id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
149,790 | from typing import Union, Optional
import jax
import jax.numpy as jnp
import ivy
from ivy import (
default_float_dtype,
is_float_dtype,
)
from ivy import promote_types_of_inputs
from ivy.functional.backends.jax import JaxArray
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
d... | null |
149,791 | from typing import Union, Optional
import jax
import jax.numpy as jnp
import ivy
from ivy import (
default_float_dtype,
is_float_dtype,
)
from ivy import promote_types_of_inputs
from ivy.functional.backends.jax import JaxArray
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
d... | null |
149,792 | from typing import Union, Optional
import jax
import jax.numpy as jnp
import ivy
from ivy import (
default_float_dtype,
is_float_dtype,
)
from ivy import promote_types_of_inputs
from ivy.functional.backends.jax import JaxArray
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
d... | null |
149,793 | from typing import Union, Optional
import jax
import jax.numpy as jnp
import ivy
from ivy import (
default_float_dtype,
is_float_dtype,
)
from ivy import promote_types_of_inputs
from ivy.functional.backends.jax import JaxArray
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
d... | null |
149,794 | from typing import Union, Optional
import jax
import jax.numpy as jnp
import ivy
from ivy import (
default_float_dtype,
is_float_dtype,
)
from ivy import promote_types_of_inputs
from ivy.functional.backends.jax import JaxArray
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
f... | null |
149,795 | from typing import Union, Optional
import jax
import jax.numpy as jnp
import ivy
from ivy import (
default_float_dtype,
is_float_dtype,
)
from ivy import promote_types_of_inputs
from ivy.functional.backends.jax import JaxArray
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
f... | null |
149,796 | from typing import Union, Optional
import jax
import jax.numpy as jnp
import ivy
from ivy import (
default_float_dtype,
is_float_dtype,
)
from ivy import promote_types_of_inputs
from ivy.functional.backends.jax import JaxArray
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
d... | null |
149,797 | from typing import Union, Optional
import jax
import jax.numpy as jnp
import ivy
from ivy import (
default_float_dtype,
is_float_dtype,
)
from ivy import promote_types_of_inputs
from ivy.functional.backends.jax import JaxArray
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
d... | null |
149,798 | from typing import Union, Optional
import jax
import jax.numpy as jnp
import ivy
from ivy import (
default_float_dtype,
is_float_dtype,
)
from ivy import promote_types_of_inputs
from ivy.functional.backends.jax import JaxArray
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
d... | null |
149,799 | from typing import Union, Optional
import jax
import jax.numpy as jnp
import ivy
from ivy import (
default_float_dtype,
is_float_dtype,
)
from ivy import promote_types_of_inputs
from ivy.functional.backends.jax import JaxArray
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
d... | null |
149,800 | from typing import Union, Optional
import jax
import jax.numpy as jnp
import ivy
from ivy import (
default_float_dtype,
is_float_dtype,
)
from ivy import promote_types_of_inputs
from ivy.functional.backends.jax import JaxArray
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
d... | null |
149,801 | from typing import Union, Optional
import jax
import jax.numpy as jnp
import ivy
from ivy import (
default_float_dtype,
is_float_dtype,
)
from ivy import promote_types_of_inputs
from ivy.functional.backends.jax import JaxArray
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
d... | null |
149,802 | from typing import Union, Optional
import jax
import jax.numpy as jnp
import ivy
from ivy import (
default_float_dtype,
is_float_dtype,
)
from ivy import promote_types_of_inputs
from ivy.functional.backends.jax import JaxArray
from ivy.func_wrapper import with_unsupported_dtypes
from . import backend_version
d... | null |
149,803 | import os
import jax
from typing import Union, Optional
import jaxlib.xla_extension
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.device import (
_shift_native_arrays_on_default_device,
Profiler as BaseProfiler,
)
def dev(
x: JaxArray,
/,
*,
as_native: bool ... | null |
149,804 | import os
import jax
from typing import Union, Optional
