Sourcery refactored master branch by sourcery-ai[bot] · Pull Request #1 · theonesud/Random-forests-and-Feature-Engineering

sourcery-ai · 2023-07-26T13:35:00Z

Branch master refactored by Sourcery.

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sourcery-ai

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sourcery-ai · 2023-07-26T13:35:03Z

fastai/adaptive_softmax.py

-        self.criterions = nn.ModuleList([nn.CrossEntropyLoss(size_average=False) for i in self.cutoff])
+        self.criterions = nn.ModuleList(
+            [nn.CrossEntropyLoss(size_average=False) for _ in self.cutoff]
+        )


Function AdaptiveLoss.__init__ refactored with the following changes:

Replace unused for index with underscore (for-index-underscore)

sourcery-ai · 2023-07-26T13:35:03Z

fastai/column_data.py

-                x = F.sigmoid(x)
-            else:
-                x = F.log_softmax(x)
+            x = F.sigmoid(x) if self.is_multi else F.log_softmax(x)


Function MixedInputModel.forward refactored with the following changes:

Replace if statement with if expression (assign-if-exp)

sourcery-ai · 2023-07-26T13:35:03Z

fastai/conv_learner.py


-        if f in model_meta: cut,self.lr_cut = model_meta[f]
-        else: cut,self.lr_cut = 0,0
+        cut,self.lr_cut = model_meta[f] if f in model_meta else (0, 0)


Function ConvnetBuilder.__init__ refactored with the following changes:

Replace if statement with if expression [×2] (assign-if-exp)

sourcery-ai · 2023-07-26T13:35:04Z

fastai/conv_learner.py

-            if self.data.test_dl: predict_to_bcolz(m, self.data.test_dl, test_act)
-
+            predict_to_bcolz(m, self.data.test_dl, test_act)


Function ConvLearner.save_fc1 refactored with the following changes:

Remove redundant conditional (remove-redundant-if)

sourcery-ai · 2023-07-26T13:35:04Z

fastai/core.py

 def datafy(x):
-    if is_listy(x): return [o.data for o in x]
-    else:           return x.data
+    return [o.data for o in x] if is_listy(x) else x.data


Function datafy refactored with the following changes:

Replace if statement with if expression (assign-if-exp)

sourcery-ai · 2023-07-26T13:35:06Z

fastai/imports.py

-    try:
-        for i in range(len(inst)): inst.pop().close()
-    except Exception:
-        pass
+    with contextlib.suppress(Exception):
+        for _ in range(len(inst)):
+            inst.pop().close()


Function clear_tqdm refactored with the following changes:

Use contextlib's suppress method to silence an error (use-contextlib-suppress)

Replace unused for index with underscore (for-index-underscore)

sourcery-ai · 2023-07-26T13:35:06Z

fastai/layer_optimizer.py

-        if 'betas' in self.opt.param_groups[0]:
-            for pg in self.opt.param_groups: pg['betas'] = (momentum, pg['betas'][1])
-        else:
-            for pg in self.opt.param_groups: pg['momentum'] = momentum
+        for pg in self.opt.param_groups:
+            if 'betas' in self.opt.param_groups[0]:
+                pg['betas'] = (momentum, pg['betas'][1])
+            else:
+                pg['momentum'] = momentum


Function LayerOptimizer.set_mom refactored with the following changes:

Hoist for/while loops out of nested conditionals (hoist-loop-from-if)

sourcery-ai · 2023-07-26T13:35:06Z

fastai/layer_optimizer.py

-        if 'betas' in self.opt.param_groups[0]:
-            for pg in self.opt.param_groups: pg['betas'] = (pg['betas'][0],beta)
-        elif 'alpha' in self.opt.param_groups[0]:
-            for pg in self.opt.param_groups: pg['alpha'] = beta
+        for pg in self.opt.param_groups:
+            if 'betas' in self.opt.param_groups[0]:
+                pg['betas'] = (pg['betas'][0],beta)
+            elif 'alpha' in self.opt.param_groups[0]:
+                pg['alpha'] = beta


Function LayerOptimizer.set_beta refactored with the following changes:

Hoist for/while loops out of nested conditionals (hoist-loop-from-if)

sourcery-ai · 2023-07-26T13:35:07Z

fastai/learner.py

-    def get_model_path(self, name): return os.path.join(self.models_path,name)+'.h5'
+    def get_model_path(self, name):
+        return f'{os.path.join(self.models_path, name)}.h5'


Function Learner.get_model_path refactored with the following changes:

Use f-string instead of string concatenation (use-fstring-for-concatenation)

sourcery-ai · 2023-07-26T13:35:07Z

fastai/learner.py

-        if hasattr(self, 'swa_model'): save_model(self.swa_model, self.get_model_path(name)[:-3]+'-swa.h5')
+        if hasattr(self, 'swa_model'):
+            save_model(self.swa_model, f'{self.get_model_path(name)[:-3]}-swa.h5')


Function Learner.save refactored with the following changes:

Use f-string instead of string concatenation (use-fstring-for-concatenation)

sourcery-ai · 2023-07-26T13:35:11Z

fastai/learner.py

-        if hasattr(self, 'swa_model'): load_model(self.swa_model, self.get_model_path(name)[:-3]+'-swa.h5')
+        if hasattr(self, 'swa_model'):
+            load_model(self.swa_model, f'{self.get_model_path(name)[:-3]}-swa.h5')


Function Learner.load refactored with the following changes:

Use f-string instead of string concatenation (use-fstring-for-concatenation)

sourcery-ai · 2023-07-26T13:35:11Z

fastai/learner.py

-        if not isinstance(arr, np.ndarray): raise OSError(f'Not valid numpy array')
+        if not isinstance(arr, np.ndarray):
+            raise OSError('Not valid numpy array')


Function Learner.predict_array refactored with the following changes:

Replace f-string with no interpolated values with string (remove-redundant-fstring)

sourcery-ai · 2023-07-26T13:35:11Z

fastai/learner.py

-        preds2 = [predict_with_targs(self.model, dl2)[0] for i in tqdm(range(n_aug), leave=False)]
+        preds2 = [
+            predict_with_targs(self.model, dl2)[0]
+            for _ in tqdm(range(n_aug), leave=False)
+        ]


Function Learner.TTA refactored with the following changes:

Replace unused for index with underscore (for-index-underscore)

sourcery-ai · 2023-07-26T13:35:11Z

fastai/lm_rnn.py

-        self.dropouths = nn.ModuleList([LockedDropout(dropouth) for l in range(n_layers)])
+        self.dropouths = nn.ModuleList(
+            [LockedDropout(dropouth) for _ in range(n_layers)]
+        )


Function RNN_Encoder.__init__ refactored with the following changes:

Replace unused for index with underscore (for-index-underscore)

sourcery-ai · 2023-07-26T13:35:11Z

fastai/lsuv_initializer.py

+
 import numpy as np
 import torch
 import torch.nn.init
 import torch.nn as nn

-gg = {}
-gg['hook_position'] = 0
-gg['total_fc_conv_layers'] = 0
-gg['done_counter'] = -1
-gg['hook'] = None
-gg['act_dict'] = {}
-gg['counter_to_apply_correction'] = 0
-gg['correction_needed'] = False
-gg['current_coef'] = 1.0
+gg = {
+    'hook_position': 0,
+    'total_fc_conv_layers': 0,
+    'done_counter': -1,
+    'hook': None,
+    'act_dict': {},
+    'counter_to_apply_correction': 0,
+    'correction_needed': False,
+    'current_coef': 1.0,
+}


Lines 35-43 refactored with the following changes:

Merge dictionary assignment with declaration [×8] (merge-dict-assign)

sourcery-ai · 2023-07-26T13:35:13Z

fastai/nlp.py

-        for i in range(len(self)):
+        for _ in range(len(self)):


Function TextDataLoader.__iter__ refactored with the following changes:

Replace unused for index with underscore (for-index-underscore)

sourcery-ai · 2023-07-26T13:35:14Z

fastai/rnn_reg.py

            w = getattr(self.module, name_w)
            del self.module._parameters[name_w]
-            self.module.register_parameter(name_w + '_raw', nn.Parameter(w.data))
+            self.module.register_parameter(f'{name_w}_raw', nn.Parameter(w.data))


Function WeightDrop._setup refactored with the following changes:

Use f-string instead of string concatenation (use-fstring-for-concatenation)

sourcery-ai · 2023-07-26T13:35:14Z

fastai/rnn_reg.py

        """
        for name_w in self.weights:
-            raw_w = getattr(self.module, name_w + '_raw')
+            raw_w = getattr(self.module, f'{name_w}_raw')


Function WeightDrop._setweights refactored with the following changes:

Use f-string instead of string concatenation (use-fstring-for-concatenation)

sourcery-ai · 2023-07-26T13:35:14Z

fastai/rnn_reg.py

-
-        if IS_TORCH_04:
-            X = F.embedding(words,
-                masked_embed_weight, padding_idx, self.embed.max_norm,
-                self.embed.norm_type, self.embed.scale_grad_by_freq, self.embed.sparse)
-        else:
-            X = self.embed._backend.Embedding.apply(words,
-                masked_embed_weight, padding_idx, self.embed.max_norm,
-                self.embed.norm_type, self.embed.scale_grad_by_freq, self.embed.sparse)
-
-        return X
+
+        return (
+            F.embedding(
+                words,
+                masked_embed_weight,
+                padding_idx,
+                self.embed.max_norm,
+                self.embed.norm_type,
+                self.embed.scale_grad_by_freq,
+                self.embed.sparse,
+            )
+            if IS_TORCH_04
+            else self.embed._backend.Embedding.apply(
+                words,
+                masked_embed_weight,
+                padding_idx,
+                self.embed.max_norm,
+                self.embed.norm_type,
+                self.embed.scale_grad_by_freq,
+                self.embed.sparse,
+            )
+        )


Function EmbeddingDropout.forward refactored with the following changes:

Replace if statement with if expression (assign-if-exp)

Inline variable that is immediately returned (inline-immediately-returned-variable)

sourcery-ai · 2023-07-26T13:35:14Z

fastai/sgdr.py

-        if self.iteration == self.nb:
-            return True
-        return super().on_batch_end(loss)
+        return True if self.iteration == self.nb else super().on_batch_end(loss)


Function LR_Finder2.on_batch_end refactored with the following changes:

Lift code into else after jump in control flow (reintroduce-else)

Replace if statement with if expression (assign-if-exp)

'Refactored by Sourcery'

92eb16b

sourcery-ai bot requested a review from theonesud July 26, 2023 13:35

sourcery-ai bot commented Jul 26, 2023

View reviewed changes

		if self.data.test_dl: predict_to_bcolz(m, self.data.test_dl, test_act)

		predict_to_bcolz(m, self.data.test_dl, test_act)

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