function_name stringlengths 1 63 | docstring stringlengths 50 5.89k | masked_code stringlengths 50 882k | implementation stringlengths 169 12.9k | start_line int32 1 14.6k | end_line int32 16 14.6k | file_content stringlengths 274 882k |
|---|---|---|---|---|---|---|
add_collision_mesh | Add a collision mesh to the planning scene.
Parameters
----------
collision_mesh : :class:`compas_fab.robots.CollisionMesh`
Object containing the collision mesh to be added.
options : dict, optional
Unused parameter.
Returns
-------
``None`` | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from compas.utilities import await_callback
from compas_fab.backends.interfaces import AddCollisionMesh
from compas_fab.backends.ros.messages import ApplyPlanningSceneRequest
from compas_fab.backends.ros.messa... | def add_collision_mesh(self, collision_mesh, options=None):
"""Add a collision mesh to the planning scene.
Parameters
----------
collision_mesh : :class:`compas_fab.robots.CollisionMesh`
Object containing the collision mesh to be added.
options : dict, optional
... | 31 | 49 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from compas.utilities import await_callback
from compas_fab.backends.interfaces import AddCollisionMesh
from compas_fab.backends.ros.messages import ApplyPlanningSceneRequest
from compas_fab.backends.ros.messa... |
get_init_code | Gets initial latent codes as the start point for optimization.
The input image is assumed to have already been preprocessed, meaning to
have shape [self.G.image_channels, self.G.resolution, self.G.resolution],
channel order `self.G.channel_order`, and pixel range [self.G.min_val,
self.G.max_val]. | # python 3.7
"""Utility functions to invert a given image back to a latent code."""
from tqdm import tqdm
import cv2
import numpy as np
import torch
from models.stylegan_generator import StyleGANGenerator
from models.stylegan_encoder import StyleGANEncoder
from models.perceptual_model import PerceptualModel
__all__... | def get_init_code(self, image):
"""Gets initial latent codes as the start point for optimization.
The input image is assumed to have already been preprocessed, meaning to
have shape [self.G.image_channels, self.G.resolution, self.G.resolution],
channel order `self.G.channel_order`, and pixel range [s... | 131 | 142 | # python 3.7
"""Utility functions to invert a given image back to a latent code."""
from tqdm import tqdm
import cv2
import numpy as np
import torch
from models.stylegan_generator import StyleGANGenerator
from models.stylegan_encoder import StyleGANEncoder
from models.perceptual_model import PerceptualModel
__all__... |
state | A decorator that identifies which methods are states.
The presence of the farc_state attr, not the value of the attr,
determines statehood.
The Spy debugging system uses the farc_state attribute
to determine which methods inside a class are actually states.
Other uses of the attribute may come in the future. | import asyncio
import collections
import math
import signal
import sys
from functools import wraps
class Spy(object):
"""Spy is the debugging system for farc.
farc contains a handful of Spy.on_*() methods
placed at useful locations in the framework.
It is up to a Spy driver (such as the included VcdSp... | def state(func):
"""A decorator that identifies which methods are states.
The presence of the farc_state attr, not the value of the attr,
determines statehood.
The Spy debugging system uses the farc_state attribute
to determine which methods inside a class are actually states... | 168 | 183 | import asyncio
import collections
import math
import signal
import sys
from functools import wraps
class Spy(object):
"""Spy is the debugging system for farc.
farc contains a handful of Spy.on_*() methods
placed at useful locations in the framework.
It is up to a Spy driver (such as the included VcdSp... |
subscribe | Adds the given Ahsm to the subscriber table list
for the given signal. The argument, signame, is a string of the name
of the Signal to which the Ahsm is subscribing. Using a string allows
the Signal to be created in the registry if it is not already. | import asyncio
import collections
import math
import signal
import sys
from functools import wraps
class Spy(object):
"""Spy is the debugging system for farc.
farc contains a handful of Spy.on_*() methods
placed at useful locations in the framework.
It is up to a Spy driver (such as the included VcdSp... | @staticmethod
def subscribe(signame, act):
"""Adds the given Ahsm to the subscriber table list
for the given signal. The argument, signame, is a string of the name
of the Signal to which the Ahsm is subscribing. Using a string allows
the Signal to be created in the registry if ... | 439 | 449 | import asyncio
import collections
import math
import signal
import sys
from functools import wraps
class Spy(object):
"""Spy is the debugging system for farc.
farc contains a handful of Spy.on_*() methods
placed at useful locations in the framework.
It is up to a Spy driver (such as the included VcdSp... |
timeEventCallback | "The callback function for all TimeEvents.\nPosts the event to the event's target Ahsm.\nIf the Time(...TRUNCATED) | "import asyncio\nimport collections\nimport math\nimport signal\nimport sys\nfrom functools import w(...TRUNCATED) | " @staticmethod\n def timeEventCallback(tm_event, expiration):\n \"\"\"The callback fun(...TRUNCATED) | 538 | 571 | "import asyncio\nimport collections\nimport math\nimport signal\nimport sys\nfrom functools import w(...TRUNCATED) |
_apply_relativistic_doppler_shift | "Given a `SpectralQuantity` and a velocity, return a new `SpectralQuantity`\nthat is Doppler shifted(...TRUNCATED) | "import warnings\nfrom textwrap import indent\n\nimport astropy.units as u\nimport numpy as np\nfrom(...TRUNCATED) | "def _apply_relativistic_doppler_shift(scoord, velocity):\n \"\"\"\n Given a `SpectralQuantity(...TRUNCATED) | 53 | 85 | "import warnings\nfrom textwrap import indent\n\nimport astropy.units as u\nimport numpy as np\nfrom(...TRUNCATED) |
_validate_coordinate | "Checks the type of the frame and whether a velocity differential and a\ndistance has been defined o(...TRUNCATED) | "import warnings\nfrom textwrap import indent\n\nimport astropy.units as u\nimport numpy as np\nfrom(...TRUNCATED) | " @staticmethod\n def _validate_coordinate(coord, label=''):\n \"\"\"\n Checks t(...TRUNCATED) | 247 | 299 | "import warnings\nfrom textwrap import indent\n\nimport astropy.units as u\nimport numpy as np\nfrom(...TRUNCATED) |
replicate | "Return a replica of the `SpectralCoord`, optionally changing the\nvalues or attributes.\n\nNote tha(...TRUNCATED) | "import warnings\nfrom textwrap import indent\n\nimport astropy.units as u\nimport numpy as np\nfrom(...TRUNCATED) | " def replicate(self, value=None, unit=None,\n observer=None, target=None,\n (...TRUNCATED) | 301 | 374 | "import warnings\nfrom textwrap import indent\n\nimport astropy.units as u\nimport numpy as np\nfrom(...TRUNCATED) |
_normalized_position_vector | "Calculate the normalized position vector between two frames.\n\nParameters\n----------\nobserver : (...TRUNCATED) | "import warnings\nfrom textwrap import indent\n\nimport astropy.units as u\nimport numpy as np\nfrom(...TRUNCATED) | " @staticmethod\n def _normalized_position_vector(observer, target):\n \"\"\"\n (...TRUNCATED) | 519 | 546 | "import warnings\nfrom textwrap import indent\n\nimport astropy.units as u\nimport numpy as np\nfrom(...TRUNCATED) |
with_radial_velocity_shift | "Apply a velocity shift to this spectral coordinate.\n\nThe shift can be provided as a redshift (flo(...TRUNCATED) | "import warnings\nfrom textwrap import indent\n\nimport astropy.units as u\nimport numpy as np\nfrom(...TRUNCATED) | " def with_radial_velocity_shift(self, target_shift=None, observer_shift=None):\n \"\"\"\n(...TRUNCATED) | 635 | 716 | "import warnings\nfrom textwrap import indent\n\nimport astropy.units as u\nimport numpy as np\nfrom(...TRUNCATED) |
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Stack-Smol-Docstrings
This dataset contains Python functions extracted from the-stack-smol, filtered for high-quality docstrings and implementations. Each sample includes the function's docstring, implementation, and a masked version of the code where the function is replaced with a comment.
The dataset is designed for code completion tasks where a model needs to restore a function that has been replaced with a comment. The model is provided with:
- The full file context with the function replaced by a comment
- The docstring of the function
- The function name
The model's task is to generate code that replaces the comment with a proper implementation of the function based on the docstring and surrounding context.
Dataset Structure
Each sample contains:
function_name: Name of the functiondocstring: The function's docstringmasked_code: The full file with the function replaced by a commentimplementation: The original function implementationstart_line: The starting line number of the function in the original fileend_line: The ending line number of the function in the original filefile_content: The full original file content
Quality Filtering
Functions are filtered based on:
- Docstring quality (length, structure, descriptiveness)
- Implementation quality (no SQL strings, reasonable number of variables, sufficient complexity)
- Downloads last month
- 10