Sourcery refactored main branch #1

sourcery-ai · 2022-08-11T21:20:20Z

Branch main refactored by Sourcery.

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sourcery-ai

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sourcery-ai · 2022-08-11T21:20:22Z

main.py

-             "Parameters can be overwritten or added with command-line options of the form `--key value`.",
-        default=list(),
+        "Parameters can be overwritten or added with command-line options of the form `--key value`.",
+        default=[],
    )
+


Function get_parser refactored with the following changes:

Replace list() with [] (list-literal)

sourcery-ai · 2022-08-11T21:20:22Z

main.py

-        self.dataset_configs = dict()
+        self.dataset_configs = {}


Function DataModuleFromConfig.__init__ refactored with the following changes:

Replace dict() with {} (dict-literal)

sourcery-ai · 2022-08-11T21:20:22Z

main.py

-        self.datasets = dict(
-            (k, instantiate_from_config(self.dataset_configs[k]))
-            for k in self.dataset_configs)
+        self.datasets = {
+            k: instantiate_from_config(self.dataset_configs[k])
+            for k in self.dataset_configs
+        }
+


Function DataModuleFromConfig.setup refactored with the following changes:

Replace list(), dict() or set() with comprehension (collection-builtin-to-comprehension)

sourcery-ai · 2022-08-11T21:20:22Z

main.py

-        return DataLoader(self.datasets["train"], batch_size=self.batch_size,
-                          num_workers=self.num_workers, shuffle=False if is_iterable_dataset else True,
-                          worker_init_fn=init_fn)
+        return DataLoader(
+            self.datasets["train"],
+            batch_size=self.batch_size,
+            num_workers=self.num_workers,
+            shuffle=not is_iterable_dataset,
+            worker_init_fn=init_fn,
+        )


Function DataModuleFromConfig._train_dataloader refactored with the following changes:

Remove unnecessary casts to int, str, float or bool (remove-unnecessary-cast)

Simplify boolean if expression (boolean-if-exp-identity)

sourcery-ai · 2022-08-11T21:20:22Z

main.py

-            if "callbacks" in self.lightning_config:
-                if 'metrics_over_trainsteps_checkpoint' in self.lightning_config['callbacks']:
-                    os.makedirs(os.path.join(self.ckptdir, 'trainstep_checkpoints'), exist_ok=True)
+            if (
+                "callbacks" in self.lightning_config
+                and 'metrics_over_trainsteps_checkpoint'
+                in self.lightning_config['callbacks']
+            ):
+                os.makedirs(os.path.join(self.ckptdir, 'trainstep_checkpoints'), exist_ok=True)
            print("Project config")
            print(OmegaConf.to_yaml(self.config))
-            OmegaConf.save(self.config,
-                           os.path.join(self.cfgdir, "{}-project.yaml".format(self.now)))
+            OmegaConf.save(
+                self.config, os.path.join(self.cfgdir, f"{self.now}-project.yaml")
+            )
+

            print("Lightning config")
            print(OmegaConf.to_yaml(self.lightning_config))
-            OmegaConf.save(OmegaConf.create({"lightning": self.lightning_config}),
-                           os.path.join(self.cfgdir, "{}-lightning.yaml".format(self.now)))
+            OmegaConf.save(
+                OmegaConf.create({"lightning": self.lightning_config}),
+                os.path.join(self.cfgdir, f"{self.now}-lightning.yaml"),
+            )

-        else:
-            # ModelCheckpoint callback created log directory --- remove it
-            if not self.resume and os.path.exists(self.logdir):
-                dst, name = os.path.split(self.logdir)
-                dst = os.path.join(dst, "child_runs", name)
-                os.makedirs(os.path.split(dst)[0], exist_ok=True)
-                try:
-                    os.rename(self.logdir, dst)
-                except FileNotFoundError:
-                    pass
+
+        elif not self.resume and os.path.exists(self.logdir):
+            dst, name = os.path.split(self.logdir)
+            dst = os.path.join(dst, "child_runs", name)
+            os.makedirs(os.path.split(dst)[0], exist_ok=True)
+            try:
+                os.rename(self.logdir, dst)
+            except FileNotFoundError:
+                pass


