Sourcery refactored master branch by sourcery-ai[bot] · Pull Request #2 · theonesud/HandsOnDeepLearningWithPytorch

sourcery-ai · 2023-07-26T13:34:36Z

Branch master refactored by Sourcery.

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sourcery-ai · 2023-07-26T13:34:38Z

2.ASimpleNeuralNetwork/fizbuz.py

-            'Number: {} -- Actual: {} -- Prediction: {}'.format(
-                num, check_fizbuz(num), outli[hyp[i].max(0)[1].item()]))
+            f'Number: {num} -- Actual: {check_fizbuz(num)} -- Prediction: {outli[hyp[i].max(0)[1].item()]}'
+        )


Lines 80-81 refactored with the following changes:

Replace call to format with f-string (use-fstring-for-formatting)

sourcery-ai · 2023-07-26T13:34:39Z

2.ASimpleNeuralNetwork/numpy_like_fizbuz.py

 b2 = torch.zeros(1, output_size, requires_grad=True, device=device, dtype=dtype)

-no_of_batches = int(len(trX) / batches)
+no_of_batches = len(trX) // batches


Lines 35-110 refactored with the following changes:

Simplify division expressions (simplify-division)

Replace call to format with f-string (use-fstring-for-formatting)

sourcery-ai · 2023-07-26T13:34:39Z

3.DLWorkFlow/ModelImplementation/bottleneck_support.py

-x_ = x[0:10]
-y_ = y[0:10]
+x_ = x[:10]
+y_ = y[:10]


Lines 92-93 refactored with the following changes:

Replace a[0:x] with a[:x] and a[x:len(a)] with a[x:] [×2] (remove-redundant-slice-index)

sourcery-ai · 2023-07-26T13:34:39Z

3.DLWorkFlow/ModelImplementation/profile_support.py

-x_ = x[0:10]
-y_ = y[0:10]
+x_ = x[:10]
+y_ = y[:10]


Lines 94-95 refactored with the following changes:

Replace a[0:x] with a[:x] and a[x:len(a)] with a[x:] [×2] (remove-redundant-slice-index)

sourcery-ai · 2023-07-26T13:34:39Z

4.ComputerVision/SemSeg/dataset.py

-            raise FileNotFoundError("Couldn't find 'labels' folder in {}".format(path))
+            raise FileNotFoundError(f"Couldn't find 'labels' folder in {path}")
        self.files = []
        for file in input_files:
            name, ext = os.path.splitext(file)
            input_file = os.path.join(inputdir_path, file)
-            label_file = os.path.join(labledir_path, '{}_L{}'.format(name, ext))
+            label_file = os.path.join(labledir_path, f'{name}_L{ext}')


Function CamvidDataSet.__init__ refactored with the following changes:

Replace call to format with f-string [×2] (use-fstring-for-formatting)

sourcery-ai · 2023-07-26T13:34:42Z

5.SequentialDataProcessing/SimpleRNN/train.py


 model.train()
-for epoch in range(epochs):
+for _ in range(epochs):


Lines 76-101 refactored with the following changes:

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

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

sourcery-ai · 2023-07-26T13:34:42Z

6.GenerativeNetworks/AutoRegressive/wavenet.py

        super().__init__()
        self.res_blocks = torch.nn.ModuleList()
-        for s in range(stack_size):
+        for _ in range(stack_size):


Function ResidualStack.__init__ refactored with the following changes:

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

sourcery-ai · 2023-07-26T13:34:42Z

6.GenerativeNetworks/AutoRegressive/wavenet_data.py

-    decoded = np.argmax(data, axis=axis)
-
-    return decoded
+    return np.argmax(data, axis=axis)


Function one_hot_decode refactored with the following changes:

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

sourcery-ai · 2023-07-26T13:34:42Z

6.GenerativeNetworks/AutoRegressive/wavenet_data.py

-    waveform = np.sign(expanded) * (np.exp(np.abs(expanded) * np.log(mu + 1)) - 1) / mu
-
-    return waveform
+    return np.sign(expanded) * (np.exp(np.abs(expanded) * np.log(mu + 1)) - 1) / mu


Function mu_law_decode refactored with the following changes:

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

sourcery-ai · 2023-07-26T13:34:43Z

6.GenerativeNetworks/AutoRegressive/wavenet_data.py

-        self.filenames = [x for x in sorted(os.listdir(data_dir))]
+        self.filenames = list(sorted(os.listdir(data_dir)))


Function Dataset.__init__ refactored with the following changes:

Replace identity comprehension with call to collection constructor (identity-comprehension)

sourcery-ai · 2023-07-26T13:34:47Z

6.GenerativeNetworks/AutoRegressive/wavenet_data.py

-        return self.sample_size if len(audio[0]) >= self.sample_size\
-                                else len(audio[0])
+        return min(len(audio[0]), self.sample_size)


