How to use set_doc method in autotest

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1import chainerx2from chainerx import _docs3def set_docs():4 ndarray = chainerx.ndarray5 _docs.set_doc(6 ndarray,7 """ndarray(shape, dtype, device=None)8Multi-dimensional array, the central data structure of ChainerX.9This class, along with other APIs in the :mod:`chainerx` module, provides a10subset of NumPy APIs. This class works similar to :class:`numpy.ndarray`,11except for some differences including the following noticeable points:12- :class:`chainerx.ndarray` has a :attr:`device` attribute. It indicates on13 which device the array is allocated.14- :class:`chainerx.ndarray` supports :ref:`Define-by-Run <define_by_run>`15 backpropagation. Once you call :meth:`require_grad`, the array starts16 recording the operations applied to it recursively. Gradient of the result17 with respect to the original array can be computed then with the18 :meth:`backward` method or the :func:`chainerx.backward` function.19Args:20 shape (tuple of ints): Shape of the new array.21 dtype: Data type.22 device (~chainerx.Device): Device on which the array is allocated.23 If omitted, :ref:`the default device <chainerx_device>` is chosen.24.. seealso:: :class:`numpy.ndarray`25""")26 _docs.set_doc(27 ndarray.data_ptr,28 """int: Address of the underlying memory allocation.29The meaning of the address is device-dependent.30""")31 _docs.set_doc(32 ndarray.data_size,33 'int: Total size of the underlying memory allocation.')34 _docs.set_doc(35 ndarray.device, '~chainerx.Device: Device on which the data exists.')36 _docs.set_doc(ndarray.dtype, 'Data type of the array.')37 # TODO(beam2d): Write about backprop id.38 _docs.set_doc(39 ndarray.grad,40 """~chainerx.ndarray: Gradient held by the array.41It is ``None`` if the gradient is not available.42Setter of this property overwrites the gradient.43""")44 _docs.set_doc(45 ndarray.is_contiguous,46 'bool: ``True`` iff the array is stored in the C-contiguous order.')47 _docs.set_doc(ndarray.itemsize, 'int: Size of each element in bytes.')48 _docs.set_doc(49 ndarray.nbytes,50 """int: Total size of all elements in bytes.51It does not count skips between elements.""")52 _docs.set_doc(ndarray.ndim, 'int: Number of dimensions.')53 _docs.set_doc(54 ndarray.offset,55 'int: Offset of the first element from the memory allocation in bytes.'56 )57 _docs.set_doc(58 ndarray.shape,59 """tuple of int: Lengths of axes.60.. note::61 Currently, this property does not support setter.""")62 _docs.set_doc(ndarray.size, 'int: Number of elements in the array.')63 _docs.set_doc(ndarray.strides, 'tuple of int: Strides of axes in bytes.')64 _docs.set_doc(65 ndarray.T,66 """~chainerx.ndarray: Shape-reversed view of the array.67New array is created at every access to this property.68``x.T`` is just a shorthand of ``x.transpose()``.69""")70 _docs.set_doc(71 ndarray.__getitem__,72 """___getitem__(self, key)73Returns self[key].74.. note::75 Currently, only basic indexing is supported not advanced indexing.76""")77 def unary_op(name, s):78 _docs.set_doc(getattr(ndarray, name), '{}()\n{}'.format(name, s))79 unary_op('__bool__', 'Casts a size-one array into a :class:`bool` value.')80 unary_op('__float__',81 'Casts a size-one array into a :class:`float` value.')82 unary_op('__int__', 'Casts a size-one array into :class:`int` value.')83 unary_op('__len__', 'Returns the length of the first axis.')84 unary_op('__neg__', 'Computes ``-x`` elementwise.')85 def binary_op(name, s):86 _docs.set_doc(getattr(ndarray, name), '{}(other)\n{}'.format(name, s))87 binary_op('__eq__', 'Computes ``x == y`` elementwise.')88 binary_op('__ne__', 'Computes ``x != y`` elementwise.')89 binary_op('__lt__', 'Computes ``x < y`` elementwise.')90 binary_op('__le__', 'Computes ``x <= y`` elementwise.')91 binary_op('__ge__', 'Computes ``x >= y`` elementwise.')92 binary_op('__gt__', 'Computes ``x > y`` elementwise.')93 binary_op('__iadd__', 'Computes ``x += y`` elementwise.')94 binary_op('__isub__', 'Computes ``x -= y`` elementwise.')95 binary_op('__imul__', 'Computes ``x *= y`` elementwise.')96 binary_op('__itruediv__', 'Computes ``x /= y`` elementwise.')97 binary_op('__iand__', 'Computes ``x &= y`` elementwise.')98 binary_op('__ior__', 'Computes ``x |= y`` elementwise.')99 binary_op('__ixor__', 'Computes ``x ^= y`` elementwise.')100 binary_op('__add__', 'Computes ``x + y`` elementwise.')101 binary_op('__sub__', 'Computes ``x - y`` elementwise.')102 binary_op('__mul__', 'Computes ``x * y`` elementwise.')103 binary_op('__truediv__', 'Computes ``x / y`` elementwise.')104 binary_op('__and__', 'Computes ``x & y`` elementwise.')105 binary_op('__or__', 'Computes ``x | y`` elementwise.')106 binary_op('__xor__', 'Computes ``x ^ y`` elementwise.')107 binary_op('__radd__', 'Computes ``y + x`` elementwise.')108 binary_op('__rsub__', 'Computes ``y - x`` elementwise.')109 binary_op('__rmul__', 'Computes ``y * x`` elementwise.')110 binary_op('__rand__', 