Function SetupCallback.on_pretrain_routine_start refactored with the following changes:

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

Merge nested if conditions (merge-nested-ifs)

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

This removes the following comments ( why? ):

# ModelCheckpoint callback created log directory --- remove it

sourcery-ai · 2022-08-11T21:20:24Z

ldm/lr_scheduler.py

-        interval = 0
-        for cl in self.cum_cycles[1:]:
+        for interval, cl in enumerate(self.cum_cycles[1:]):
            if n <= cl:
                return interval
-            interval += 1


Function LambdaWarmUpCosineScheduler2.find_in_interval refactored with the following changes:

Replace manual loop counter with call to enumerate (convert-to-enumerate)

sourcery-ai · 2022-08-11T21:20:24Z

ldm/lr_scheduler.py

-        if self.verbosity_interval > 0:
+        if self.verbosity_interval > 0 and n % self.verbosity_interval == 0:
            if n % self.verbosity_interval == 0: print(f"current step: {n}, recent lr-multiplier: {self.last_f}, "
                                                       f"current cycle {cycle}")
        if n < self.lr_warm_up_steps[cycle]:
            f = (self.f_max[cycle] - self.f_start[cycle]) / self.lr_warm_up_steps[cycle] * n + self.f_start[cycle]
-            self.last_f = f
-            return f
        else:
            t = (n - self.lr_warm_up_steps[cycle]) / (self.cycle_lengths[cycle] - self.lr_warm_up_steps[cycle])
            t = min(t, 1.0)
            f = self.f_min[cycle] + 0.5 * (self.f_max[cycle] - self.f_min[cycle]) * (
                    1 + np.cos(t * np.pi))
-            self.last_f = f
-            return f
+
+        self.last_f = f
+        return f


Function LambdaWarmUpCosineScheduler2.schedule refactored with the following changes:

Merge nested if conditions (merge-nested-ifs)

Hoist repeated code outside conditional statement [×2] (hoist-statement-from-if)

sourcery-ai · 2022-08-11T21:20:24Z

ldm/lr_scheduler.py

-        if self.verbosity_interval > 0:
+        if self.verbosity_interval > 0 and n % self.verbosity_interval == 0:
            if n % self.verbosity_interval == 0: print(f"current step: {n}, recent lr-multiplier: {self.last_f}, "
                                                       f"current cycle {cycle}")
-
        if n < self.lr_warm_up_steps[cycle]:
            f = (self.f_max[cycle] - self.f_start[cycle]) / self.lr_warm_up_steps[cycle] * n + self.f_start[cycle]
-            self.last_f = f
-            return f
        else:
            f = self.f_min[cycle] + (self.f_max[cycle] - self.f_min[cycle]) * (self.cycle_lengths[cycle] - n) / (self.cycle_lengths[cycle])
-            self.last_f = f
-            return f
+
+        self.last_f = f
+        return f


Function LambdaLinearScheduler.schedule refactored with the following changes:

Merge nested if conditions (merge-nested-ifs)

Hoist repeated code outside conditional statement [×2] (hoist-statement-from-if)

sourcery-ai · 2022-08-11T21:20:24Z

ldm/util.py

    # xc a list of captions to plot
    b = len(xc)
-    txts = list()
+    txts = []


Function log_txt_as_img refactored with the following changes:

Replace list() with [] (list-literal)

sourcery-ai · 2022-08-11T21:20:24Z

ldm/util.py

-    if not isinstance(x, torch.Tensor):
-        return False
-    return (len(x.shape) == 4) and (x.shape[1] > 3)
+    return (
+        (len(x.shape) == 4) and (x.shape[1] > 3)
+        if isinstance(x, torch.Tensor)
+        else False
+    )