import jaxlib.xla_extension
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.device import (
_shift_native_arrays_on_default_device,
Profiler as BaseProfiler,
)
def _shift_native_arrays_on_default_device(*args, **kwargs)... | null |
149,805 | import os
import jax
from typing import Union, Optional
import jaxlib.xla_extension
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.device import (
_shift_native_arrays_on_default_device,
Profiler as BaseProfiler,
)
def clear_cached_mem_on_dev(device: str, /):
return Non... | null |
149,806 | import os
import jax
from typing import Union, Optional
import jaxlib.xla_extension
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.device import (
_shift_native_arrays_on_default_device,
Profiler as BaseProfiler,
)
def _dev_is_available(base_dev):
try:
jax.device... | null |
149,807 | import os
import jax
from typing import Union, Optional
import jaxlib.xla_extension
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.device import (
_shift_native_arrays_on_default_device,
Profiler as BaseProfiler,
)
def num_gpus() -> int:
try:
return len(jax.devi... | null |
149,808 | import os
import jax
from typing import Union, Optional
import jaxlib.xla_extension
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.device import (
_shift_native_arrays_on_default_device,
Profiler as BaseProfiler,
)
def _dev_is_available(base_dev):
def tpu_is_available() -> ... | null |
149,809 | import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from typing import Optional, Union, Sequence
import ivy
from ivy.functional.ivy.random import (
_check_bounds_and_get_shape,
_randint_check_dtype_and_bound,
_check_valid_scale,
)
from ivy.functional.backends.jax import JaxArray
from ivy.func_wra... | null |
149,810 | import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from typing import Optional, Union, Sequence
import ivy
from ivy.functional.ivy.random import (
_check_bounds_and_get_shape,
_randint_check_dtype_and_bound,
_check_valid_scale,
)
from ivy.functional.backends.jax import JaxArray
from ivy.func_wra... | null |
149,811 | import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from typing import Optional, Union, Sequence
import ivy
from ivy.functional.ivy.random import (
_check_bounds_and_get_shape,
_randint_check_dtype_and_bound,
_check_valid_scale,
)
from ivy.functional.backends.jax import JaxArray
from ivy.func_wra... | null |
149,812 | import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from typing import Optional, Union, Sequence
import ivy
from ivy.functional.ivy.random import (
_check_bounds_and_get_shape,
_randint_check_dtype_and_bound,
_check_valid_scale,
)
from ivy.functional.backends.jax import JaxArray
from ivy.func_wra... | null |
149,813 | import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from typing import Optional, Union, Sequence
import ivy
from ivy.functional.ivy.random import (
_check_bounds_and_get_shape,
_randint_check_dtype_and_bound,
_check_valid_scale,
)
from ivy.functional.backends.jax import JaxArray
from ivy.func_wra... | null |
149,814 | import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from typing import Optional, Union, Sequence
import ivy
from ivy.functional.ivy.random import (
_check_bounds_and_get_shape,
_randint_check_dtype_and_bound,
_check_valid_scale,
)
from ivy.functional.backends.jax import JaxArray
from ivy.func_wra... | null |
149,815 | import jax.lax as jlax
import jax.numpy as jnp
import ivy
from ivy.functional.backends.jax import JaxArray
from typing import Union, Tuple, Optional, Sequence
from ivy.functional.ivy.layers import (
_handle_padding,
_deconv_length,
_get_x_data_format,
)
def _handle_padding(x, strides, filters, padding):
... | null |
149,816 | import jax.lax as jlax
import jax.numpy as jnp
import ivy
from ivy.functional.backends.jax import JaxArray
from typing import Union, Tuple, Optional, Sequence
from ivy.functional.ivy.layers import (
_handle_padding,
_deconv_length,
_get_x_data_format,
)
def conv_general_dilated(
x: JaxArray,
filters... | null |
149,817 | import jax.lax as jlax
import jax.numpy as jnp
import ivy
from ivy.functional.backends.jax import JaxArray
from typing import Union, Tuple, Optional, Sequence
from ivy.functional.ivy.layers import (
_handle_padding,
_deconv_length,
_get_x_data_format,
)
def _get_tranpose_padding(
x_shape, filter_shape, ... | null |
149,818 | import jax.lax as jlax
import jax.numpy as jnp
import ivy
