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from ..math import * import ivy from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back import ivy from ivy.func_wrapper import ( with_unsupported_dtypes, with_supported_dtypes, with_supported_device_and_dt...
null
146,689
from ..math import * import ivy from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back import ivy from ivy.func_wrapper import ( with_unsupported_dtypes, with_supported_dtypes, with_supported_device_and_dt...
null
146,690
from ..math import * import ivy from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back import ivy from ivy.func_wrapper import ( with_unsupported_dtypes, with_supported_dtypes, with_supported_device_and_dt...
null
146,691
from ..math import * import ivy from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back import ivy from ivy.func_wrapper import ( with_unsupported_dtypes, with_supported_dtypes, with_supported_device_and_dt...
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146,692
from ..math import * import ivy from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back import ivy from ivy.func_wrapper import ( with_unsupported_dtypes, with_supported_dtypes, with_supported_device_and_dt...
null
146,693
from ..math import * import ivy from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back import ivy from ivy.func_wrapper import ( with_unsupported_dtypes, with_supported_dtypes, with_supported_device_and_dt...
null
146,694
from ..math import * import ivy from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back import ivy from ivy.func_wrapper import ( with_unsupported_dtypes, with_supported_dtypes, with_supported_device_and_dt...
null
146,695
from ..math import * import ivy from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back import ivy from ivy.func_wrapper import ( with_unsupported_dtypes, with_supported_dtypes, with_supported_device_and_dt...
null
146,696
from ..math import * import ivy from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back import ivy from ivy.func_wrapper import ( with_unsupported_dtypes, with_supported_dtypes, with_supported_device_and_dt...
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146,697
from ..math import * import ivy from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back import ivy from ivy.func_wrapper import ( with_unsupported_dtypes, with_supported_dtypes, with_supported_device_and_dt...
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146,698
from ..manipulation import * import ivy from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) from ivy.func_wrapper import with_unsupported_dtypes import ivy from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) from ivy.func_wrapper import ( w...
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from ..manipulation import * import ivy from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) from ivy.func_wrapper import with_unsupported_dtypes import ivy from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) from ivy.func_wrapper import ( w...
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from ..random import * import ivy from ivy.func_wrapper import with_supported_dtypes from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) import ivy from ivy.func_wrapper import with_supported_dtypes from ivy.func_wrapper import with_supported_device_and_dtypes, with_unsupported_dt...
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from ..random import * import ivy from ivy.func_wrapper import with_supported_dtypes from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) import ivy from ivy.func_wrapper import with_supported_dtypes from ivy.func_wrapper import with_supported_device_and_dtypes, with_unsupported_dt...
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import ivy from ivy.func_wrapper import with_supported_dtypes from ivy.func_wrapper import with_supported_device_and_dtypes, with_unsupported_dtypes from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) import ivy from ivy.utils.exceptions import handle_exceptions from ivy.functional...
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import ivy from ivy.func_wrapper import with_supported_dtypes from ivy.func_wrapper import with_supported_device_and_dtypes, with_unsupported_dtypes from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) import ivy from ivy.utils.exceptions import handle_exceptions from ivy.functional...
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import ivy from ivy.func_wrapper import with_supported_dtypes from ivy.func_wrapper import with_supported_device_and_dtypes, with_unsupported_dtypes from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) import ivy from ivy.utils.exceptions import handle_exceptions from ivy.functional...
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import ivy from ivy.func_wrapper import with_supported_dtypes from ivy.func_wrapper import with_supported_device_and_dtypes, with_unsupported_dtypes from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) import ivy from ivy.utils.exceptions import handle_exceptions from ivy.functional...
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import ivy from ivy.func_wrapper import with_supported_dtypes from ivy.func_wrapper import with_supported_device_and_dtypes, with_unsupported_dtypes from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) def randint(low=0, high=None, shape=[1], dtype=None, name=None): return ivy.ra...
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import ivy from ivy.func_wrapper import with_supported_dtypes from ivy.func_wrapper import with_supported_device_and_dtypes, with_unsupported_dtypes from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) import ivy from ivy.utils.exceptions import handle_exceptions from ivy.functional...
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import ivy from ivy.func_wrapper import with_supported_dtypes from ivy.func_wrapper import with_supported_device_and_dtypes, with_unsupported_dtypes from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) import ivy from ivy.utils.exceptions import handle_exceptions from ivy.functional...
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import ivy from ivy.func_wrapper import with_supported_dtypes from ivy.func_wrapper import with_supported_device_and_dtypes, with_unsupported_dtypes from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) import ivy from ivy.utils.exceptions import handle_exceptions from ivy.functional...
