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npdl/layers/pooling.py

Summary

Maintainability
F
1 wk
Test Coverage

Function backward has a Cognitive Complexity of 26 (exceeds 5 allowed). Consider refactoring.
Open

    def backward(self, pre_grad, *args, **kwargs):
        new_h, new_w = self.out_shape[-2:]
        pool_h, pool_w = self.pool_size
        length = np.prod(self.pool_size)
Severity: Minor
Found in npdl/layers/pooling.py - About 3 hrs to fix

Cognitive Complexity

Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

A method's cognitive complexity is based on a few simple rules:

  • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
  • Code is considered more complex for each "break in the linear flow of the code"
  • Code is considered more complex when "flow breaking structures are nested"

Further reading

Function forward has a Cognitive Complexity of 26 (exceeds 5 allowed). Consider refactoring.
Open

    def forward(self, input, *args, **kwargs):

        # shape
        self.input_shape = input.shape
        pool_h, pool_w = self.pool_size
Severity: Minor
Found in npdl/layers/pooling.py - About 3 hrs to fix

Cognitive Complexity

Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

A method's cognitive complexity is based on a few simple rules:

  • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
  • Code is considered more complex for each "break in the linear flow of the code"
  • Code is considered more complex when "flow breaking structures are nested"

Further reading

Function forward has a Cognitive Complexity of 26 (exceeds 5 allowed). Consider refactoring.
Open

    def forward(self, input, *args, **kwargs):
        # shape
        self.input_shape = input.shape
        pool_h, pool_w = self.pool_size
        new_h, new_w = self.out_shape[-2:]
Severity: Minor
Found in npdl/layers/pooling.py - About 3 hrs to fix

Cognitive Complexity

Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

A method's cognitive complexity is based on a few simple rules:

  • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
  • Code is considered more complex for each "break in the linear flow of the code"
  • Code is considered more complex when "flow breaking structures are nested"

Further reading

Function backward has a Cognitive Complexity of 26 (exceeds 5 allowed). Consider refactoring.
Open

    def backward(self, pre_grad, *args, **kwargs):
        new_h, new_w = self.out_shape[-2:]
        pool_h, pool_w = self.pool_size

        layer_grads = _zero(self.input_shape)
Severity: Minor
Found in npdl/layers/pooling.py - About 3 hrs to fix

Cognitive Complexity

Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

A method's cognitive complexity is based on a few simple rules:

  • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
  • Code is considered more complex for each "break in the linear flow of the code"
  • Code is considered more complex when "flow breaking structures are nested"

Further reading

Avoid deeply nested control flow statements.
Open

                        for w in np.arange(new_w):
                            outputs[a, b, h, w] = np.mean(input[a, b, h:h + pool_h, w:w + pool_w])
Severity: Major
Found in npdl/layers/pooling.py - About 45 mins to fix

    Avoid deeply nested control flow statements.
    Open

                            for w in np.arange(new_w):
                            patch = self.last_input[a, b, h:h + pool_h, w:w + pool_w]
                            max_idx = np.unravel_index(patch.argmax(), patch.shape)
                            h_shift, w_shift = h * pool_h + max_idx[0], w * pool_w + max_idx[1]
                            layer_grads[a, b, h_shift, w_shift] = pre_grad[a, b, a, w]
    Severity: Major
    Found in npdl/layers/pooling.py - About 45 mins to fix

      Avoid deeply nested control flow statements.
      Open

                              for w in np.arange(new_w):
                            h_shift, w_shift = h * pool_h, w * pool_w
                            layer_grads[a, b, h_shift: h_shift + pool_h, w_shift: w_shift + pool_w] = \
                                pre_grad[a, b, h, w] / length
      Severity: Major
      Found in npdl/layers/pooling.py - About 45 mins to fix

        Avoid deeply nested control flow statements.
        Open

                                for w in np.arange(new_w):
                            outputs[a, b, h, w] = np.max(input[a, b, h:h + pool_h, w:w + pool_w])
        Severity: Major
        Found in npdl/layers/pooling.py - About 45 mins to fix

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

                  if np.ndim(input) == 4:
            nb_batch, nb_axis, _, _ = input.shape

            for a in np.arange(nb_batch):
                for b in np.arange(nb_axis):
          Severity: Major
          Found in npdl/layers/pooling.py and 1 other location - About 2 days to fix
          npdl/layers/pooling.py on lines 155..173

          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 252.

          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

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

                  if np.ndim(input) == 4:
            nb_batch, nb_axis, _, _ = input.shape

            for a in np.arange(nb_batch):
                for b in np.arange(nb_axis):
          Severity: Major
          Found in npdl/layers/pooling.py and 1 other location - About 2 days to fix
          npdl/layers/pooling.py on lines 54..72

          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 252.

          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

                                      h_shift, w_shift = h * pool_h + max_idx[0], w * pool_w + max_idx[1]
          Severity: Major
          Found in npdl/layers/pooling.py and 1 other location - About 1 hr to fix
          npdl/layers/pooling.py on lines 203..203

          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 47.

          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

                                  h_shift, w_shift = h * pool_h + max_idx[0], w * pool_w + max_idx[1]
          Severity: Major
          Found in npdl/layers/pooling.py and 1 other location - About 1 hr to fix
          npdl/layers/pooling.py on lines 192..192

          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 47.

          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

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