'Computes ``y & x`` elementwise.')111 binary_op('__ror__', 'Computes ``y | x`` elementwise.')112 binary_op('__rxor__', 'Computes ``y ^ x`` elementwise.')113 # TODO(beam2d): Write about as_grad_stopped(backprop_ids, copy) overload.114 _docs.set_doc(115 ndarray.as_grad_stopped,116 """as_grad_stopped(copy=False)117Creates a view or a copy of the array that stops gradient propagation.118This method behaves similar to :meth:`view` and :meth:`copy`, except that119the gradient is not propagated through this operation (internally, this120method creates a copy or view of the array without connecting the computational121graph for backprop).122Args:123 copy (bool): If ``True``, it copies the array. Otherwise, it returns a view124 of the original array.125Returns:126 ~chainerx.ndarray:127 A view or a copy of the array without propagating the gradient on128 backprop.129""")130 _docs.set_doc(131 ndarray.argmax,132 """argmax(axis=None)133Returns the indices of the maximum elements along a given axis.134See :func:`chainerx.argmax` for the full documentation.135""")136 _docs.set_doc(137 ndarray.argmin,138 """argmin(axis=None)139Returns the indices of the minimum elements along a given axis.140See :func:`chainerx.argmin` for the full documentation.141""")142 _docs.set_doc(143 ndarray.astype,144 """astype(dtype, copy=True)145Casts each element to the specified data type.146Args:147 dtype: Data type of the new array.148 copy (bool): If ``True``, this method always copies the data. Otherwise,149 it creates a view of the array if possible.150Returns:151 ~chainerx.ndarray: An array with the specified dtype.152""")153 _docs.set_doc(154 ndarray.backward,155 """backward(backprop_id=None, enable_double_backprop=False)156Performs backpropagation starting from this array.157This method is equivalent to ``chainerx.backward([self], *args)``.158See :func:`chainerx.backward` for the full documentation.159""")160 # TODO(beam2d): Write about backprop id.161 _docs.set_doc(162 ndarray.cleargrad,163 """cleargrad()164Clears the gradient held by this array.165""")166 _docs.set_doc(167 ndarray.copy,168 """copy()169Creates an array and copies all the elements to it.170The copied array is allocated on the same device as ``self``.171.. seealso:: :func:`chainerx.copy`172""")173 _docs.set_doc(174,175 """dot(b)176Returns the dot product with a given array.177See :func:`` for the full documentation.178""")179 _docs.set_doc(180 ndarray.fill,181 """fill(value)182Fills the array with a scalar value in place.183Args:184 value: Scalar value with which the array will be filled.185""")186 # TODO(beam2d): Write about backprop_id argument.187 _docs.set_doc(188 ndarray.get_grad,189 """get_grad()190Returns the gradient held by the array.191If the gradient is not available, it returns ``None``.192""")193 # TODO(beam2d): Write about backprop_id argument.194 _docs.set_doc(195 ndarray.is_backprop_required,196 """is_backprop_required()197Returns ``True`` if gradient propagates through this array on backprop.198See the note on :meth:`require_grad` for details.199""")200 # TODO(beam2d): Write about backprop_id argument.201 _docs.set_doc(202 ndarray.is_grad_required,203 """is_grad_required()204Returns ``True`` if the gradient will be set after backprop.205See the note on :meth:`require_grad` for details.206""")207 _docs.set_doc(208 ndarray.item,209 """item()210Copies an element of an array to a standard Python scalar and returns it.211Returns:212 z:213 A copy of the specified element of the array as a suitable Python214 scalar.215.. seealso:: :func:`numpy.item`216""")217 _docs.set_doc(218 ndarray.max,219 """max(axis=None, keepdims=False)220Returns the maximum along a given axis.221See :func:`chainerx.amax` for the full documentation.222""")223 _docs.set_doc(224 ndarray.min,225 """min(axis=None, keepdims=False)226Returns the minimum along a given axis.227See :func:`chainerx.amin` for the full documentation.228""")229 # TODO(beam2d): Write about backprop_id argument.230 _docs.set_doc(231 ndarray.require_grad,232 """require_grad()233Declares that a gradient for this array will be made available after backprop.234Once calling this method, any operations applied to this array are recorded for235later backprop. After backprop, the :attr:`grad` attribute holds the gradient236array.237.. note::238 ChainerX distinguishes *gradient requirements* and *backprop requirements*239 strictly. They are strongly related, but different concepts as follows.240 - *Gradient requirement* indicates that the gradient array should be made241 available after backprop. This attribute **is not propagated** through242 any operations. It implicates the backprop requirement.243 - *Backprop requirement* indicates that the gradient should be propagated244 through the array during backprop. This attribute **is propagated**245 through differentiable operations.246 :meth:`require_grad` sets the gradient requirement flag. If you need to247 extract the gradient after backprop, you have to