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import ivy from ivy.func_wrapper import ( with_supported_dtypes, with_unsupported_device_and_dtypes, ) from ..tensor.tensor import Tensor from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) def _blend_images(img1, img2, ratio): # TODO: ivy.check_float(img1) returns False...
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import ivy from ivy.func_wrapper import ( with_supported_dtypes, with_unsupported_device_and_dtypes, ) from ..tensor.tensor import Tensor from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) def _get_image_num_channels(img, data_format): def _hsv_to_rgb(img): def _rgb_to_hsv(...
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import ivy from ivy.func_wrapper import ( with_supported_dtypes, with_unsupported_device_and_dtypes, ) from ..tensor.tensor import Tensor from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) def hflip(img): img = ivy.array(img) return ivy.flip(img, axis=-1)
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import ivy from ivy.func_wrapper import ( with_supported_dtypes, with_unsupported_device_and_dtypes, ) from ..tensor.tensor import Tensor from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) def normalize(img, mean, std, data_format="CHW", to_rgb=False): if ivy.is_array(...
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import ivy from ivy.func_wrapper import ( with_supported_dtypes, with_unsupported_device_and_dtypes, ) from ..tensor.tensor import Tensor from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) def pad(img, padding, fill=0, padding_mode="constant"): dim_size = img.ndim ...
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import ivy from ivy.func_wrapper import ( with_supported_dtypes, with_unsupported_device_and_dtypes, ) from ..tensor.tensor import Tensor from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) class Tensor: def __init__(self, array, dtype=None, place="cpu", stop_gradient=T...
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import ivy from ivy.func_wrapper import ( with_supported_dtypes, with_unsupported_device_and_dtypes, ) from ..tensor.tensor import Tensor from ivy.functional.frontends.paddle.func_wrapper import ( to_ivy_arrays_and_back, ) def vflip(img, data_format="CHW"): if data_format.lower() == "chw": axis...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, ) import ivy.functional.frontends.numpy as np_frontend def fill_diagonal(a, val, wrap=False): if a.ndim < 2: raise ValueError("array must be at least 2-d") end = None if a.ndim == 2: # Explicit,...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, inputs_to_ivy_arrays, handle_numpy_out, ) def compress(condition, a, axis=None, out=None): condition_arr = ivy.asarray(condition).astype(bool) if condition_arr.ndim != 1: raise ivy.utils.exceptions....
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, inputs_to_ivy_arrays, handle_numpy_out, ) def diag(v, k=0): return ivy.diag(v, k=k)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, inputs_to_ivy_arrays, handle_numpy_out, ) def diagonal(a, offset, axis1, axis2): return ivy.diagonal(a, offset=offset, axis1=axis1, axis2=axis2)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, inputs_to_ivy_arrays, handle_numpy_out, ) def fill_diagonal(a, val, wrap=False): if a.ndim < 2: raise ValueError("array must be at least 2-d") end = None if a.ndim == 2: # Explicit, fast...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, inputs_to_ivy_arrays, handle_numpy_out, ) def indices(dimensions, dtype=int, sparse=False): dimensions = tuple(dimensions) N = len(dimensions) shape = (1,) * N if sparse: res = () else: ...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, inputs_to_ivy_arrays, handle_numpy_out, ) def put_along_axis(arr, indices, values, axis): ivy.put_along_axis(arr, indices, values, axis)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, inputs_to_ivy_arrays, handle_numpy_out, ) def take(a, indices, /, *, axis=None, out=None, mode="raise"): return ivy.take(a, indices, axis=axis, out=out, mode=mode)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, inputs_to_ivy_arrays, handle_numpy_out, ) def take_along_axis(arr, indices, axis): return ivy.take_along_axis(arr, indices, axis)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, inputs_to_ivy_arrays, handle_numpy_out, ) def tril_indices(n, k=0, m=None): return ivy.tril_indices(n, m, k)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, inputs_to_ivy_arrays, handle_numpy_out, ) def unravel_index(indices, shape, order="C"): ret = [x.astype("int64") for x in ivy.unravel_index(indices, shape)] return tuple(ret)
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import inspect import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, ) def diag_indices(n, ndim=2): idx = ivy.arange(n) res = ivy.array((idx,) * ndim) res = tuple(res.astype("int64")) return res
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import inspect import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, ) def indices(dimensions, dtype=int, sparse=False): return ivy.indices(dimensions, dtype=dtype, sparse=sparse) def mask_indices(n, mask_func, k=0): mask_func_obj = inspect.unwrap(mask_func) mask_...
