prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  Add consistency check for model data object in the CI tests
  We should take a snapshot of a "correct" model data object (as returned by `get_model_data()`) for the CI testing dataset and always compare the json-parsed outputs of `get_model_data` with it.
  
  Might be a bit tedious to alter every time when we run `get_model_data` ,but otherwise there are certain situation where we can get silent failures. Since certain parts of the Model Analyzer have more general exception catching built in (since certain data simply can't be produced in various situations) and `get_model_data` itself is made to work with incomplete data in order to return this data during training.
  
  If we want to be really scrupulous we should check the model data object at each phase of training, but I think that'd be overdoing it.
  
  </issue>
  <code>
  [start of mindsdb/__about__.py]
  1 __title__ = 'MindsDB'
  2 __package_name__ = 'mindsdb'
  3 __version__ = '1.7.11'
  4 __description__ = "MindsDB's goal is to make it very simple for developers to use the power of artificial neural networks in their projects."
  5 __email__ = "jorge@mindsdb.com"
  6 __author__ = 'MindsDB Inc'
  7 __github__ = 'https://github.com/mindsdb/mindsdb'
  8 __pypi__ = 'https://pypi.org/project/mindsdb'
  9 __license__ = 'MIT'
  10 __copyright__ = 'Copyright 2018- mindsdb'
  11
  [end of mindsdb/__about__.py]
  </code>
  
  I need you to solve this issue by generating a single patch file that I can apply directly to this repository using git apply. Please respond with a single patch file in the following format.
  <patch>
  diff --git a/file.py b/file.py
  --- a/file.py
  +++ b/file.py
  @@ -1,27 +1,35 @@
   def euclidean(a, b):
  -    while b:
  -        a, b = b, a % b
  -    return a
  +    if b == 0:
  +        return a
  +    return euclidean(b, a % b)
   
   
   def bresenham(x0, y0, x1, y1):
       points = []
       dx = abs(x1 - x0)
       dy = abs(y1 - y0)
  -    sx = 1 if x0 < x1 else -1
  -    sy = 1 if y0 < y1 else -1
  -    err = dx - dy
  +    x, y = x0, y0
  +    sx = -1 if x0 > x1 else 1
  +    sy = -1 if y0 > y1 else 1
   
  -    while True:
  -        points.append((x0, y0))
  -        if x0 == x1 and y0 == y1:
  -            break
  -        e2 = 2 * err
  -        if e2 > -dy:
  -            err -= dy
  -            x0 += sx
  -        if e2 < dx:
  -            err += dx
  -            y0 += sy
  +    if dx > dy:
  +        err = dx / 2.0
  +        while x != x1:
  +            points.append((x, y))
  +            err -= dy
  +            if err < 0:
  +                y += sy
  +                err += dx
  +            x += sx
  +    else:
  +        err = dy / 2.0
  +        while y != y1:
  +            points.append((x, y))
  +            err -= dx
  +            if err < 0:
  +                x += sx
  +                err += dy
  +            y += sy
  +
  +    points.append((x, y))
       return points
  
  </patch>
golden_diff: diff --git a/mindsdb/__about__.py b/mindsdb/__about__.py
  --- a/mindsdb/__about__.py
  +++ b/mindsdb/__about__.py
  @@ -1,6 +1,6 @@
   __title__ = 'MindsDB'
   __package_name__ = 'mindsdb'
  -__version__ = '1.7.11'
  +__version__ = '1.7.12'
   __description__ = "MindsDB's goal is to make it very simple for developers to use the power of artificial neural networks in their projects."
   __email__ = "jorge@mindsdb.com"
   __author__ = 'MindsDB Inc'
  
verification_info: {"golden_diff": "diff --git a/mindsdb/__about__.py b/mindsdb/__about__.py\n--- a/mindsdb/__about__.py\n+++ b/mindsdb/__about__.py\n@@ -1,6 +1,6 @@\n __title__ = 'MindsDB'\n __package_name__ = 'mindsdb'\n-__version__ = '1.7.11'\n+__version__ = '1.7.12'\n __description__ = \"MindsDB's goal is to make it very simple for developers to use the power of artificial neural networks in their projects.\"\n __email__ = \"jorge@mindsdb.com\"\n __author__ = 'MindsDB Inc'\n", "issue": "Add consistency check for model data object in the CI tests\nWe should take a snapshot of a \"correct\" model data object (as returned by `get_model_data()`) for the CI testing dataset and always compare the json-parsed outputs of `get_model_data` with it.\r\n\r\nMight be a bit tedious to alter every time when we run `get_model_data` ,but otherwise there are certain situation where we can get silent failures. Since certain parts of the Model Analyzer have more general exception catching built in (since certain data simply can't be produced in various situations) and `get_model_data` itself is made to work with incomplete data in order to return this data during training.\r\n\r\nIf we want to be really scrupulous we should check the model data object at each phase of training, but I think that'd be overdoing it.\n", "before_files": [{"content": "__title__ = 'MindsDB'\n__package_name__ = 'mindsdb'\n__version__ = '1.7.11'\n__description__ = \"MindsDB's goal is to make it very simple for developers to use the power of artificial neural networks in their projects.\"\n__email__ = \"jorge@mindsdb.com\"\n__author__ = 'MindsDB Inc'\n__github__ = 'https://github.com/mindsdb/mindsdb'\n__pypi__ = 'https://pypi.org/project/mindsdb'\n__license__ = 'MIT'\n__copyright__ = 'Copyright 2018- mindsdb'\n", "path": "mindsdb/__about__.py"}]}