from ivy.functional.backends.jax import JaxArray
from typing import Union, Tuple, Optional, Sequence
from ivy.functional.ivy.layers import (
_handle_padding,
_deconv_length,
_get_x_data_format,
)
def conv_general_dilated(
x: JaxArray,
filters... | null |
149,819 | import jax.lax as jlax
import jax.numpy as jnp
import ivy
from ivy.functional.backends.jax import JaxArray
from typing import Union, Tuple, Optional, Sequence
from ivy.functional.ivy.layers import (
_handle_padding,
_deconv_length,
_get_x_data_format,
)
def _get_tranpose_padding(
x_shape, filter_shape, ... | null |
149,820 | import jax.lax as jlax
import jax.numpy as jnp
import ivy
from ivy.functional.backends.jax import JaxArray
from typing import Union, Tuple, Optional, Sequence
from ivy.functional.ivy.layers import (
_handle_padding,
_deconv_length,
_get_x_data_format,
)
def conv_general_dilated(
x: JaxArray,
filters... | null |
149,821 | import jax.lax as jlax
import jax.numpy as jnp
import ivy
from ivy.functional.backends.jax import JaxArray
from typing import Union, Tuple, Optional, Sequence
from ivy.functional.ivy.layers import (
_handle_padding,
_deconv_length,
_get_x_data_format,
)
def conv_general_dilated(
x: JaxArray,
filters... | null |
149,822 | import jax.lax as jlax
import jax.numpy as jnp
import ivy
from ivy.functional.backends.jax import JaxArray
from typing import Union, Tuple, Optional, Sequence
from ivy.functional.ivy.layers import (
_handle_padding,
_deconv_length,
_get_x_data_format,
)
def _get_tranpose_padding(
x_shape, filter_shape, ... | null |
149,823 | import jax.lax as jlax
import jax.numpy as jnp
import ivy
from ivy.functional.backends.jax import JaxArray
from typing import Union, Tuple, Optional, Sequence
from ivy.functional.ivy.layers import (
_handle_padding,
_deconv_length,
_get_x_data_format,
)
def _get_tranpose_padding(
x_shape, filter_shape, ... | null |
149,824 | import jax.lax as jlax
import jax.numpy as jnp
import ivy
from ivy.functional.backends.jax import JaxArray
from typing import Union, Tuple, Optional, Sequence
from ivy.functional.ivy.layers import (
_handle_padding,
_deconv_length,
_get_x_data_format,
)
from ivy.functional.frontends import set_frontend_to_... | null |
149,825 | import numpy as np
import jax.numpy as jnp
from typing import Optional, Union, Sequence, List
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.data_type import _handle_nestable_dtype_info
def as_native_dtype(
dtype_in: Union[jnp.dtype, str, bool, int, float, np.dtype],
) -> jnp.dt... | null |
149,826 | import numpy as np
import jax.numpy as jnp
from typing import Optional, Union, Sequence, List
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.data_type import _handle_nestable_dtype_info
from ivy.functional.frontends import set_frontend_to_specific_version
if ivy.is_local():
... | null |
149,827 | import numpy as np
import jax.numpy as jnp
from typing import Optional, Union, Sequence, List
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.data_type import _handle_nestable_dtype_info
from ivy.functional.frontends import set_frontend_to_specific_version
if ivy.is_local():
... | null |
149,828 | import numpy as np
import jax.numpy as jnp
from typing import Optional, Union, Sequence, List
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.data_type import _handle_nestable_dtype_info
class Finfo:
def __init__(self, jnp_finfo: jnp.finfo):
self._jnp_finfo = jnp_finfo
... | null |
149,829 | import numpy as np
import jax.numpy as jnp
from typing import Optional, Union, Sequence, List
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.data_type import _handle_nestable_dtype_info
def as_native_dtype(
dtype_in: Union[jnp.dtype, str, bool, int, float, np.dtype],
) -> jnp.dt... | null |
149,830 | import numpy as np
import jax.numpy as jnp
from typing import Optional, Union, Sequence, List
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.data_type import _handle_nestable_dtype_info
def as_ivy_dtype(
dtype_in: Union[jnp.dtype, str, int, float, complex, bool, np.dtype],
/... | null |
149,831 | import numpy as np
import jax.numpy as jnp
from typing import Optional, Union, Sequence, List
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.data_type import _handle_nestable_dtype_info
def as_ivy_dtype(
dtype_in: Union[jnp.dtype, str, int, float, complex, bool, np.dtype],
/... | null |
149,832 | import numpy as np
import jax.numpy as jnp