call :meth:`require_grad`248 on the array even if the array is an intermediate result of differentiable249 computations.250Returns:251 ~chainerx.ndarray: ``self``252""")253 _docs.set_doc(254 ndarray.reshape,255 """reshape(newshape)256Creates an array with a new shape and the same data.257See :func:`chainerx.reshape` for the full documentation.258""")259 _docs.set_doc(260 ndarray.set_grad,261 """set_grad(grad)262Sets a gradient to the array.263This method overwrites the gradient with a given array.264Args:265 grad (~chainerx.ndarray): New gradient array.266""")267 _docs.set_doc(268 ndarray.squeeze,269 """squeeze(axis=None)270Removes size-one axes from an array.271See :func:`chainerx.squeeze` for the full documentation.272""")273 _docs.set_doc(274 ndarray.swapaxes,275 """swapaxes(axis1, axis2)276Interchange two axes of an array..277See :func:`chainerx.swapaxes` for the full documentation.278""")279 _docs.set_doc(280 ndarray.repeat,281 """repeat(repeats, axis=None)282Constructs an array by repeating a given array.283See :func:`chainerx.repeats` for the full documentation.284""")285 _docs.set_doc(286 ndarray.sum,287 """sum(axis=None, keepdims=False)288Returns the sum of an array along given axes.289See :func:`chainerx.sum` for the full documentation.290""")291 _docs.set_doc(292 ndarray.take,293 """take(indices, axis)294Takes elements from the array along an axis.295See :func:`chainerx.take` for the full documentation.296""")297 _docs.set_doc(298 ndarray.to_device,299 """to_device(device, index=None)300Transfers the array to the specified device.301Args:302 device (~chainerx.Device or str): Device to which the array is transferred,303 or a backend name. If it is a backend name, ``index`` should also be304 specified.305 index (int): Index of the device for the backend specified by ``device``.306Returns:307 ~chainerx.ndarray:308 An array on the target device.309 If the original array is already on the device, it is a view of that.310 Otherwise, it is a copy of the array on the target device.311""")312 _docs.set_doc(313 ndarray.transpose,314 """transpose(axes=None)315Creates a view of an array with permutated axes.316See :func:`chainerx.transpose` for the full documentation.317""")318 _docs.set_doc(319 ndarray.view,320 """view()321Returns a view of the array.322The returned array shares the underlying buffer, though it has a different323identity as a Python object....

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1import chainerx2from chainerx import _docs3def _set_docs_device():4 Device = chainerx.Device5 _docs.set_doc(6 Device,7 """Represents a physical computing unit.8""")9 _docs.set_doc(10 Device.synchronize,11 """Synchronizes the device.12""")13 _docs.set_doc(14,15 """Device name.16It is the backend name and the device index concatenated with a colon, e.g.17``native:0``.18Returns:19 str: Device name.20""")21 _docs.set_doc(22 Device.backend,23 """Backend to which this device belongs.24Returns:25 ~chainerx.Backend: Backend object.26""")27 _docs.set_doc(28 Device.context,29 """Context to which this device belongs.30Returns:31 ~chainerx.Context: Context object.32""")33 _docs.set_doc(34 Device.index,35 """Index of this device.36Returns:37 int: Index of this device.38""")39def set_docs():40 _set_docs_device()41 _docs.set_doc(42 chainerx.get_device,43 """get_device(*device)44Returns a device specified by the arguments.45If the argument is a single :class:`~chainerx.Device` instance, it's simply46returned.47Otherwise, there are three ways to specify a device:48.. testcode::49 # Specify a backend name and a device index separately.50 chainerx.get_device('native', 0)51 # Specify a backend name and a device index in a single string.52 chainerx.get_device('native:0')53 # Specify only a backend name. In this case device index 0 is chosen.54 chainerx.get_device('native')55Returns:56 ~chainerx.Device: Device object.57""")58 _docs.set_doc(59 chainerx.get_default_device,60 """get_default_device()61Returns the default device associated with the current thread.62Returns:63 ~chainerx.Device: The default device.64.. seealso::65 * :func:`chainerx.set_default_device`66 * :func:`chainerx.using_device`67""")68 _docs.set_doc(69 chainerx.set_default_device,70 """set_default_device(device)71Sets the given device as the default device of the current thread.72Args:73 device (~chainerx.Device or str): Device object or device name to set as74 the default device.75.. seealso::76 * :func:`chainerx.get_default_device`77 * :func:`chainerx.using_device`78""")79 _docs.set_doc(80 chainerx.using_device,81 """using_device(device)82Creates a context manager to temporarily set the default device.83Args:84 device (~chainerx.Device or str): Device object or device name to set as85 the default device during the context. See :data:``86 for the specification of device names.87.. seealso::88 * :func:`chainerx.get_default_device`89 * :func:`chainerx.set_default_device`...

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