Sourcery Starbot ⭐ refactored jevenzh/deepplantphenomics #1
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
SourceryAI
commented
Aug 14, 2023
Comment on lines
-142
to
+146
| return next(layer for layer in self.__layers if isinstance(layer, layers.convLayer) or isinstance(layer, layers.fullyConnectedLayer)) | ||
| return next( | ||
| layer | ||
| for layer in self.__layers | ||
| if isinstance(layer, (layers.convLayer, layers.fullyConnectedLayer)) | ||
| ) |
There was a problem hiding this comment.
Function DPPModel.__first_layer refactored with the following changes:
- Merge isinstance calls (
merge-isinstance)
Comment on lines
-35
to
+53
| self.weights = tf.get_variable(self.name + '_weights', | ||
| shape=self.filter_dimension, | ||
| initializer=tf.contrib.layers.xavier_initializer_conv2d()) | ||
| self.weights = tf.get_variable( | ||
| f'{self.name}_weights', | ||
| shape=self.filter_dimension, | ||
| initializer=tf.contrib.layers.xavier_initializer_conv2d(), | ||
| ) | ||
| else: | ||
| self.weights = tf.get_variable(self.name + '_weights', | ||
| shape=self.filter_dimension, | ||
| initializer=tf.truncated_normal_initializer(stddev=5e-2), | ||
| dtype=tf.float32) | ||
|
|
||
| self.biases = tf.get_variable(self.name + '_bias', | ||
| [self.output_size[-1]], | ||
| initializer=tf.constant_initializer(0.1), | ||
| dtype=tf.float32) | ||
| self.weights = tf.get_variable( | ||
| f'{self.name}_weights', | ||
| shape=self.filter_dimension, | ||
| initializer=tf.truncated_normal_initializer(stddev=5e-2), | ||
| dtype=tf.float32, | ||
| ) | ||
|
|
||
| self.biases = tf.get_variable( | ||
| f'{self.name}_bias', | ||
| [self.output_size[-1]], | ||
| initializer=tf.constant_initializer(0.1), | ||
| dtype=tf.float32, | ||
| ) |
There was a problem hiding this comment.
Function convLayer.__init__ refactored with the following changes:
- Use f-string instead of string concatenation [×3] (
use-fstring-for-concatenation)
Comment on lines
-134
to
+160
| self.weights = tf.get_variable(self.name + '_weights', shape=[vec_size, output_size], | ||
| initializer=tf.contrib.layers.xavier_initializer()) | ||
| self.weights = tf.get_variable( | ||
| f'{self.name}_weights', | ||
| shape=[vec_size, output_size], | ||
| initializer=tf.contrib.layers.xavier_initializer(), | ||
| ) | ||
| else: | ||
| self.weights = tf.get_variable(self.name + '_weights', | ||
| shape=[vec_size, output_size], | ||
| initializer=tf.truncated_normal_initializer(stddev=math.sqrt(2.0/self.output_size)), | ||
| dtype=tf.float32) | ||
|
|
||
| self.biases = tf.get_variable(self.name + '_bias', | ||
| [self.output_size], | ||
| initializer=tf.constant_initializer(0.1), | ||
| dtype=tf.float32) | ||
| self.weights = tf.get_variable( | ||
| f'{self.name}_weights', | ||
| shape=[vec_size, output_size], | ||
| initializer=tf.truncated_normal_initializer( | ||
| stddev=math.sqrt(2.0 / self.output_size) | ||
| ), | ||
| dtype=tf.float32, | ||
| ) | ||
|
|
||
| self.biases = tf.get_variable( | ||
| f'{self.name}_bias', | ||
| [self.output_size], | ||
| initializer=tf.constant_initializer(0.1), | ||
| dtype=tf.float32, | ||
| ) |
There was a problem hiding this comment.
Function fullyConnectedLayer.__init__ refactored with the following changes:
- Use f-string instead of string concatenation [×3] (
use-fstring-for-concatenation)
Comment on lines
-205
to
+220
| if deterministic: | ||
| return x | ||
| else: | ||
| return tf.nn.dropout(x, self.p) | ||
| return x if deterministic else tf.nn.dropout(x, self.p) |
There was a problem hiding this comment.
Function dropoutLayer.forward_pass refactored with the following changes:
- Replace if statement with if expression (
assign-if-exp)
| dense = tf.reshape(values, (batch_size, num_outputs)) | ||
|
|
||
| return dense | ||
| return tf.reshape(values, (batch_size, num_outputs)) |
There was a problem hiding this comment.
Function label_string_to_tensor refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
Comment on lines
-101
to
+99
| unique = set([label.strip() for label in labels]) | ||
| unique = {label.strip() for label in labels} |
There was a problem hiding this comment.
Function string_labels_to_sequential refactored with the following changes:
- Replace list(), dict() or set() with comprehension (
collection-builtin-to-comprehension) - Replace unneeded comprehension with generator (
comprehension-to-generator)
| y = self.model.forward_pass_with_file_inputs(x) | ||
|
|
||
| return y | ||
| return self.model.forward_pass_with_file_inputs(x) |
There was a problem hiding this comment.
Function arabidopsisStrainClassifier.forward_pass refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
Comment on lines
37
to
38
| labels = [mapping[index] for index in indices] | ||
|
|
||
| return labels No newline at end of file | ||
| return [mapping[index] for index in indices] |
There was a problem hiding this comment.
Function tools.classify_arabidopsis_strain refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Thanks for starring sourcery-ai/sourcery ✨ 🌟 ✨
Here's your pull request refactoring your most popular Python repo.
If you want Sourcery to refactor all your Python repos and incoming pull requests install our bot.
Review changes via command line
To manually merge these changes, make sure you're on the
masterbranch, then run: