prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  Add documentation in user guide on `torch.compile` usage
  - `torch.compile` "from-scratch" usage
  
  </issue>
  <code>
  [start of py/torch_tensorrt/dynamo/_settings.py]
  1 from dataclasses import dataclass, field
  2 from typing import Optional, Set
  3 
  4 import torch
  5 from torch_tensorrt._Device import Device
  6 from torch_tensorrt.dynamo._defaults import (
  7     DEBUG,
  8     ENABLE_EXPERIMENTAL_DECOMPOSITIONS,
  9     MAX_AUX_STREAMS,
  10     MIN_BLOCK_SIZE,
  11     OPTIMIZATION_LEVEL,
  12     PASS_THROUGH_BUILD_FAILURES,
  13     PRECISION,
  14     REQUIRE_FULL_COMPILATION,
  15     TRUNCATE_LONG_AND_DOUBLE,
  16     USE_FAST_PARTITIONER,
  17     USE_PYTHON_RUNTIME,
  18     VERSION_COMPATIBLE,
  19     WORKSPACE_SIZE,
  20     default_device,
  21 )
  22 
  23 
  24 @dataclass
  25 class CompilationSettings:
  26     """Compilation settings for Torch-TensorRT Dynamo Paths
  27 
  28     Args:
  29         precision (torch.dtype): Model Layer precision
  30         debug (bool): Whether to print out verbose debugging information
  31         workspace_size (int): Workspace TRT is allowed to use for the module (0 is default)
  32         min_block_size (int): Minimum number of operators per TRT-Engine Block
  33         torch_executed_ops (Sequence[str]): Sequence of operations to run in Torch, regardless of converter coverage
  34         pass_through_build_failures (bool): Whether to fail on TRT engine build errors (True) or not (False)
  35         max_aux_streams (Optional[int]): Maximum number of allowed auxiliary TRT streams for each engine
  36         version_compatible (bool): Provide version forward-compatibility for engine plan files
  37         optimization_level (Optional[int]): Builder optimization 0-5, higher levels imply longer build time,
  38             searching for more optimization options. TRT defaults to 3
  39         use_python_runtime (Optional[bool]): Whether to strictly use Python runtime or C++ runtime. To auto-select a runtime
  40             based on C++ dependency presence (preferentially choosing C++ runtime if available), leave the
  41             argument as None
  42         truncate_long_and_double (bool): Truncate int64/float64 TRT engine inputs or weights to int32/float32
  43         enable_experimental_decompositions (bool): Whether to enable all core aten decompositions
  44             or only a selected subset of them
  45     """
  46 
  47     precision: torch.dtype = PRECISION
  48     debug: bool = DEBUG
  49     workspace_size: int = WORKSPACE_SIZE
  50     min_block_size: int = MIN_BLOCK_SIZE
  51     torch_executed_ops: Set[str] = field(default_factory=set)
  52     pass_through_build_failures: bool = PASS_THROUGH_BUILD_FAILURES
  53     max_aux_streams: Optional[int] = MAX_AUX_STREAMS
  54     version_compatible: bool = VERSION_COMPATIBLE
  55     optimization_level: Optional[int] = OPTIMIZATION_LEVEL
  56     use_python_runtime: Optional[bool] = USE_PYTHON_RUNTIME
  57     truncate_long_and_double: bool = TRUNCATE_LONG_AND_DOUBLE
  58     use_fast_partitioner: bool = USE_FAST_PARTITIONER
  59     enable_experimental_decompositions: bool = ENABLE_EXPERIMENTAL_DECOMPOSITIONS
  60     device: Device = field(default_factory=default_device)
  61     require_full_compilation: bool = REQUIRE_FULL_COMPILATION
  62
  [end of py/torch_tensorrt/dynamo/_settings.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/py/torch_tensorrt/dynamo/_settings.py b/py/torch_tensorrt/dynamo/_settings.py
  --- a/py/torch_tensorrt/dynamo/_settings.py
  +++ b/py/torch_tensorrt/dynamo/_settings.py
  @@ -39,9 +39,13 @@
           use_python_runtime (Optional[bool]): Whether to strictly use Python runtime or C++ runtime. To auto-select a runtime
               based on C++ dependency presence (preferentially choosing C++ runtime if available), leave the
               argument as None
  -        truncate_long_and_double (bool): Truncate int64/float64 TRT engine inputs or weights to int32/float32
  +        truncate_long_and_double (bool): Whether to truncate int64/float64 TRT engine inputs or weights to int32/float32
  +        use_fast_partitioner (bool): Whether to use the fast or global graph partitioning system
           enable_experimental_decompositions (bool): Whether to enable all core aten decompositions
               or only a selected subset of them
  +        device (Device): GPU to compile the model on
  +        require_full_compilation (bool): Whether to require the graph is fully compiled in TensorRT.
  +            Only applicable for `ir="dynamo"`; has no effect for `torch.compile` path
       """
   
       precision: torch.dtype = PRECISION
  
verification_info: {"golden_diff": "diff --git a/py/torch_tensorrt/dynamo/_settings.py b/py/torch_tensorrt/dynamo/_settings.py\n--- a/py/torch_tensorrt/dynamo/_settings.py\n+++ b/py/torch_tensorrt/dynamo/_settings.py\n@@ -39,9 +39,13 @@\n         use_python_runtime (Optional[bool]): Whether to strictly use Python runtime or C++ runtime. To auto-select a runtime\n             based on C++ dependency presence (preferentially choosing C++ runtime if available), leave the\n             argument as None\n-        truncate_long_and_double (bool): Truncate int64/float64 TRT engine inputs or weights to int32/float32\n+        truncate_long_and_double (bool): Whether to truncate int64/float64 TRT engine inputs or weights to int32/float32\n+        use_fast_partitioner (bool): Whether to use the fast or global graph partitioning system\n         enable_experimental_decompositions (bool): Whether to enable all core aten decompositions\n             or only a selected subset of them\n+        device (Device): GPU to compile the model on\n+        require_full_compilation (bool): Whether to require the graph is fully compiled in TensorRT.\n+            Only applicable for `ir=\"dynamo\"`; has no effect for `torch.compile` path\n     \"\"\"\n \n     precision: torch.dtype = PRECISION\n", "issue": "Add documentation in user guide on `torch.compile` usage\n- `torch.compile` \"from-scratch\" usage\n", "before_files": [{"content": "from dataclasses import dataclass, field\nfrom typing import Optional, Set\n\nimport torch\nfrom torch_tensorrt._Device import Device\nfrom torch_tensorrt.dynamo._defaults import (\n    DEBUG,\n    ENABLE_EXPERIMENTAL_DECOMPOSITIONS,\n    MAX_AUX_STREAMS,\n    MIN_BLOCK_SIZE,\n    OPTIMIZATION_LEVEL,\n    PASS_THROUGH_BUILD_FAILURES,\n    PRECISION,\n    REQUIRE_FULL_COMPILATION,\n    TRUNCATE_LONG_AND_DOUBLE,\n    USE_FAST_PARTITIONER,\n    USE_PYTHON_RUNTIME,\n    VERSION_COMPATIBLE,\n    WORKSPACE_SIZE,\n    default_device,\n)\n\n\n@dataclass\nclass CompilationSettings:\n    \"\"\"Compilation settings for Torch-TensorRT Dynamo Paths\n\n    Args:\n        precision (torch.dtype): Model Layer precision\n        debug (bool): Whether to print out verbose debugging information\n        workspace_size (int): Workspace TRT is allowed to use for the module (0 is default)\n        min_block_size (int): Minimum number of operators per TRT-Engine Block\n        torch_executed_ops (Sequence[str]): Sequence of operations to run in Torch, regardless of converter coverage\n        pass_through_build_failures (bool): Whether to fail on TRT engine build errors (True) or not (False)\n        max_aux_streams (Optional[int]): Maximum number of allowed auxiliary TRT streams for each engine\n        version_compatible (bool): Provide version forward-compatibility for engine plan files\n        optimization_level (Optional[int]): Builder optimization 0-5, higher levels imply longer build time,\n            searching for more optimization options. TRT defaults to 3\n        use_python_runtime (Optional[bool]): Whether to strictly use Python runtime or C++ runtime. To auto-select a runtime\n            based on C++ dependency presence (preferentially choosing C++ runtime if available), leave the\n            argument as None\n        truncate_long_and_double (bool): Truncate int64/float64 TRT engine inputs or weights to int32/float32\n        enable_experimental_decompositions (bool): Whether to enable all core aten decompositions\n            or only a selected subset of them\n    \"\"\"\n\n    precision: torch.dtype = PRECISION\n    debug: bool = DEBUG\n    workspace_size: int = WORKSPACE_SIZE\n    min_block_size: int = MIN_BLOCK_SIZE\n    torch_executed_ops: Set[str] = field(default_factory=set)\n    pass_through_build_failures: bool = PASS_THROUGH_BUILD_FAILURES\n    max_aux_streams: Optional[int] = MAX_AUX_STREAMS\n    version_compatible: bool = VERSION_COMPATIBLE\n    optimization_level: Optional[int] = OPTIMIZATION_LEVEL\n    use_python_runtime: Optional[bool] = USE_PYTHON_RUNTIME\n    truncate_long_and_double: bool = TRUNCATE_LONG_AND_DOUBLE\n    use_fast_partitioner: bool = USE_FAST_PARTITIONER\n    enable_experimental_decompositions: bool = ENABLE_EXPERIMENTAL_DECOMPOSITIONS\n    device: Device = field(default_factory=default_device)\n    require_full_compilation: bool = REQUIRE_FULL_COMPILATION\n", "path": "py/torch_tensorrt/dynamo/_settings.py"}]}