prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  fourier_mix attention does not support mixed precision training
  Fourier mix attention does not support half precision.
  
  ```Traceback (most recent call last):
   ...
    File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1102, in _call_impl
      return forward_call(*input, **kwargs)
    File "/content/muzik/src/modules/xformer/custom_block_factory.py", line 196, in forward
      x = self.mha(q, k, v, att_mask=att_mask)
    File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1102, in _call_impl
      return forward_call(*input, **kwargs)
    File "/content/muzik/src/modules/xformer/custom_multi_head_dispatch.py", line 254, in forward
      y = self.attention(q=q, k=k, v=v, att_mask=att_mask)
    File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1102, in _call_impl
      return forward_call(*input, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/xformers/components/attention/fourier_mix.py", line 25, in forward
      att = torch.fft.fft2(q).real
  RuntimeError: Unsupported dtype Half```
  
  </issue>
  <code>
  [start of xformers/components/attention/fourier_mix.py]
  1 # Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
  2 #
  3 # This source code is licensed under the BSD license found in the
  4 # LICENSE file in the root directory of this source tree.
  5 
  6 import torch
  7 
  8 from xformers.components.attention import Attention, AttentionConfig, register_attention
  9 
  10 
  11 @register_attention("fourier_mix", AttentionConfig)
  12 class FourierMix(Attention):
  13     def __init__(self, dropout: float, *_, **__):
  14         """
  15         FFT-based pseudo-attention mechanism, from
  16         "
  17         "FNet: Mixing Tokens with Fourier Transforms"
  18         Lee-Thorp et al., 2021, https://arxiv.org/pdf/2105.03824.pdf
  19         """
  20         super().__init__()
  21         self.attn_drop = torch.nn.Dropout(dropout, inplace=False)
  22         self.requires_input_projection = False
  23 
  24     def forward(self, q: torch.Tensor, *_, **__):
  25         att = torch.fft.fft2(q).real
  26 
  27         att = self.attn_drop(att)
  28 
  29         return att
  30
  [end of xformers/components/attention/fourier_mix.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/xformers/components/attention/fourier_mix.py b/xformers/components/attention/fourier_mix.py
  --- a/xformers/components/attention/fourier_mix.py
  +++ b/xformers/components/attention/fourier_mix.py
  @@ -4,6 +4,7 @@
   # LICENSE file in the root directory of this source tree.
   
   import torch
  +from torch.cuda.amp import autocast
   
   from xformers.components.attention import Attention, AttentionConfig, register_attention
   
  @@ -22,7 +23,9 @@
           self.requires_input_projection = False
   
       def forward(self, q: torch.Tensor, *_, **__):
  -        att = torch.fft.fft2(q).real
  +        # Guard against autocast / fp16, not supported by torch.fft.fft2
  +        with autocast(enabled=False):
  +            att = torch.fft.fft2(q).real
   
           att = self.attn_drop(att)
  
verification_info: {"golden_diff": "diff --git a/xformers/components/attention/fourier_mix.py b/xformers/components/attention/fourier_mix.py\n--- a/xformers/components/attention/fourier_mix.py\n+++ b/xformers/components/attention/fourier_mix.py\n@@ -4,6 +4,7 @@\n # LICENSE file in the root directory of this source tree.\n \n import torch\n+from torch.cuda.amp import autocast\n \n from xformers.components.attention import Attention, AttentionConfig, register_attention\n \n@@ -22,7 +23,9 @@\n         self.requires_input_projection = False\n \n     def forward(self, q: torch.Tensor, *_, **__):\n-        att = torch.fft.fft2(q).real\n+        # Guard against autocast / fp16, not supported by torch.fft.fft2\n+        with autocast(enabled=False):\n+            att = torch.fft.fft2(q).real\n \n         att = self.attn_drop(att)\n", "issue": "fourier_mix attention does not support mixed precision training\nFourier mix attention does not support half precision.\r\n\r\n```Traceback (most recent call last):\r\n ...\r\n  File \"/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py\", line 1102, in _call_impl\r\n    return forward_call(*input, **kwargs)\r\n  File \"/content/muzik/src/modules/xformer/custom_block_factory.py\", line 196, in forward\r\n    x = self.mha(q, k, v, att_mask=att_mask)\r\n  File \"/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py\", line 1102, in _call_impl\r\n    return forward_call(*input, **kwargs)\r\n  File \"/content/muzik/src/modules/xformer/custom_multi_head_dispatch.py\", line 254, in forward\r\n    y = self.attention(q=q, k=k, v=v, att_mask=att_mask)\r\n  File \"/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py\", line 1102, in _call_impl\r\n    return forward_call(*input, **kwargs)\r\n  File \"/usr/local/lib/python3.7/dist-packages/xformers/components/attention/fourier_mix.py\", line 25, in forward\r\n    att = torch.fft.fft2(q).real\r\nRuntimeError: Unsupported dtype Half```\n", "before_files": [{"content": "# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.\n#\n# This source code is licensed under the BSD license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport torch\n\nfrom xformers.components.attention import Attention, AttentionConfig, register_attention\n\n\n@register_attention(\"fourier_mix\", AttentionConfig)\nclass FourierMix(Attention):\n    def __init__(self, dropout: float, *_, **__):\n        \"\"\"\n        FFT-based pseudo-attention mechanism, from\n        \"\n        \"FNet: Mixing Tokens with Fourier Transforms\"\n        Lee-Thorp et al., 2021, https://arxiv.org/pdf/2105.03824.pdf\n        \"\"\"\n        super().__init__()\n        self.attn_drop = torch.nn.Dropout(dropout, inplace=False)\n        self.requires_input_projection = False\n\n    def forward(self, q: torch.Tensor, *_, **__):\n        att = torch.fft.fft2(q).real\n\n        att = self.attn_drop(att)\n\n        return att\n", "path": "xformers/components/attention/fourier_mix.py"}]}