from typing import Optional, Union, Sequence, List
import ivy
from ivy.functional.backends.jax import JaxArray
from ivy.functional.ivy.data_type import _handle_nestable_dtype_info
ivy_dtype_dict = {
jnp.dtype("int8"): "int8",
jnp.dtype("int16"): "int16",
jnp.dtype(... | null |
149,833 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,834 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,835 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,836 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,837 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,838 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,839 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,840 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,841 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,842 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,843 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,844 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,845 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,846 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,847 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,848 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,849 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,850 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,851 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,852 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,853 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,854 | import importlib
import multiprocessing as _multiprocessing
from functools import reduce as _reduce
from numbers import Number
from operator import mul
from typing import Callable, Optional, Sequence, Tuple, Union
import jax
import jax.numpy as jnp
import numpy as np
import ivy
from ivy.func_wrapper import with_unsuppo... | null |
149,855 | import jax
from typing import Callable
import ivy
from ivy.func_wrapper import inputs_to_native_arrays
def inputs_to_native_arrays(fn: Callable) -> Callable:
def _inputs_to_native_arrays(*args, **kwargs):
"""Convert all `ivy.Array` instances in both the positional and keyword
arguments into `ivy.Na... | null |
149,856 | import jax
from typing import Callable
import ivy
from ivy.func_wrapper import inputs_to_native_arrays
def vjp(func: Callable, *primals):
def grad_fn(*x_in):
return ivy.to_native(
func(*ivy.to_ivy(x_in, nested=True)), nested=True, include_derived=True
)
primals_out, _vjpfun = ivy.o... | null |
149,857 | import jax
from typing import Callable
import ivy
from ivy.func_wrapper import inputs_to_native_arrays
def jvp(func: Callable, primals, tangents):
def grad_fn(*x_in):
return ivy.to_native(
func(*ivy.to_ivy(x_in, nested=True)), nested=True, include_derived=True
)
primals_out, tangen... | null |
149,858 | import jax.numpy as jnp
from typing import Optional, Union
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.backends.jax import JaxArray
from . import backend_version
def invert_permutation(
x: Union[JaxArray, list, tuple],
/,
) -> JaxArray:
x = jnp.array(x) if not ivy.is... | null |
149,859 | import jax.numpy as jnp
from typing import Optional, Union
import ivy
from ivy.func_wrapper import with_unsupported_dtypes
from ivy.functional.backends.jax import JaxArray
from . import backend_version
def lexsort(
keys: JaxArray,
/,
*,
axis: int = -1,
out: Optional[JaxArray] = None,
) -> JaxArray:... | null |
149,860 | import jax.numpy as jnp
from typing import Optional
from ivy.functional.backends.jax import JaxArray
def l1_normalize(
x: JaxArray,
/,
*,
axis: Optional[int] = None,
out: Optional[JaxArray] = None,
) -> JaxArray:
if not isinstance(x, JaxArray):
x = jnp.array(x)
if axis is None:
... | null |
149,861 | import jax.numpy as jnp
from typing import Optional
from ivy.functional.backends.jax import JaxArray
def l2_normalize(
x: JaxArray,
/,
*,
axis: Optional[int] = None,
out: Optional[JaxArray] = None,
) -> JaxArray:
if axis is None:
denorm = jnp.linalg.norm(x.flatten(), 2, axis)
else:
... | null |
149,862 | import jax.numpy as jnp
from typing import Optional
from ivy.functional.backends.jax import JaxArray
def lp_normalize(
x: JaxArray,
/,
*,
p: float = 2,
axis: Optional[int] = None,
out: Optional[JaxArray] = None,
) -> JaxArray:
if axis is None:
denorm = jnp.linalg.norm(x.flatten(), a... | null |
149,863 | import logging
import ivy
from ivy.functional.ivy.experimental.sparse_array import (
_is_valid_format,
_verify_bsc_components,
