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tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py

Summary

Maintainability
F
1 wk
Test Coverage

Function _verifyExponential has a Cognitive Complexity of 8 (exceeds 5 allowed). Consider refactoring.
Open

  def _verifyExponential(self, x, np_type):
    inp = x.astype(np_type)
    with test_util.use_gpu():
      tf_ans = linalg_impl.matrix_exponential(inp)
      if x.size == 0:
Severity: Minor
Found in tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py - About 45 mins 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

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

class MatrixExponentialBenchmark(test.Benchmark):

  shapes = [
      (4, 4),
      (10, 10),
Severity: Major
Found in tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py and 1 other location - About 4 days to fix
tensorflow/python/kernel_tests/linalg/determinant_op_test.py on lines 209..259

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 438.

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

  def testNonsymmetricReal(self):
    # 2x2 matrices
    matrix1 = np.array([[1., 2.], [3., 4.]])
    matrix2 = np.array([[1., 3.], [3., 5.]])
    self._verifyExponentialReal(matrix1)
Severity: Major
Found in tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py and 1 other location - About 4 hrs to fix
tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py on lines 102..109

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 80.

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

  def testSymmetricPositiveDefiniteReal(self):
    # 2x2 matrices
    matrix1 = np.array([[2., 1.], [1., 2.]])
    matrix2 = np.array([[3., -1.], [-1., 3.]])
    self._verifyExponentialReal(matrix1)
Severity: Major
Found in tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py and 1 other location - About 4 hrs to fix
tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py on lines 80..87

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 80.

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 4 locations. Consider refactoring.
Open

  def _makeBatch(self, matrix1, matrix2):
    matrix_batch = np.concatenate(
        [np.expand_dims(matrix1, 0),
         np.expand_dims(matrix2, 0)])
    matrix_batch = np.tile(matrix_batch, [2, 3, 1, 1])
Severity: Major
Found in tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py and 3 other locations - About 2 hrs to fix
tensorflow/python/kernel_tests/linalg/matrix_inverse_op_test.py on lines 69..74
tensorflow/python/kernel_tests/linalg/matrix_logarithm_op_test.py on lines 50..55
tensorflow/python/kernel_tests/linalg/matrix_square_root_op_test.py on lines 47..52

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 56.

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

      for scale_ in [0.01, 0.2, 0.5, 1.5, 6.0, 25.0]:
        name = "%s_%d_%d" % (dtype_.__name__, len(shape_), int(scale_ * 100))
        setattr(ExponentialOpTest, "testL1Norms_" + name,
                _TestL1Norms(dtype_, shape_, scale_))
Severity: Major
Found in tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py and 1 other location - About 2 hrs to fix
tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py on lines 253..256

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 53.

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

      for scale_ in [0.1, 1.5, 5.0, 20.0]:
        name = "%s_%d_%d" % (dtype_.__name__, len(shape_), int(scale_ * 10))
        setattr(ExponentialOpTest, "testL1Norms_" + name,
                _TestL1Norms(dtype_, shape_, scale_))
Severity: Major
Found in tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py and 1 other location - About 2 hrs to fix
tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py on lines 258..261

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 53.

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

  @test_util.run_deprecated_v1
  def testNonSquareMatrix(self):
    # When the exponential of a non-square matrix is attempted we should return
    # an error
    with self.assertRaises(ValueError):
Severity: Major
Found in tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py and 1 other location - About 1 hr to fix
tensorflow/python/kernel_tests/linalg/matrix_inverse_op_test.py on lines 110..115

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 46.

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 3 locations. Consider refactoring.
Open

  def testEmpty(self):
    self._verifyExponentialReal(np.empty([0, 2, 2]))
    self._verifyExponentialReal(np.empty([2, 0, 0]))
Severity: Major
Found in tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py and 2 other locations - About 1 hr to fix
tensorflow/python/kernel_tests/linalg/determinant_op_test.py on lines 154..156
tensorflow/python/kernel_tests/linalg/matrix_inverse_op_test.py on lines 133..135

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 44.

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

  @test_util.run_deprecated_v1
  def testWrongDimensions(self):
    # The input to the exponential should be at least a 2-dimensional tensor.
    tensor3 = constant_op.constant([1., 2.])
    with self.assertRaises(ValueError):
Severity: Major
Found in tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py and 1 other location - About 1 hr to fix
tensorflow/python/kernel_tests/linalg/matrix_inverse_op_test.py on lines 117..122

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 43.

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 9 locations. Consider refactoring.
Open

    matrix = np.random.uniform(
        low=-1.0, high=1.0, size=np.prod(shape)).reshape(shape).astype(dtype)
Severity: Major
Found in tensorflow/python/kernel_tests/linalg/matrix_exponential_op_test.py and 8 other locations - About 1 hr to fix
tensorflow/python/kernel_tests/linalg/matrix_inverse_op_test.py on lines 143..145
tensorflow/python/kernel_tests/linalg/qr_op_test.py on lines 128..129
tensorflow/python/kernel_tests/linalg/sparse/conjugate_gradient_test.py on lines 37..38
tensorflow/python/kernel_tests/linalg/svd_op_test.py on lines 193..194
tensorflow/python/kernel_tests/math_ops/tensordot_op_test.py on lines 155..157
tensorflow/python/kernel_tests/math_ops/tensordot_op_test.py on lines 158..160
tensorflow/python/kernel_tests/math_ops/tensordot_op_test.py on lines 209..210
tensorflow/python/kernel_tests/math_ops/tensordot_op_test.py on lines 211..212

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 39.

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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