Function ismap refactored with the following changes:

Swap if/else branches of if expression to remove negation (swap-if-expression)

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

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

sourcery-ai · 2022-08-11T21:20:28Z

ldm/util.py

-    if not isinstance(x, torch.Tensor):
-        return False
-    return (len(x.shape) == 4) and (x.shape[1] == 3 or x.shape[1] == 1)
+    return (
+        len(x.shape) == 4 and x.shape[1] in [3, 1]
+        if isinstance(x, torch.Tensor)
+        else False
+    )


Function isimage refactored with the following changes:

Swap if/else branches of if expression to remove negation (swap-if-expression)

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

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

Replace multiple comparisons of same variable with in operator (merge-comparisons)

sourcery-ai · 2022-08-11T21:20:28Z

ldm/util.py

-    if idx_to_fn:
-        res = func(data, worker_id=idx)
-    else:
-        res = func(data)
+    res = func(data, worker_id=idx) if idx_to_fn else func(data)


Function _do_parallel_data_prefetch refactored with the following changes:

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

sourcery-ai · 2022-08-11T21:20:28Z

ldm/util.py

-                f'WARNING:"data" argument passed to parallel_data_prefetch is a dict: Using only its values and disregarding keys.'
+                'WARNING:"data" argument passed to parallel_data_prefetch is a dict: Using only its values and disregarding keys.'
            )
+
            data = list(data.values())
-        if target_data_type == "ndarray":
-            data = np.asarray(data)
-        else:
-            data = list(data)
+        data = np.asarray(data) if target_data_type == "ndarray" else list(data)


Function parallel_data_prefetch refactored with the following changes:

Swap if/else branches of if expression to remove negation (swap-if-expression)

Replace f-string with no interpolated values with string [×2] (remove-redundant-fstring)

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

Replace unneeded comprehension with generator (comprehension-to-generator)

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

This removes the following comments ( why? ):

# order outputs

sourcery-ai · 2022-08-11T21:20:29Z

ldm/data/imagenet.py

    with open(path_to_yaml) as f:
        di2s = yaml.load(f)
-    return dict((v,k) for k,v in di2s.items())
+    return {v: k for k,v in di2s.items()}


Function synset2idx refactored with the following changes:

Replace list(), dict() or set() with comprehension (collection-builtin-to-comprehension)

sourcery-ai · 2022-08-11T21:20:29Z

ldm/data/imagenet.py

    def __init__(self, config=None):
        self.config = config or OmegaConf.create()
-        if not type(self.config)==dict:
+        if type(self.config) != dict:


Function ImageNetBase.__init__ refactored with the following changes:

Simplify logical expression using De Morgan identities (de-morgan)

sourcery-ai · 2022-08-11T21:20:30Z

ldm/models/autoencoder.py

            for ik in ignore_keys:
                if k.startswith(ik):
-                    print("Deleting key {} from state_dict.".format(k))
+                    print(f"Deleting key {k} from state_dict.")


Function VQModel.init_from_ckpt refactored with the following changes:

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

sourcery-ai · 2022-08-11T21:20:30Z

ldm/models/autoencoder.py

        quant = self.post_quant_conv(quant)
-        dec = self.decoder(quant)
-        return dec
+        return self.decoder(quant)


Function VQModel.decode refactored with the following changes:

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

sourcery-ai · 2022-08-11T21:20:30Z

ldm/models/autoencoder.py

-        dec = self.decode(quant_b)
-        return dec
+        return self.decode(quant_b)


Function VQModel.decode_code refactored with the following changes:

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

sourcery-ai · 2022-08-11T21:20:30Z

ldm/models/autoencoder.py

-        if return_pred_indices:
-            return dec, diff, ind
-        return dec, diff
+        return (dec, diff, ind) if return_pred_indices else (dec, diff)