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import inspect import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, ) def tril_indices(n, k=0, m=None): return ivy.tril_indices(n, m, k) def tril_indices_from(arr, k=0): return ivy.tril_indices(arr.shape[0], arr.shape[1], k)
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import inspect import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, ) def unravel_index(indices, shape, order="C"): ret = [x.astype("int64") for x in ivy.unravel_index(indices, shape)] return tuple(ret)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, ) def array(object, dtype=None, *, copy=True, order="K", subok=False, ndmin=0, like=None): ret = ivy.array(object, copy=copy, dtype=dtype) if ivy.get_num_dims(ret) < ndmin: ret = ivy...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, ) def asarray( a, dtype=None, order=None, *, like=None, ): return ivy.asarray(a, dtype=dtype)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, ) def copy(a, order="K", subok=False): return ivy.copy_array(a)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, ) def frombuffer(buffer, dtype=float, count=-1, offset=0, *, like=None): return ivy.frombuffer(buffer)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, ) def diag(v, k=0): return ivy.diag(v, k=k)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, ) def diagflat(v, k=0): ret = ivy.diagflat(v, offset=k) while len(ivy.shape(ret)) < 2: ret = ret.expand_dims(axis=0) return ret
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, ) def tril(m, k=0): return ivy.tril(m, k=k) def tri(N, M=None, k=0, dtype="float64", *, like=None): if M is None: M = N ones = ivy.ones((N, M), dtype=dtype) return ivy.tril(o...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, ) def triu(m, k=0): return ivy.triu(m, k=k)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, ) def vander(x, N=None, increasing=False): if ivy.is_float_dtype(x): x = x.astype(ivy.float64) elif ivy.is_bool_dtype or ivy.is_int_dtype(x): x = x.astype(ivy.int64) retu...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( outputs_to_frontend_arrays, to_ivy_arrays_and_back, handle_numpy_dtype, ) def arange(start, stop=None, step=1, dtype=None, *, like=None): return ivy.arange(start, stop, step, dtype=dtype)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( outputs_to_frontend_arrays, to_ivy_arrays_and_back, handle_numpy_dtype, ) def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0): ret = ivy.linspace(start, stop, num, axis=axis, endpoint=endpoint, dtype=dty...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( outputs_to_frontend_arrays, to_ivy_arrays_and_back, handle_numpy_dtype, ) def logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None, axis=0): if not endpoint: interval = (stop - start) / num stop -= interv...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( outputs_to_frontend_arrays, to_ivy_arrays_and_back, handle_numpy_dtype, ) def meshgrid(*xi, copy=True, sparse=False, indexing="xy"): # Todo: add sparse check ret = ivy.meshgrid(*xi, indexing=indexing) if copy: return [...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( outputs_to_frontend_arrays, handle_numpy_dtype, ) def empty(shape, dtype="float64", order="C", *, like=None): return ivy.empty(shape=shape, dtype=dtype) def empty_like(prototype, dtype=None, order="K", subok=True, shape=None): if shap...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( outputs_to_frontend_arrays, handle_numpy_dtype, ) def fromfunction(function, shape, *, dtype="float64", like=None, **kwargs): args = ivy.indices(shape, dtype=dtype) return function(*args, **kwargs)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( outputs_to_frontend_arrays, handle_numpy_dtype, ) def full(shape, fill_value, dtype=None, order="C", *, like=None): return ivy.full(shape, fill_value, dtype=dtype) def full_like(a, fill_value, dtype=None, order="K", subok=True, shape=None...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( outputs_to_frontend_arrays, handle_numpy_dtype, ) def eye(N, M=None, k=0, dtype="float64", order="C", *, like=None): return ivy.eye(N, M, k=k, dtype=dtype) def identity(n, dtype=None, *, like=None): return ivy.eye(n, dtype=dtype)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( outputs_to_frontend_arrays, handle_numpy_dtype, ) def ones(shape, dtype=None, order="C", *, like=None): return ivy.ones(shape, dtype=dtype) def ones_like(a, dtype=None, order="K", subok=True, shape=None): if shape: return ivy....
