prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  dropout1d
  
  
  </issue>
  <code>
  [start of ivy/functional/frontends/torch/nn/functional/dropout_functions.py]
  1 # local
  2 import ivy
  3 from ivy.func_wrapper import with_unsupported_dtypes
  4 
  5 from ivy.functional.frontends.torch.func_wrapper import to_ivy_arrays_and_back
  6 
  7 
  8 @to_ivy_arrays_and_back
  9 @with_unsupported_dtypes({"2.0.1 and below": ("float16",)}, "torch")
  10 def dropout(input, p=0.5, training=True, inplace=False):
  11     return ivy.dropout(input, p, training=training)
  12
  [end of ivy/functional/frontends/torch/nn/functional/dropout_functions.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/ivy/functional/frontends/torch/nn/functional/dropout_functions.py b/ivy/functional/frontends/torch/nn/functional/dropout_functions.py
  --- a/ivy/functional/frontends/torch/nn/functional/dropout_functions.py
  +++ b/ivy/functional/frontends/torch/nn/functional/dropout_functions.py
  @@ -9,3 +9,11 @@
   @with_unsupported_dtypes({"2.0.1 and below": ("float16",)}, "torch")
   def dropout(input, p=0.5, training=True, inplace=False):
       return ivy.dropout(input, p, training=training)
  +
  +
  +@to_ivy_arrays_and_back
  +@with_unsupported_dtypes({"2.0.1 and below": ("float16",)}, "torch")
  +def dropout1d(input, p=0.5, training=True, inplace=False):
  +    if inplace:
  +        return ivy.dropout1d(input, p, training=training, data_format="NCW", out=input)
  +    return ivy.dropout1d(input, p, training=training, data_format="NCW")
  
verification_info: {"golden_diff": "diff --git a/ivy/functional/frontends/torch/nn/functional/dropout_functions.py b/ivy/functional/frontends/torch/nn/functional/dropout_functions.py\n--- a/ivy/functional/frontends/torch/nn/functional/dropout_functions.py\n+++ b/ivy/functional/frontends/torch/nn/functional/dropout_functions.py\n@@ -9,3 +9,11 @@\n @with_unsupported_dtypes({\"2.0.1 and below\": (\"float16\",)}, \"torch\")\n def dropout(input, p=0.5, training=True, inplace=False):\n     return ivy.dropout(input, p, training=training)\n+\n+\n+@to_ivy_arrays_and_back\n+@with_unsupported_dtypes({\"2.0.1 and below\": (\"float16\",)}, \"torch\")\n+def dropout1d(input, p=0.5, training=True, inplace=False):\n+    if inplace:\n+        return ivy.dropout1d(input, p, training=training, data_format=\"NCW\", out=input)\n+    return ivy.dropout1d(input, p, training=training, data_format=\"NCW\")\n", "issue": "dropout1d\n\n", "before_files": [{"content": "# local\nimport ivy\nfrom ivy.func_wrapper import with_unsupported_dtypes\n\nfrom ivy.functional.frontends.torch.func_wrapper import to_ivy_arrays_and_back\n\n\n@to_ivy_arrays_and_back\n@with_unsupported_dtypes({\"2.0.1 and below\": (\"float16\",)}, \"torch\")\ndef dropout(input, p=0.5, training=True, inplace=False):\n    return ivy.dropout(input, p, training=training)\n", "path": "ivy/functional/frontends/torch/nn/functional/dropout_functions.py"}]}