Function VQModel.forward 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)

sourcery-ai · 2022-08-11T21:20:31Z

ldm/models/autoencoder.py

-        aeloss, log_dict_ae = self.loss(qloss, x, xrec, 0,
-                                        self.global_step,
-                                        last_layer=self.get_last_layer(),
-                                        split="val"+suffix,
-                                        predicted_indices=ind
-                                        )
-
-        discloss, log_dict_disc = self.loss(qloss, x, xrec, 1,
-                                            self.global_step,
-                                            last_layer=self.get_last_layer(),
-                                            split="val"+suffix,
-                                            predicted_indices=ind
-                                            )
+        aeloss, log_dict_ae = self.loss(
+            qloss,
+            x,
+            xrec,
+            0,
+            self.global_step,
+            last_layer=self.get_last_layer(),
+            split=f"val{suffix}",
+            predicted_indices=ind,
+        )
+
+
+        discloss, log_dict_disc = self.loss(
+            qloss,
+            x,
+            xrec,
+            1,
+            self.global_step,
+            last_layer=self.get_last_layer(),
+            split=f"val{suffix}",
+            predicted_indices=ind,
+        )
+


Function VQModel._validation_step refactored with the following changes:

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

sourcery-ai · 2022-08-11T21:20:36Z

ldm/models/autoencoder.py

-        log = dict()
+        log = {}


Function VQModel.log_images refactored with the following changes:

Replace dict() with {} (dict-literal)

sourcery-ai · 2022-08-11T21:20:36Z

ldm/models/autoencoder.py

-        dec = self.decoder(quant)
-        return dec
+        return self.decoder(quant)


Function VQModelInterface.decode refactored with the following changes:

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

sourcery-ai · 2022-08-11T21:20:36Z

ldm/models/autoencoder.py

-                    print("Deleting key {} from state_dict.".format(k))
+                    print(f"Deleting key {k} from state_dict.")


Function AutoencoderKL.init_from_ckpt refactored with the following changes:

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

sourcery-ai · 2022-08-11T21:20:36Z

ldm/models/autoencoder.py

-        posterior = DiagonalGaussianDistribution(moments)
-        return posterior
+        return DiagonalGaussianDistribution(moments)


Function AutoencoderKL.encode refactored with the following changes:

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

sourcery-ai · 2022-08-11T21:20:36Z

ldm/models/autoencoder.py

-        dec = self.decoder(z)
-        return dec
+        return self.decoder(z)


Function AutoencoderKL.decode refactored with the following changes:

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

sourcery-ai · 2022-08-11T21:20:38Z

ldm/models/diffusion/ddim.py

-        if x_T is None:
-            img = torch.randn(shape, device=device)
-        else:
-            img = x_T
-
+        img = torch.randn(shape, device=device) if x_T is None else x_T
        if timesteps is None:
            timesteps = self.ddpm_num_timesteps if ddim_use_original_steps else self.ddim_timesteps
-        elif timesteps is not None and not ddim_use_original_steps:
+        elif not ddim_use_original_steps:
            subset_end = int(min(timesteps / self.ddim_timesteps.shape[0], 1) * self.ddim_timesteps.shape[0]) - 1
            timesteps = self.ddim_timesteps[:subset_end]

        intermediates = {'x_inter': [img], 'pred_x0': [img]}
-        time_range = reversed(range(0,timesteps)) if ddim_use_original_steps else np.flip(timesteps)
+        time_range = (
+            reversed(range(timesteps))
+            if ddim_use_original_steps
+            else np.flip(timesteps)
+        )
+


Function DDIMSampler.ddim_sampling refactored with the following changes:

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

Remove redundant conditional (remove-redundant-if)