_verify_bsr_components,
_verify_coo_components,
_verify_csc_components,
_verify_csr_components,
)
The provided code snippet includes necessary dependencies for implemen... | Jax does not support sparse arrays natively. |
149,864 | import logging
import ivy
from ivy.functional.ivy.experimental.sparse_array import (
_is_valid_format,
_verify_bsc_components,
_verify_bsr_components,
_verify_coo_components,
_verify_csc_components,
_verify_csr_components,
)
def _verify_coo_components(indices=None, values=None, dense_shape=None... | null |
149,865 | import logging
import ivy
from ivy.functional.ivy.experimental.sparse_array import (
_is_valid_format,
_verify_bsc_components,
_verify_bsr_components,
_verify_coo_components,
_verify_csc_components,
_verify_csr_components,
)
def native_sparse_array_to_indices_values_and_shape(x):
logging.wa... | null |
149,866 | import jax.numpy as jnp
from typing import Optional, Tuple
from ivy.functional.backends.jax import JaxArray
def unravel_index(
indices: JaxArray,
shape: Tuple[int],
/,
*,
out: Optional[JaxArray] = None,
) -> Tuple[JaxArray]:
return jnp.unravel_index(indices.astype(jnp.int32), shape) | null |
149,867 | import math
from typing import Optional, Tuple, Sequence, Union
import jax.numpy as jnp
import jax.scipy.linalg as jla
from collections import namedtuple
from ivy.func_wrapper import with_supported_dtypes
from ivy.functional.backends.jax import JaxArray
import ivy
from ivy.functional.ivy.experimental.linear_algebra imp... | null |
149,868 | import math
from typing import Optional, Tuple, Sequence, Union
import jax.numpy as jnp
import jax.scipy.linalg as jla
from collections import namedtuple
from ivy.func_wrapper import with_supported_dtypes
from ivy.functional.backends.jax import JaxArray
import ivy
from ivy.functional.ivy.experimental.linear_algebra imp... | null |
149,869 | import math
from typing import Optional, Tuple, Sequence, Union
import jax.numpy as jnp
import jax.scipy.linalg as jla
from collections import namedtuple
from ivy.func_wrapper import with_supported_dtypes
from ivy.functional.backends.jax import JaxArray
import ivy
from ivy.functional.ivy.experimental.linear_algebra imp... | null |
149,870 | import math
from typing import Optional, Tuple, Sequence, Union
import jax.numpy as jnp
import jax.scipy.linalg as jla
from collections import namedtuple
from ivy.func_wrapper import with_supported_dtypes
from ivy.functional.backends.jax import JaxArray
import ivy
from ivy.functional.ivy.experimental.linear_algebra imp... | null |
149,871 | import math
from typing import Optional, Tuple, Sequence, Union
import jax.numpy as jnp
import jax.scipy.linalg as jla
from collections import namedtuple
from ivy.func_wrapper import with_supported_dtypes
from ivy.functional.backends.jax import JaxArray
import ivy
from ivy.functional.ivy.experimental.linear_algebra imp... | null |
149,872 | import math
from typing import Optional, Tuple, Sequence, Union
import jax.numpy as jnp
import jax.scipy.linalg as jla
from collections import namedtuple
from ivy.func_wrapper import with_supported_dtypes
from ivy.functional.backends.jax import JaxArray
import ivy
from ivy.functional.ivy.experimental.linear_algebra imp... | null |
149,873 | import math
from typing import Optional, Tuple, Sequence, Union
import jax.numpy as jnp
import jax.scipy.linalg as jla
from collections import namedtuple
from ivy.func_wrapper import with_supported_dtypes
from ivy.functional.backends.jax import JaxArray
import ivy
from ivy.functional.ivy.experimental.linear_algebra imp... | null |
149,874 | import math
from typing import Optional, Tuple, Sequence, Union
import jax.numpy as jnp
import jax.scipy.linalg as jla
from collections import namedtuple
from ivy.func_wrapper import with_supported_dtypes
from ivy.functional.backends.jax import JaxArray
import ivy
from ivy.functional.ivy.experimental.linear_algebra imp... | null |
149,875 | import math
from typing import Optional, Tuple, Sequence, Union
import jax.numpy as jnp
import jax.scipy.linalg as jla
from collections import namedtuple
from ivy.func_wrapper import with_supported_dtypes
from ivy.functional.backends.jax import JaxArray
import ivy
from ivy.functional.ivy.experimental.linear_algebra imp... | null |
149,876 | import math
from typing import Optional, Tuple, Sequence, Union
import jax.numpy as jnp
import jax.scipy.linalg as jla
from collections import namedtuple
