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gae/optimizer.py

Summary

Maintainability
B
5 hrs
Test Coverage

Function __init__ has 6 arguments (exceeds 4 allowed). Consider refactoring.
Open

    def __init__(self, preds, labels, model, num_nodes, pos_weight, norm):
Severity: Minor
Found in gae/optimizer.py - About 45 mins to fix

    Identical blocks of code found in 2 locations. Consider refactoring.
    Open

            self.correct_prediction = tf.equal(tf.cast(tf.greater_equal(tf.sigmoid(preds_sub), 0.5), tf.int32),
                                           tf.cast(labels_sub, tf.int32))
    Severity: Major
    Found in gae/optimizer.py and 1 other location - About 1 hr to fix
    gae/optimizer.py on lines 18..19

    Duplicated Code

    Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

    Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

    When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

    Tuning

    This issue has a mass of 45.

    We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

    The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

    If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

    See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

    Refactorings

    Further Reading

    Identical blocks of code found in 2 locations. Consider refactoring.
    Open

            self.correct_prediction = tf.equal(tf.cast(tf.greater_equal(tf.sigmoid(preds_sub), 0.5), tf.int32),
                                           tf.cast(labels_sub, tf.int32))
    Severity: Major
    Found in gae/optimizer.py and 1 other location - About 1 hr to fix
    gae/optimizer.py on lines 40..41

    Duplicated Code

    Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

    Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

    When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

    Tuning

    This issue has a mass of 45.

    We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

    The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

    If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

    See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

    Refactorings

    Further Reading

    Identical blocks of code found in 2 locations. Consider refactoring.
    Open

            self.cost = norm * tf.reduce_mean(tf.nn.weighted_cross_entropy_with_logits(logits=preds_sub, targets=labels_sub, pos_weight=pos_weight))
    Severity: Minor
    Found in gae/optimizer.py and 1 other location - About 45 mins to fix
    gae/optimizer.py on lines 28..28

    Duplicated Code

    Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

    Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

    When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

    Tuning

    This issue has a mass of 35.

    We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

    The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

    If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

    See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

    Refactorings

    Further Reading

    Identical blocks of code found in 2 locations. Consider refactoring.
    Open

            self.cost = norm * tf.reduce_mean(tf.nn.weighted_cross_entropy_with_logits(logits=preds_sub, targets=labels_sub, pos_weight=pos_weight))
    Severity: Minor
    Found in gae/optimizer.py and 1 other location - About 45 mins to fix
    gae/optimizer.py on lines 12..12

    Duplicated Code

    Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

    Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

    When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

    Tuning

    This issue has a mass of 35.

    We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

    The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

    If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

    See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

    Refactorings

    Further Reading

    Line too long (100 > 79 characters)
    Open

            self.optimizer = tf.train.AdamOptimizer(learning_rate=FLAGS.learning_rate)  # Adam Optimizer
    Severity: Minor
    Found in gae/optimizer.py by pep8

    Limit all lines to a maximum of 79 characters.

    There are still many devices around that are limited to 80 character
lines; plus, limiting windows to 80 characters makes it possible to
have several windows side-by-side.  The default wrapping on such
devices looks ugly.  Therefore, please limit all lines to a maximum
of 79 characters. For flowing long blocks of text (docstrings or
comments), limiting the length to 72 characters is recommended.

Reports error E501.

    Line too long (118 > 79 characters)
    Open

            self.kl = (0.5 / num_nodes) * tf.reduce_mean(tf.reduce_sum(1 + 2 * model.z_log_std - tf.square(model.z_mean) -
    Severity: Minor
    Found in gae/optimizer.py by pep8

    Limit all lines to a maximum of 79 characters.

    There are still many devices around that are limited to 80 character
lines; plus, limiting windows to 80 characters makes it possible to
have several windows side-by-side.  The default wrapping on such
devices looks ugly.  Therefore, please limit all lines to a maximum
of 79 characters. For flowing long blocks of text (docstrings or
comments), limiting the length to 72 characters is recommended.

Reports error E501.

    Line too long (144 > 79 characters)
    Open

            self.cost = norm * tf.reduce_mean(tf.nn.weighted_cross_entropy_with_logits(logits=preds_sub, targets=labels_sub, pos_weight=pos_weight))
    Severity: Minor
    Found in gae/optimizer.py by pep8

    Limit all lines to a maximum of 79 characters.

    There are still many devices around that are limited to 80 character
lines; plus, limiting windows to 80 characters makes it possible to
have several windows side-by-side.  The default wrapping on such
devices looks ugly.  Therefore, please limit all lines to a maximum
of 79 characters. For flowing long blocks of text (docstrings or
comments), limiting the length to 72 characters is recommended.

