prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  Using torch backend
  Using PyTorch backend.
  Epoch 1/3
  32/32 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - mean_absolute_error: 0.4083 - loss: 0.2566
  Epoch 2/3
  32/32 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - mean_absolute_error: 0.3805 - loss: 0.2151
  Epoch 3/3
  32/32 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - mean_absolute_error: 0.3704 - loss: 0.2056
  Epoch 1/5
  32/32 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - loss: 0.2699 - mae: 0.4200
  Epoch 2/5
  32/32 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - loss: 0.2409 - mae: 0.3940
  Epoch 3/5
  32/32 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - loss: 0.2271 - mae: 0.3856
  Epoch 4/5
  32/32 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - loss: 0.2174 - mae: 0.3785
  Epoch 5/5
  32/32 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - loss: 0.2120 - mae: 0.3699
  Epoch 1/3
  32/32 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - mean_absolute_error: 0.7020 - loss: 0.3334
  Epoch 2/3
  32/32 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - mean_absolute_error: 0.4075 - loss: 0.1271
  Epoch 3/3
  32/32 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - mean_absolute_error: 0.3776 - loss: 0.1010
  32/32 ━━━━━━━━━━━━━━━━━━━━ 0s 2ms/step - mean_absolute_error: 0.8608 - loss: 0.9672
  Traceback (most recent call last):
    File "E:\custom_train_step_in_torch.py", line 483, in <module>
      gan.fit(dataloader, epochs=1)
    File "C:\Python_310\lib\site-packages\keras_core\src\utils\traceback_utils.py", line 123, in error_handler
      raise e.with_traceback(filtered_tb) from None
    File "C:\Python_310\lib\site-packages\keras_core\src\utils\module_utils.py", line 26, in initialize
      raise ImportError(
  ImportError: This requires the tensorflow module. You can install it via `pip install tensorflow`
  
  </issue>
  <code>
  [start of keras_core/utils/module_utils.py]
  1 import importlib
  2 
  3 
  4 class LazyModule:
  5     def __init__(self, name, pip_name=None):
  6         self.name = name
  7         pip_name = pip_name or name
  8         self.pip_name = pip_name
  9         self.module = None
  10         self._available = None
  11 
  12     @property
  13     def available(self):
  14         if self._available is None:
  15             try:
  16                 self.initialize()
  17             except ImportError:
  18                 self._available = False
  19             self._available = True
  20         return self._available
  21 
  22     def initialize(self):
  23         try:
  24             self.module = importlib.import_module(self.name)
  25         except ImportError:
  26             raise ImportError(
  27                 f"This requires the {self.name} module. "
  28                 f"You can install it via `pip install {self.pip_name}`"
  29             )
  30 
  31     def __getattr__(self, name):
  32         if self.module is None:
  33             self.initialize()
  34         return getattr(self.module, name)
  35 
  36 
  37 tensorflow = LazyModule("tensorflow")
  38 gfile = LazyModule("tensorflow.io.gfile")
  39
  [end of keras_core/utils/module_utils.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/keras_core/utils/module_utils.py b/keras_core/utils/module_utils.py
  --- a/keras_core/utils/module_utils.py
  +++ b/keras_core/utils/module_utils.py
  @@ -14,9 +14,9 @@
           if self._available is None:
               try:
                   self.initialize()
  +                self._available = True
               except ImportError:
                   self._available = False
  -            self._available = True
           return self._available
   
       def initialize(self):
  
verification_info: {"golden_diff": "diff --git a/keras_core/utils/module_utils.py b/keras_core/utils/module_utils.py\n--- a/keras_core/utils/module_utils.py\n+++ b/keras_core/utils/module_utils.py\n@@ -14,9 +14,9 @@\n         if self._available is None:\n             try:\n                 self.initialize()\n+                self._available = True\n             except ImportError:\n                 self._available = False\n-            self._available = True\n         return self._available\n \n     def initialize(self):\n", "issue": "Using torch backend\nUsing PyTorch backend.\r\nEpoch 1/3\r\n32/32 \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 1s 4ms/step - mean_absolute_error: 0.4083 - loss: 0.2566\r\nEpoch 2/3\r\n32/32 \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 0s 4ms/step - mean_absolute_error: 0.3805 - loss: 0.2151\r\nEpoch 3/3\r\n32/32 \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 0s 4ms/step - mean_absolute_error: 0.3704 - loss: 0.2056\r\nEpoch 1/5\r\n32/32 \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 0s 4ms/step - loss: 0.2699 - mae: 0.4200\r\nEpoch 2/5\r\n32/32 \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 0s 4ms/step - loss: 0.2409 - mae: 0.3940\r\nEpoch 3/5\r\n32/32 \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 0s 4ms/step - loss: 0.2271 - mae: 0.3856\r\nEpoch 4/5\r\n32/32 \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 0s 4ms/step - loss: 0.2174 - mae: 0.3785\r\nEpoch 5/5\r\n32/32 \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 0s 4ms/step - loss: 0.2120 - mae: 0.3699\r\nEpoch 1/3\r\n32/32 \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 0s 4ms/step - mean_absolute_error: 0.7020 - loss: 0.3334\r\nEpoch 2/3\r\n32/32 \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 0s 4ms/step - mean_absolute_error: 0.4075 - loss: 0.1271\r\nEpoch 3/3\r\n32/32 \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 0s 4ms/step - mean_absolute_error: 0.3776 - loss: 0.1010\r\n32/32 \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 0s 2ms/step - mean_absolute_error: 0.8608 - loss: 0.9672\r\nTraceback (most recent call last):\r\n  File \"E:\\custom_train_step_in_torch.py\", line 483, in <module>\r\n    gan.fit(dataloader, epochs=1)\r\n  File \"C:\\Python_310\\lib\\site-packages\\keras_core\\src\\utils\\traceback_utils.py\", line 123, in error_handler\r\n    raise e.with_traceback(filtered_tb) from None\r\n  File \"C:\\Python_310\\lib\\site-packages\\keras_core\\src\\utils\\module_utils.py\", line 26, in initialize\r\n    raise ImportError(\r\nImportError: This requires the tensorflow module. You can install it via `pip install tensorflow`\n", "before_files": [{"content": "import importlib\n\n\nclass LazyModule:\n    def __init__(self, name, pip_name=None):\n        self.name = name\n        pip_name = pip_name or name\n        self.pip_name = pip_name\n        self.module = None\n        self._available = None\n\n    @property\n    def available(self):\n        if self._available is None:\n            try:\n                self.initialize()\n            except ImportError:\n                self._available = False\n            self._available = True\n        return self._available\n\n    def initialize(self):\n        try:\n            self.module = importlib.import_module(self.name)\n        except ImportError:\n            raise ImportError(\n                f\"This requires the {self.name} module. \"\n                f\"You can install it via `pip install {self.pip_name}`\"\n            )\n\n    def __getattr__(self, name):\n        if self.module is None:\n            self.initialize()\n        return getattr(self.module, name)\n\n\ntensorflow = LazyModule(\"tensorflow\")\ngfile = LazyModule(\"tensorflow.io.gfile\")\n", "path": "keras_core/utils/module_utils.py"}]}