Replace range(0, x) with range(x) (remove-zero-from-range)

sourcery-ai · 2022-08-11T21:20:38Z

ldm/models/diffusion/ddpm.py

-                    print("Deleting key {} from state_dict.".format(k))
+                    print(f"Deleting key {k} from state_dict.")
                    del sd[k]
-        missing, unexpected = self.load_state_dict(sd, strict=False) if not only_model else self.model.load_state_dict(
-            sd, strict=False)
+        missing, unexpected = (
+            self.model.load_state_dict(sd, strict=False)
+            if only_model
+            else self.load_state_dict(sd, strict=False)
+        )
+


Function DDPM.init_from_ckpt refactored with the following changes:

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

Swap if/else branches of if expression to remove negation (swap-if-expression)

sourcery-ai · 2022-08-11T21:20:38Z

ldm/models/diffusion/ddpm.py

-        for i in tqdm(reversed(range(0, self.num_timesteps)), desc='Sampling t', total=self.num_timesteps):
+        for i in tqdm(reversed(range(self.num_timesteps)), desc='Sampling t', total=self.num_timesteps):
            img = self.p_sample(img, torch.full((b,), i, device=device, dtype=torch.long),
                                clip_denoised=self.clip_denoised)
            if i % self.log_every_t == 0 or i == self.num_timesteps - 1:
                intermediates.append(img)
-        if return_intermediates:
-            return img, intermediates
-        return img
+        return (img, intermediates) if return_intermediates else img


Function DDPM.p_sample_loop refactored with the following changes:

Replace range(0, x) with range(x) (remove-zero-from-range)

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

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

sourcery-ai · 2022-08-11T21:20:38Z

ldm/models/diffusion/ddpm.py

        x_noisy = self.q_sample(x_start=x_start, t=t, noise=noise)
        model_out = self.model(x_noisy, t)

-        loss_dict = {}


Function DDPM.p_losses refactored with the following changes:

Merge dictionary assignment with declaration (merge-dict-assign)

Move assignment closer to its usage within a block (move-assign-in-block)

Add single value to dictionary directly rather than using update() [×3] (simplify-dictionary-update)

sourcery-ai · 2022-08-11T21:20:38Z

ldm/models/diffusion/ddpm.py

-            loss_dict_ema = {key + '_ema': loss_dict_ema[key] for key in loss_dict_ema}
+            loss_dict_ema = {f'{key}_ema': loss_dict_ema[key] for key in loss_dict_ema}


Function DDPM.validation_step refactored with the following changes:

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

sourcery-ai · 2022-08-11T21:25:25Z

Sourcery Code Quality Report

✅ Merging this PR will increase code quality in the affected files by 0.34%.

Quality metrics	Before	After	Change
Complexity	9.96 🙂	9.58 🙂	-0.38 👍
Method Length	98.56 🙂	97.98 🙂	-0.58 👍
Working memory	12.98 😞	12.94 😞	-0.04 👍
Quality	53.09% 🙂	53.43% 🙂	0.34% 👍

