||
| self.relation_emb.save(path, f'{dataset}_{self.model_name}_relation') | ||
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| self.score_func.save(path, dataset+'_'+self.model_name) | ||
| self.score_func.save(path, f'{dataset}_{self.model_name}') |
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Function KEModel.save_emb refactored with the following changes:
- Use f-string instead of string concatenation [×11] (
use-fstring-for-concatenation)
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| self.entity_emb.load(path, dataset+'_'+self.model_name+'_entity') | ||
| self.relation_emb.load(path, dataset+'_'+self.model_name+'_relation') | ||
| self.score_func.load(path, dataset+'_'+self.model_name) | ||
| self.entity_emb.load(path, f'{dataset}_{self.model_name}_entity') | ||
| self.relation_emb.load(path, f'{dataset}_{self.model_name}_relation') | ||
| self.score_func.load(path, f'{dataset}_{self.model_name}') |
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Function KEModel.load_emb refactored with the following changes:
- Use f-string instead of string concatenation [×8] (
use-fstring-for-concatenation)
| if neg_deg_sample: | ||
| neg_g.neg_sample_size = neg_sample_size | ||
| mask = mask.reshape(num_chunks, chunk_size, neg_sample_size) | ||
| return neg_score * mask | ||
| else: | ||
| if not neg_deg_sample: | ||
| return neg_score | ||
| neg_g.neg_sample_size = neg_sample_size | ||
| mask = mask.reshape(num_chunks, chunk_size, neg_sample_size) | ||
| return neg_score * mask |
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Function KEModel.predict_neg_score refactored with the following changes:
- Swap if/else branches (
swap-if-else-branches) - Remove unnecessary else after guard condition (
remove-unnecessary-else)
| res = nd.sqrt(nd.clip(squared_res, 1e-30, np.finfo(np.float32).max)) | ||
| return res | ||
| return nd.sqrt(nd.clip(squared_res, 1e-30, np.finfo(np.float32).max)) |
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Function batched_l2_dist refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
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| res = nd.norm(a - b, ord=1, axis=-1) | ||
| return res | ||
| return nd.norm(a - b, ord=1, axis=-1) |
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Function batched_l1_dist refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
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| self.projection_emb.save(path, name+'projection') | ||
| self.projection_emb.save(path, f'{name}projection') |
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Function TransRScore.save refactored with the following changes:
- Use f-string instead of string concatenation (
use-fstring-for-concatenation)
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| file_name = os.path.join(path, name+'.npy') | ||
| file_name = os.path.join(path, f'{name}.npy') |
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Function ExternalEmbedding.load refactored with the following changes:
- Use f-string instead of string concatenation (
use-fstring-for-concatenation)
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| np.random.seed(42) | ||
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| from models.mxnet.score_fun import * | ||
| from models.mxnet.tensor_models import ExternalEmbedding | ||
| else: | ||
| import torch as th | ||
| th.manual_seed(42) | ||
| np.random.seed(42) | ||
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| from models.pytorch.score_fun import * | ||
| from models.pytorch.tensor_models import ExternalEmbedding | ||
| np.random.seed(42) | ||
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Lines 31-39 refactored with the following changes:
- Hoist repeated code outside conditional statement (
hoist-statement-from-if)
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| neg_score = self.head_neg_score(neg_head, rel, tail, | ||
| num_chunks, chunk_size, neg_sample_size) | ||
| return self.head_neg_score( | ||
| neg_head, rel, tail, num_chunks, chunk_size, neg_sample_size | ||
| ) | ||
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Function BaseKEModel.predict_neg_score refactored with the following changes:
- Lift return into if (
lift-return-into-if)
| assert f_remote.status_code == 200, 'fail to open {}'.format(url) | ||
| assert f_remote.status_code == 200, f'fail to open {url}' |
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Function _download refactored with the following changes:
- Replace call to format with f-string (
use-fstring-for-formatting)
| bin_path = "/tmp/dataset/livejournal/livejournal_{}.bin".format(format) | ||
| bin_path = f"/tmp/dataset/livejournal/livejournal_{format}.bin" |
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Function get_graph refactored with the following changes:
- Replace call to format with f-string [×3] (
use-fstring-for-formatting)
Sourcery Code Quality Report❌ Merging this PR will decrease code quality in the affected files by 0.11%.
Here are some functions in these files that still need a tune-up:
Legend and ExplanationThe emojis denote the absolute quality of the code:
The 👍 and 👎 indicate whether the quality has improved or gotten worse with this pull request. Please see our documentation here for details on how these metrics are calculated. We are actively working on this report - lots more documentation and extra metrics to come! Help us improve this quality report! |
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xinrefactored by Sourcery.If you're happy with these changes, merge this Pull Request using the Squash and merge strategy.
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