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( outputs_to_frontend_arrays, handle_numpy_dtype, ) def zeros(shape, dtype=float, order="C", *, like=None): return ivy.zeros(shape, dtype=dtype) def zeros_like(a, dtype=None, order="K", subok=True, shape=None): if shape: return ...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _arccosh( x, /, out=None, *, where=True, casting="same_kind", order="k", dty...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _arcsinh( x, /, out=None, *, where=True, casting="same_kind", order="k", dty...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _arctanh( x, /, out=None, *, where=True, casting="same_kind", order="K", dty...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _cosh( x, /, out=None, *, where=True, casting="same_kind", order="k", dtype=...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _sinh( x, /, out=None, *, where=True, casting="same_kind", order="k", dtype=...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _tanh( x, /, out=None, *, where=True, casting="same_kind", order="k", dtype=...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) import ivy.functional.frontends.numpy as np_frontend def diff(x, /, *, n=1, axis=-1, prepend=None, append=None): return ivy.diff(x, n=n...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) import ivy.functional.frontends.numpy as np_frontend def cumprod(a, /, axis=None, dtype=None, out=None): return ivy.cumprod(a, axis=axi...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) import ivy.functional.frontends.numpy as np_frontend def cumsum(a, /, axis=None, dtype=None, out=None): def nancumsum(a, /, axis=None, dty...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) import ivy.functional.frontends.numpy as np_frontend def prod( x, /, *, axis=None, dtype=None, out=None, keepdi...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) import ivy.functional.frontends.numpy as np_frontend def sum( x, /, *, axis=None, dtype=None, keepdims=False, o...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) import ivy.functional.frontends.numpy as np_frontend def trapz(y, x=None, dx=1.0, axis=-1): return ivy.trapz(y, x=x, dx=dx, axis=axis)
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _arccos( x, /, out=None, *, where=True, casting="same_kind", order="K", dtyp...
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import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _arcsin( x, /, out=None, *, where=True, casting="same_kind", order="K", dtyp...
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146,766
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _arctan( x, /, out=None, *, where=True, casting="same_kind", order="K", dtyp...
null
146,767
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _arctan2( x1, x2, /, out=None, *, where=True, casting="same_kind", order="K"...
null
146,768
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _cos( x, /, out=None, *, where=True, casting="same_kind", order="k", dtype=N...
null
146,769
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _deg2rad( x, /, out=None, *, where=True, casting="same_kind", order="K", dty...
null
146,770
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _degrees( x, /, out=None, *, where=True, casting="same_kind", order="K", dty...
null
146,771
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _rad2deg( x, /, out=None, *, where=True, casting="same_kind", order="K", dty...
null
146,772
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _sin( x, /, out=None, *, where=True, casting="same_kind", order="k", dtype=N...
null
146,773
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _tan( x, /, out=None, *, where=True, casting="same_kind", order="K", dtype=N...
null
146,774
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, from_zero_dim_arrays_to_scalar, ) def sinc(x): if ivy.get_num_dims(x) == 0: x = ivy.astype(x, ivy.float64) return ivy.sinc(x)
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146,775
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, from_zero_dim_arrays_to_scalar, ) def unwrap(p, discont=None, axis=-1, *, period=2 * ivy.pi): p = ivy.asarray(p) nd = p.ndim dd = ivy.diff(p, axis=axis) if discont is None: discont = period / 2 ...
null
146,776
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_out, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_casting, ) def _nextafter( x1, x2, /, out=None, *, where=True, casting="same_kind", order="...
null
146,777
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_out, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_casting, ) def _signbit( x, /, out=None, *, where=True, casting="safe", order="K", dtype=No...
null
146,778
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_out, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_casting, ) def _spacing( x, /, out=None, *, where=True, casting="same_kind", order="K", dty...
null
146,779
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _exp( x, /, out=None, *, where=True, casting="same_kind", order="K", dtype=N...
null
146,780
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _exp2( x, /, out=None, *, where=True, casting="same_kind", order="k", dtype=...
null
146,781
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _expm1( x, /, out=None, *, where=True, casting="same_kind", order="k", dtype...
null
146,782
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _frexp( x, /, out1_2=(None, None), out=(None, None), *, where=True, casting="sam...
null
146,783
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _ldexp( x1, x2, /, out=None, *, where=True, casting="same_kind", order="k", ...
null
146,784
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _log( x, /, out=None, *, where=True, casting="same_kind", order="K", dtype=N...
null
146,785
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _log10( x, /, out=None, *, where=True, casting="same_kind", order="k", dtype...
null
146,786
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _log1p( x, /, out=None, *, where=True, casting="same_kind", order="k", dtype...
null
146,787
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _log2( x, /, out=None, *, where=True, casting="same_kind", order="k", dtype=...
null
146,788
import ivy from ivy.functional.frontends.numpy.func_wrapper import ( to_ivy_arrays_and_back, handle_numpy_casting, handle_numpy_dtype, from_zero_dim_arrays_to_scalar, handle_numpy_out, ) def _logaddexp( x1, x2, /, out=None, *, where=True, casting="same_kind", order="...
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