Function DataLoader.calc_sample_size refactored with the following changes:

Replace comparison with min/max call (min-max-identity)

sourcery-ai · 2023-07-26T13:34:47Z

6.GenerativeNetworks/GAN/CycleGAN/mode.py

-        self.files_A = sorted(glob.glob(os.path.join(root, '%sA' % mode) + '/*.*'))
-        self.files_B = sorted(glob.glob(os.path.join(root, '%sB' % mode) + '/*.*'))
+        self.files_A = sorted(glob.glob(f"{os.path.join(root, f'{mode}A')}/*.*"))
+        self.files_B = sorted(glob.glob(f"{os.path.join(root, f'{mode}B')}/*.*"))


Function ImageDataset.__init__ refactored with the following changes:

Use f-string instead of string concatenation [×2] (use-fstring-for-concatenation)

Replace interpolated string formatting with f-string [×2] (replace-interpolation-with-fstring)

sourcery-ai · 2023-07-26T13:34:47Z

6.GenerativeNetworks/GAN/CycleGAN/mode.py

+            elif random.uniform(0, 1) > 0.5:
+                i = random.randint(0, self.max_size - 1)
+                to_return.append(self.data[i].clone())
+                self.data[i] = element
            else:
-                if random.uniform(0, 1) > 0.5:
-                    i = random.randint(0, self.max_size - 1)
-                    to_return.append(self.data[i].clone())
-                    self.data[i] = element
-                else:
-                    to_return.append(element)
+                to_return.append(element)


Function ReplayBuffer.push_and_pop refactored with the following changes:

Merge else clause's nested if statement into elif (merge-else-if-into-elif)

sourcery-ai · 2023-07-26T13:34:47Z

6.GenerativeNetworks/GAN/CycleGAN/mode.py

-for epoch in range(opt.epoch, opt.n_epochs):
-    for i, batch in enumerate(dataloader):
+for _ in range(opt.epoch, opt.n_epochs):
+    for batch in dataloader:


Lines 319-320 refactored with the following changes:

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

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

sourcery-ai · 2023-07-26T13:34:47Z

6.GenerativeNetworks/GAN/CycleGAN/util.py

    parser.add_argument('--size', type=int, default=256, help='crop to this size')
-    args = parser.parse_args(args=[])
-    return args
+    return parser.parse_args(args=[])


Function get_args refactored with the following changes:

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

sourcery-ai · 2023-07-26T13:34:49Z

8.PyTorchInProduction/FizBuzONNX/fizbuz_package/fizbuz_service.py

-        data_names = []
-        data_shapes = []


Function MXNetModelService.initialize refactored with the following changes:

Move assignment closer to its usage within a block [×2] (move-assign-in-block)

Replace call to format with f-string (use-fstring-for-formatting)

Merge append into list declaration [×2] (merge-list-append)

sourcery-ai · 2023-07-26T13:34:49Z

8.PyTorchInProduction/FizBuzONNX/fizbuz_package/fizbuz_service.py

-        data = batch[0].get('body').get(param_name)
-        if data:
+        if data := batch[0].get('body').get(param_name):
            self.input = data + 1
-            tensor = mx.nd.array([self.binary_encoder(self.input, input_size=10)])
-            return tensor
+            return mx.nd.array([self.binary_encoder(self.input, input_size=10)])


Function MXNetModelService.preprocess refactored with the following changes:

Use named expression to simplify assignment and conditional (use-named-expression)

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

sourcery-ai · 2023-07-26T13:34:49Z

8.PyTorchInProduction/FizBuzONNX/fizbuz_package/fizbuz_service.py

-        out = [{'next_number': prediction}]
-        return out
+        return [{'next_number': prediction}]


Function MXNetModelService.postprocess refactored with the following changes:

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

sourcery-ai · 2023-07-26T13:34:49Z

8.PyTorchInProduction/RedisAI/run_redis.py

-        return input_num
-    else:
-        return input_output_map[prediction]
+    return input_num if prediction == 3 else input_output_map[prediction]


Function get_readable_output refactored with the following changes:

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

sourcery-ai · 2023-07-26T13:34:49Z

8.PyTorchInProduction/TorchScriptExamples/multinomial.py

    output_dist = output.squeeze().div(0.8).exp()
-    prob = torch.multinomial(output_dist, 2)
-    return prob
+    return torch.multinomial(output_dist, 2)


Function post_processing refactored with the following changes:

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

'Refactored by Sourcery'

3d9281f

sourcery-ai bot requested a review from theonesud July 26, 2023 13:34

sourcery-ai bot commented Jul 26, 2023

View reviewed changes

		self.filenames = [x for x in sorted(os.listdir(data_dir))]
		self.filenames = list(sorted(os.listdir(data_dir)))

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