Other metrics	Before	After	Change
Lines	9710	9719	9

Changed files	Quality Before	Quality After	Quality Change
main.py	64.57% 🙂	65.23% 🙂	0.66% 👍
notebook_helpers.py	52.38% 🙂	53.90% 🙂	1.52% 👍
ldm/lr_scheduler.py	66.79% 🙂	67.83% 🙂	1.04% 👍
ldm/util.py	50.72% 🙂	49.91% 😞	-0.81% 👎
ldm/data/imagenet.py	55.21% 🙂	56.07% 🙂	0.86% 👍
ldm/data/lsun.py	73.32% 🙂	73.51% 🙂	0.19% 👍
ldm/models/autoencoder.py	70.16% 🙂	69.48% 🙂	-0.68% 👎
ldm/models/diffusion/classifier.py	68.19% 🙂	68.38% 🙂	0.19% 👍
ldm/models/diffusion/ddim.py	43.83% 😞	45.09% 😞	1.26% 👍
ldm/models/diffusion/ddpm.py	43.64% 😞	44.78% 😞	1.14% 👍
ldm/models/diffusion/plms.py	36.31% 😞	37.53% 😞	1.22% 👍
ldm/modules/attention.py	75.13% ⭐	75.23% ⭐	0.10% 👍
ldm/modules/ema.py	71.01% 🙂	71.08% 🙂	0.07% 👍
ldm/modules/x_transformer.py	55.04% 🙂	55.64% 🙂	0.60% 👍
ldm/modules/diffusionmodules/model.py	53.29% 🙂	53.12% 🙂	-0.17% 👎
ldm/modules/diffusionmodules/openaimodel.py	44.50% 😞	44.47% 😞	-0.03% 👎
ldm/modules/distributions/distributions.py	78.18% ⭐	80.40% ⭐	2.22% 👍
ldm/modules/encoders/modules.py	85.31% ⭐	85.27% ⭐	-0.04% 👎
ldm/modules/image_degradation/bsrgan.py	48.02% 😞	48.03% 😞	0.01% 👍
ldm/modules/image_degradation/bsrgan_light.py	53.86% 🙂	53.93% 🙂	0.07% 👍
ldm/modules/image_degradation/utils_image.py	60.15% 🙂	60.31% 🙂	0.16% 👍
ldm/modules/losses/contperceptual.py	35.09% 😞	35.43% 😞	0.34% 👍
ldm/modules/losses/vqperceptual.py	43.49% 😞	44.08% 😞	0.59% 👍
scripts/img2img.py	32.73% 😞	32.86% 😞	0.13% 👍
scripts/knn2img.py	42.00% 😞	43.03% 😞	1.03% 👍
scripts/sample_diffusion.py	54.95% 🙂	54.74% 🙂	-0.21% 👎
scripts/train_searcher.py	49.11% 😞	49.66% 😞	0.55% 👍
scripts/txt2img.py	28.77% 😞	29.39% 😞	0.62% 👍

Here are some functions in these files that still need a tune-up:

File	Function	Complexity	Length	Working Memory	Quality	Recommendation
ldm/modules/diffusionmodules/openaimodel.py	UNetModel.__init__	77 ⛔	831 ⛔	36 ⛔	1.01% ⛔	Refactor to reduce nesting. Try splitting into smaller methods. Extract out complex expressions
ldm/modules/image_degradation/bsrgan.py	degradation_bsrgan_plus	41 ⛔	459 ⛔	25 ⛔	7.90% ⛔	Refactor to reduce nesting. Try splitting into smaller methods. Extract out complex expressions
ldm/modules/x_transformer.py	AttentionLayers.__init__	29 😞	474 ⛔	28 ⛔	11.79% ⛔	Refactor to reduce nesting. Try splitting into smaller methods. Extract out complex expressions
ldm/models/diffusion/ddpm.py	LatentDiffusion.progressive_denoising	32 😞	394 ⛔	25 ⛔	11.84% ⛔	Refactor to reduce nesting. Try splitting into smaller methods. Extract out complex expressions
ldm/models/diffusion/ddpm.py	LatentDiffusion.log_images	28 😞	749 ⛔	27 ⛔	11.92% ⛔	Refactor to reduce nesting. Try splitting into smaller methods. Extract out complex expressions

Legend and Explanation

The emojis denote the absolute quality of the code:

⭐ excellent
🙂 good
😞 poor
⛔ very poor

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!

'Refactored by Sourcery'

6a44454

sourcery-ai bot requested a review from edson-github August 11, 2022 21:20

sourcery-ai bot commented Aug 11, 2022

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		print("Deleting key {} from state_dict.".format(k))
		print(f"Deleting key {k} from state_dict.")

		loss_dict_ema = {key + '_ema': loss_dict_ema[key] for key in loss_dict_ema}
		loss_dict_ema = {f'{key}_ema': loss_dict_ema[key] for key in loss_dict_ema}

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