Reports error E501.

    Line too long (84 > 79 characters)
    Open

            self.accuracy = tf.reduce_mean(tf.cast(self.correct_prediction, tf.float32))
    Severity: Minor
    Found in gae/optimizer.py by pep8

    Limit all lines to a maximum of 79 characters.

    There are still many devices around that are limited to 80 character
lines; plus, limiting windows to 80 characters makes it possible to
have several windows side-by-side.  The default wrapping on such
devices looks ugly.  Therefore, please limit all lines to a maximum
of 79 characters. For flowing long blocks of text (docstrings or
comments), limiting the length to 72 characters is recommended.

Reports error E501.

    Line too long (84 > 79 characters)
    Open

            self.accuracy = tf.reduce_mean(tf.cast(self.correct_prediction, tf.float32))
    Severity: Minor
    Found in gae/optimizer.py by pep8

    Limit all lines to a maximum of 79 characters.

    There are still many devices around that are limited to 80 character
lines; plus, limiting windows to 80 characters makes it possible to
have several windows side-by-side.  The default wrapping on such
devices looks ugly.  Therefore, please limit all lines to a maximum
of 79 characters. For flowing long blocks of text (docstrings or
comments), limiting the length to 72 characters is recommended.

Reports error E501.

    Line too long (106 > 79 characters)
    Open

                                                                       tf.square(tf.exp(model.z_log_std)), 1))
    Severity: Minor
    Found in gae/optimizer.py by pep8

    Limit all lines to a maximum of 79 characters.

    There are still many devices around that are limited to 80 character
lines; plus, limiting windows to 80 characters makes it possible to
have several windows side-by-side.  The default wrapping on such
devices looks ugly.  Therefore, please limit all lines to a maximum
of 79 characters. For flowing long blocks of text (docstrings or
comments), limiting the length to 72 characters is recommended.

Reports error E501.

    Line too long (107 > 79 characters)
    Open

            self.correct_prediction = tf.equal(tf.cast(tf.greater_equal(tf.sigmoid(preds_sub), 0.5), tf.int32),
    Severity: Minor
    Found in gae/optimizer.py by pep8

    Limit all lines to a maximum of 79 characters.

    There are still many devices around that are limited to 80 character
lines; plus, limiting windows to 80 characters makes it possible to
have several windows side-by-side.  The default wrapping on such
devices looks ugly.  Therefore, please limit all lines to a maximum
of 79 characters. For flowing long blocks of text (docstrings or
comments), limiting the length to 72 characters is recommended.

Reports error E501.

    Line too long (144 > 79 characters)
    Open

            self.cost = norm * tf.reduce_mean(tf.nn.weighted_cross_entropy_with_logits(logits=preds_sub, targets=labels_sub, pos_weight=pos_weight))
    Severity: Minor
    Found in gae/optimizer.py by pep8

    Limit all lines to a maximum of 79 characters.

    There are still many devices around that are limited to 80 character
lines; plus, limiting windows to 80 characters makes it possible to
have several windows side-by-side.  The default wrapping on such
devices looks ugly.  Therefore, please limit all lines to a maximum
of 79 characters. For flowing long blocks of text (docstrings or
comments), limiting the length to 72 characters is recommended.

Reports error E501.

    Line too long (100 > 79 characters)
    Open

            self.optimizer = tf.train.AdamOptimizer(learning_rate=FLAGS.learning_rate)  # Adam Optimizer
    Severity: Minor
    Found in gae/optimizer.py by pep8

    Limit all lines to a maximum of 79 characters.

    There are still many devices around that are limited to 80 character
lines; plus, limiting windows to 80 characters makes it possible to
have several windows side-by-side.  The default wrapping on such
devices looks ugly.  Therefore, please limit all lines to a maximum
of 79 characters. For flowing long blocks of text (docstrings or
comments), limiting the length to 72 characters is recommended.

Reports error E501.

    Line too long (107 > 79 characters)
    Open

            self.correct_prediction = tf.equal(tf.cast(tf.greater_equal(tf.sigmoid(preds_sub), 0.5), tf.int32),
    Severity: Minor
    Found in gae/optimizer.py by pep8

    Limit all lines to a maximum of 79 characters.

    There are still many devices around that are limited to 80 character
lines; plus, limiting windows to 80 characters makes it possible to
have several windows side-by-side.  The default wrapping on such
devices looks ugly.  Therefore, please limit all lines to a maximum
of 79 characters. For flowing long blocks of text (docstrings or
comments), limiting the length to 72 characters is recommended.

Reports error E501.

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