from ivy.func_wrapper import with_supported_dtypes
from ivy.functional.backends.jax import JaxArray
import ivy
from ivy.functional.ivy.experimental.linear_algebra imp... | null |
149,877 | import math
from typing import Optional, Tuple, Sequence, Union
import jax.numpy as jnp
import jax.scipy.linalg as jla
from collections import namedtuple
from ivy.func_wrapper import with_supported_dtypes
from ivy.functional.backends.jax import JaxArray
import ivy
from ivy.functional.ivy.experimental.linear_algebra imp... | null |
149,878 | import math
from typing import Optional, Tuple, Sequence, Union
import jax.numpy as jnp
import jax.scipy.linalg as jla
from collections import namedtuple
from ivy.func_wrapper import with_supported_dtypes
from ivy.functional.backends.jax import JaxArray
import ivy
from ivy.functional.ivy.experimental.linear_algebra imp... | null |
149,879 | from typing import Optional, Tuple
import math
import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from ivy.functional.backends.jax import JaxArray
import ivy
def vorbis_window(
window_length: JaxArray,
*,
dtype: jnp.dtype = jnp.float32,
out: Optional[JaxArray] = None,
) -> JaxArray:
ret... | null |
149,880 | from typing import Optional, Tuple
import math
import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from ivy.functional.backends.jax import JaxArray
import ivy
def hann_window(
size: int,
/,
*,
periodic: bool = True,
dtype: Optional[jnp.dtype] = None,
out: Optional[JaxArray] = None,
)... | null |
149,881 | from typing import Optional, Tuple
import math
import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from ivy.functional.backends.jax import JaxArray
import ivy
def kaiser_window(
window_length: int,
periodic: bool = True,
beta: float = 12.0,
*,
dtype: Optional[jnp.dtype] = None,
out: ... | null |
149,882 | from typing import Optional, Tuple
import math
import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from ivy.functional.backends.jax import JaxArray
import ivy
def tril_indices(
n_rows: int,
n_cols: Optional[int] = None,
k: int = 0,
/,
*,
device: jaxlib.xla_extension.Device = None,
) ... | null |
149,883 | from typing import Optional, Tuple
import math
import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from ivy.functional.backends.jax import JaxArray
import ivy
def unsorted_segment_min(
data: JaxArray,
segment_ids: JaxArray,
num_segments: int,
) -> JaxArray:
# added this check to keep the sam... | null |
149,884 | from typing import Optional, Tuple
import math
import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from ivy.functional.backends.jax import JaxArray
import ivy
def unsorted_segment_sum(
data: JaxArray,
segment_ids: JaxArray,
num_segments: int,
) -> JaxArray:
# Used the same check which is use... | null |
149,885 | from typing import Optional, Tuple
import math
import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from ivy.functional.backends.jax import JaxArray
import ivy
def blackman_window(
size: int,
/,
*,
periodic: bool = True,
dtype: Optional[jnp.dtype] = None,
out: Optional[JaxArray] = Non... | null |
149,886 | from typing import Optional, Tuple
import math
import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from ivy.functional.backends.jax import JaxArray
import ivy
def trilu(
x: JaxArray, /, *, k: int = 0, upper: bool = True, out: Optional[JaxArray] = None
) -> JaxArray:
if upper:
return jnp.triu... | null |
149,887 | from typing import Optional, Tuple
import math
import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from ivy.functional.backends.jax import JaxArray
import ivy
def mel_weight_matrix(
num_mel_bins: int,
dft_length: int,
sample_rate: int,
lower_edge_hertz: float = 0.0,
upper_edge_hertz: flo... | null |
149,888 | from typing import Optional, Tuple
import math
import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from ivy.functional.backends.jax import JaxArray
import ivy
def unsorted_segment_mean(
data: JaxArray,
segment_ids: JaxArray,
num_segments: int,
) -> JaxArray:
ivy.utils.assertions.check_unsort... | null |
149,889 | from typing import Optional, Tuple
import math
import jax
import jax.numpy as jnp
import jaxlib.xla_extension
from ivy.functional.backends.jax import JaxArray
import ivy
def polyval(
coeffs: JaxArray,
x: JaxArray,
) -> JaxArray:
with ivy.PreciseMode(True):
promoted_type = ivy.promote_types(ivy.dtyp... | null |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.